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USING HIS TECHNIQUES WITHIN INSTRUCTIONAL PROGRAMS:

DATA FLOW DIAGRAMS To DESIGN INSTRUCTION
and

EXPERT SYSTEMS TO DELIVER EXPERTISE

by

Mary Jane Garrett

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Counseling,
Educational Psychology,
and Special Education

1988

ABSTRACT

USING MIS TECHNIQUES WITHIN INSTRUCTIONAL PROGRAMS:
DATA FLOW DIAGRAMS TO DESIGN INSTRUCTION
and
EXPERT SYSTEMS To DELIVER EXPERTISE

by

Mary Jane Garrett

This dissertation discussed the increased need for
efficient and effective instruction of high level intellec-
tual skills. It was noted that learning theories and in-
structional design theories had been developed that dealt
with cognitive processing, but that the tools currently used
by instructional designers did not readily facilitate the
teaching of cognitive processes. Problems with a current
design technique were discussed, and a need was determined
for instructional design techniques that permit developers
to apply learning and instructional theories more effective-
ly, especially in the indicated problem areas.

It was noted that business and industry had also been
affected by the Information Age. The use of data flow
diagrams in instructional design was demonstrated and the
following advantages were found: (a) they help to locate
the points in the learning process where teachers' help may
be needed for students to master the cognitive task; (b)
they show the type and position of information needed for

each process within the instructional system; (c) they aid

in analyzing the cognitive skill to be taught, identifying
the cognitive processes for higher order thinking skills,
and presenting the cognitive skill as a whole; (d) they
show the interrelationships among topics and processes of
instruction at various levels from course to lesson; and (e)
they provide a convenient way to explain a course to inter-
ested, content-area-naive, parties.

The use of expert systems to deliver expertise was
discussed. The limitations of expert systems and the dif-
ferences between expert systems developed for industry and
instruction were discussed. The steps necessary to develop
an expert system for the delivery of expertise within in-
structional programs was discussed and an example of the
development of an expert system to help students learn to
debug computer programs was given. Finally some cautions
about the use of expert systems as a part of instruction

were presented.

ACKNOWLEDGMENTS

I wish to express my appreciation to Dr. Lawrence
Alexander, chairman of my Doctoral Committee, for his en-
couragement and understanding. His counsel and judgement
were most influential in my years at Michigan State Univer-
sity, and his interpretation of often confusing policies and
practices was critical in the completion of my degree. The
amount of time he willingly devoted to the advancement of my
knowledge in instructional design and cognitive psychology
was staggering. I wish there were some way to repay him for
his kindness other than remembering his generosity when
working with my students.

I wish also to express my gratitude to Dr. Paul Slocum,
Dr. Robert Poland, and Dr. Richard McLeod, members of my
committee, who took time from their extremely busy schedules
to attend meetings, review papers, and offer advice. I feel
special gratitude to Dr. Dale Davis, from the University of
Michigan, Flint, for being willing to provide expertise in
Management Information Systems, providing support in my
approach to the topic, and for being part of my committee at
Michigan State University.

Two additional members of Michigan State University's
faculty have more than earned my gratitude: Dr. Joe Byers
and Dr. Stephen Yelon. Neither of these dedicated profes-

sors had any obligation to provide support for me in the

completion of my program, yet Dr. Byers' door was also open
for some friendly advice and Dr. Yelon even reviewed por-
tions of my dissertation and made numerous suggestions for
improvements.

I am also grateful to two former colleagues, Frank
Gregory and Paul Heavilin, who not only provided encourage-
ment and emotional support, but also proofread papers and
offered constructive criticism. Also, without the willing-
ness of Pat Gilbert to allow me to adjust my school schedule
to attend classes at Michigan State University, my advanced
education would have remained a dream.

Finally no words can express my indebtedness to my
parents, Andrew and Irma Tesner, whose love and confidence
in me gave me the desire to learn more, and my children,
Patrick and Paula Garrett, whose willingness to often "do

without their Mother" made this endeavor possible.

ii

TABLE OF CONTENTS

Chapter
LIST OF FIGURES O O O O O O O O O O O O O O O O O O O O

1 STATEMENT OF THE PROBLEM AND THE PURPOSE OF THIS

2

3

RESEARCH . . . . . . . . . . . . . .
RESEARCH QUESTIONS . . . . . . . . . .
Broad Questions to be Addressed .
Specific questions to be answered
SCOPE AND LIMITATION OF THIS RESEARCH
OVERVIEW OF THE DISSERTATION . . . . .

PROBLEMS WITH THE CURRENT INSTRUCTIONAL ANALYSIS

TECHNIQUES . . . . . . . . . . . . . . . . . . . .
Introduction . . . . . . . . . . . . . . . .
The Development of the Michigan Department of
Education' 3 Data Processing Curriculum Guide
Needs assessment . . . . . . . . . . . . . .
Analysis and formulation of the program's
goals and objectives . . . . . . . . . .
Occupational and (d) learning task analysis
Design of the course '. . . . . . . . . . . .
Implementation and evaluation . . . . . . . .
Inadequate Consideration for need for Expertise
and Knowledge . . . . . . . . . . . . . . . .
Insufficient Focus on Information . . . . . . . .
Limitations created by expressing cognitive skills
in a task format . . . . . . . . . . . . . .
Lack of Consideration for the Interrelationships
Among Topics of Instruction . . . . . . . . .
Lack of Convenient Ways to Explain a Course to
Interested, Content-Area-Naive, Parties . . .
Summary and Conclusion . . . . . . . . . . . . . .
A Possible Source of Instructional Analysis and
Design Tools . . . . . . . . . . . . . . . .

INSTRUCTIONAL DESIGN USING DATA FLOW DIAGRAMS . . .

Introduction . . . . . . . . . . . . . . . . .
Instructional Analysis and Design Using data flow
diagrams . . . . . . . ._. . . . . . . . . .
Data Flow Diagrams in Management Information
Systems . . . . . . . . . . . . . . . . . . .
An Example of Data Flow Diagrams in Instructional
Design . . . . . . . . . . . . . . . . . . .

iii

Page
.vii

\OQmUIUlH

11

13
15

15
17
17
17

20
23

25

26

27
29

30

32
32

32

36

39

4

EXPERT SYSTEMS . . . . . . .

Using data flow diagrams to Design Interactive
Video Courseware . . . . . . . . . . . . . .
Advantages of the Use of data flow diagrams . . .
Data flow diagrams help locate the points in
the learning process where help may be
needed . . . . . . . . . . . . . . . . .

Data flow diagrams show the type and position
of information needed for processes
within the instruction . . . . . . . . .

Data flow diagrams aid in analyzing the
cognitive skill to be taught . . . . . .

Data flow diagrams show the interrelation-
ships among topics and processes of
instruction . . . . . . . . . . . . . .

Data flow diagrams provide a convenient way
to explain a course to interested, con-
tent-area-naive, parties . . . . . . . .

Summary . . . . . . . . . . . . . . . . . . . . .

Introduction . . . . . . .
Definitions . . . . . . .
Classes of Expert Systems .
Limitations of Expert Systems . .
Reasons for Developing Expert Systems and
Examples . . . . . . . . . . . . . .
Expert systems could be developed for
codification, replication and
distribution of expertise . . . . . . .
Expert systems could be developed for
combining expertise from many sources .
Expert systems could be developed to amplify
expertise and thus produce dramatic
gains in productivity or in the creation
of new tasks, products, and services . .
Expert systems could be developed to avoid
significant costs in wasted resources
and capital . . . . . . . . . . . .
Expert systems could be developed to generate
complementary streams of revenue . . . .
Expert systems could be developed to solve a
variety of problems that are mainly
tractable . . . . . . . . . . . . . .
Examples that Illustrate Use for Expert Systems in
Education . . . . . . . . . . . . . . .
The Theoretical Potential for the Use of Expert
Systems in Education . . . . . . . . .
The theoretical body of knowledge of expert
systems . . . . . . . . .
The theoretical body of knowledge of learning
theory . . . . . . . . . . . . . . . . .

iv

53
57

57

58

59
60
61
61
64
64
65
66
68

72

73

74

74

75

76

76

78

83

83

85

Guidelines for Selecting Points for Expert System
Usage . . . . . . . . . . . . . . . .
Guidelines for Selecting Points for Expert System
Usage in Instruction . . . . . . . . . . . .
Business versus instructional use . . . . . .
A specific example from vocational data
processing . . . . . . . . . . . . .
Steps in Developing an Expert System in Business .
The Use of Shells in Developing Expert Systems . .
Steps in Developing an Expert System in Instruction
In developing an expert system, the purpose
must be kept clearly in mind . . . . . .
Major steps of development . . . . . . . . .
Developing an Expert System for Debugging Programs
Within the Vocational Data Processing
Program . . . . . . . . . . . . . . . .
Introduction and first two steps . . .
Selecting a shell . . . . . . . . . . .
Locating expertise and creating the mle

base . . . . . . . . . . .
Creating a prototype . . . . .
Testing the expert system . . .
Monitoring the expert system .

5 DISCUSSION AND RECOMMENDATIONS . . .
Summary of the Research Reported
Recommendations . . . . . . . . .
Cautions . . . . . . . . . . . . .

GLOSSARY OF TERMS IN THIS DISSERTATION . . . . . . . .

APPENDIX A . . . . . . . . . .
CURRENT INSTRUCTIONAL SYSTEMS AND DEVELOPMENTS
FIVE INSTRUCTIONAL SYSTEMS MODELS . . . . . .

Core Elements Andrews/Goodson Tasks . .
Stages of Instructional Design . . . . .
Courseware Design Model . . . . . . . . .

Michigan State University Instructional
Systems Procedure Model . . . . . . . . . . .

Information Relationships Among Learning

System Design Procedures.

Data Entry Task . . . . . . . . .
Computer Operations Task . . .

Computer Programming Task . . . . . . . . . .
CURRICULUM WORKSHEET . . . . . . . . . . . . . . .
Duty No. CP Task No. 2 . . . . . . . . .
Duty No. CP Task No. 5 . . . . . . . . .
Duty No. C? Task No. 11 . . . . . . . .
Duty No. CP Task No. 15 . . . . . . . .

87

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91

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96
98

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98

102
102
103

104
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105
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114
114
121
126

127

131
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133
134

136

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143
146
146
150
154
158

APPENDIX B . . . . . . . . . . . . . . . . . . . . .
DATA FLOW DIAGRAMS FOR DEVELOPING A COMPUTER

PROGRAM . . . . . . . . . . . . . . . . . . .

Designing a Computer Program . . . . . . . .

Define the Problem 1.0 . . . . . . . . . . .

Define specific outputs 2.0 . . . . . . . . .

Define specific inputs 3.0 . . . .
Define processing sequence and detailed

process 4.0 . . . . . . . . . . . . . .

Represent process specifications graphically

SOO O O O O O O O O O O O O O O O O O O

Develop program detail code 6.0 . . . .

Test program 7.0 . . . . . . . . . . . . . . .
Debug Program 8.0 . . . . . .
Evaluate Program 9.0 . . . . . . . . . . . . .

APPENDIX C O O O O O O O O O O O O O O O O O O
AN EXPERT SYSTEM AID TO DEBUGGING BASIC PROGRAMS .

APPENDIX D O O O O O O O O O O O O O O O O O O O O O O
Checklist for Data Flow Diagrams in Instructional
Des ign O O O O O O O O O O O O O O O O O O O

APPENDIX E O O O O O O O O O O O O O O O O O O O O O O
Data flow diagrams for a part of a veterinary

medicine course '. . . . . . . . . . . . . . ;

PAIN AND ITS TREATMENT IN VETERINARY
MEDICINE 1. 0 .. . . . . . .
PAIN AND ITS CONSEQUENCES 1.1 .
SPECIFIC RESPONSES TO PAIN 1.1.4
TYPES OF PAIN CONTROL 1.2 . . .
OPIATES AND OPIATE RECEPTORS 1.3 .
AGONIST/ANTAGONIST AND NARCOTIC DRUGS 1.4 .
INSTRUCTIONAL DICTIONARY . .'. . . . . . . . . .
Methods of Controling Pain in Veterinary
Medicine . . . . . . . . . . . . . . . .

APPEND I X F O O O O O O O O O O O O O O O O O
PROCEDURES FOR DESIGNING AND DEVELOPING
INTERACTIVE VIDEO INSTRUCTION . . . . . . . .

List of References . . . . . . . . . . . . . . . . . .
General References . . . . . . . . . . . . . . . .

vi

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176

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216
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248

Figure 1:

Figure 2:
analys

Figure 3:

LIST OF FIGURES

Instructional Systems Model . .

is process . . . . . . . . . .

Overview of the occupational/task

Relationships Between Occupational

Analysis and Program and Course Development

Figure 4: Commonly used symbols in data flow
diagrams . . . . . . . . . . . . .
Figure 5: Analysis of the Vocational Data
Processing Program: An Overview of the
System . . . . . . . . . . . . . . . .
Figure 6: Designing a Computer Program . .
Figure 7: Define the problem 1. 0 . . . . .
Figure 8: Determine type of output 1. 2 . .
Figure 9: Method of Controlling Pain in

Veterinary Medicine . . . . . . . . .

Figure 10:
Figure 11:

Tasks
Figure 12:
Figure 13:
Figure 14:

Debug Program 8. 0 . . . . . .

Comparison of Core Elements and Common

Stages of Instructional Design
Courseware Design Model . . .
Michigan State University

Instructional Systems Procedure Model .

Figure 15:

Information Relationships Among

Learning System Design Procedures. .

Figure 6:
Figure 7:
Figure 16:
Figure 17:
Figure 18:

Designing a Computer Program .
Define the Problem 1.0 . . . .

Define specific outputs 2.0 .
Define specific inputs 3.0 .
Define processing sequence and

detailed process 4.0 . . . . . . . .
Represent process specifications
graphically 5.0 . . . . . . . . . . .

Figure 19:

Figure 20:
Figure 21:
Figure 10:
Figure 22:
Figure 23:

Figure 24:
Figure 25:
Figure 26:
Figure 27:
Figure 28:

DRUGS

Develop program detail code 6.0
Test program 7.0 . . . . . . .
Debug Program 8. 0

Evaluate Program 9. 0 . . . . .

PAIN AND ITS TREATMENT IN VETERINARY
MEDICINE 1O 0 O O O O O O O O O O O O

PAIN AND ITS CONSEQUENCES 1.1 .

SPECIFIC RESPONSES TO PAIN 1.1.4.

TYPES OF PAIN CONTROL 1.2 . . .

OPIATES AND OPIATE RECEPTORS 1.3.

AGONIST/ANTAGONIST AND NARCOTIC

104 O O O O O O O O O O O O O O

vii

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.225

CHAPTER 1

STATEMENT OF THE PROBLEM AND THE PURPOSE OF THIS STUDY

With the advent of the Information Age new knowledge is
being produced at an ever increasing rate. Consequently,
efficient and effective education is becoming increasingly
important as a means for communicating this new knowledge.
This has placed an added burden on teachers who are expected
to teach more content at higher skill levels. In addition,
schools are expected to provide instruction in sex, drugs
and careers, areas that, in the past, were never their
responsibility. To meet these demands, educators need
better tools and techniques for planning and delivering
instruction. Resnick (1963, p. 439) suggests "Programmed
instruction offers a means of coping with the universally
acknowledged teacher overload". Reigeluth (1983) states
that if we can develop highly effective instructional re-
sources, then we can free some of the teacher's time to work
on the social, psychological, emotional, and moral develop-
ment of our children and prepare them better for living in
the Information Age.

Business has an analogous problem as a consequence of
our entry into the Information Age, viz, to manage more
information, in more areas, at a higher level of application

so that not only are day-to-day transactions processed, but

2
all levels of management are supplied with information and
supported in the use of technological tools for decision
making. To alleviate these problems, industry has adopted
the techniques of Management Information Systems (MIS), a
branch of computer science/data processing that is concerned
with the organization and coordination of information.

MIS has developed two techniques to deal with the need
for better planning of information systems and more effi-
cient delivery of organized information. These are struc-
tured design methodology, such as data flow diagrams, and
expert systems. Structured design methodology uses systems
concepts to analyze and describe an information system as
functional subsystems and to define the boundaries of and
interfaces between each subsystem. Expert systems are com-
puter programs that simulate the cognitive processes of a
human expert.

Because both education and business systems have simi-
lar problems, involving efficient handling of large amounts
of information, it is reasonable to inquire whether MIS
techniques of data flow diagrams and expert systems might be
used profitably in education. Perelman (1987) comments that
recent changes in instruction have been facilitated by the
use of advanced information technology to design, manage,
and deliver instruction. However, adaptation and transfer

‘of techniques from other fields to the field of instruction

3
should not be done without careful consideration of the
unique constraints in the field of education.

Although current instructional design techniques apply
well to the teaching of learning objectives, such as know-
ledge, comprehension, and application, from the lower levels
of Bloom's (1950) taxonomy, they do not apply well to the
teaching of higher level cognitive skills, such as analysis,
synthesis, and evaluation. In addition, current design
techniques have several problems that a designer of instruc—
tion should consider when attempting to improve instruction:
(a) inadequate consideration for need for expertise and
knowledge, (b) insufficient focus on needed information, (c)
limitations created by expressing cognitive skills in a task
format, (d) lack of consideration for the interrelation-
ships among topics and processes in the instruction, and (e)
lack of convenient ways to explain a course to interested,
content-area-naive, parties. The tools used in designing
instructional systems affect the efficiency of the instruc-
tion produced. Instructional design tools need to be ana-
lyzed and improved. These problems are discussed in more
detail in Chapter II.

The purpose of this dissertation is to investigate the
adaptability of M18 techniques to the design of instruc-
‘tional systems. Two MIS techniques, data flow diagrams and
'expert systems, are examined to determine the potential

utility of these techniques in the design and delivery of

4
instructional systems. To examine this potential utility, a
demonstration is provided of how they might be used in a
particular instructional system, namely teaching programming
in a secondary level vocational data processing course. A
second demonstration of the use of data flow diagrams in the
design of an interactive video course on pain control in

veterinary medicine is also made.

1).

2).

3).

4).

5).

QUESTIONS CONSIDERED IN THIS STUDY

t' s o Addr s

Might the MIS design tool, data flow diagrams, be used
to provide information about the relationships between
major chunks of instruction, that is courses, units,
chapters, and lessons: or the major cognitive processes
within the chunks?

Might the MIS design tool, data flow diagrams, indicate
what information might be needed by students at various
points of instructional programs?

How might the use of data flow diagrams to design MIS
systems be modified to use data flow diagrams to design
instructional systems?

When the objective is to teach complex cognitive
processes such as problem solving, might data flow
diagrams indicate specific points in an instructional
program where individualized expert help might be
provided by an expert system?

How might the MIS techniques for the development and
use of expert systems be modified to use these tech-
niques for the development of expert systems for in-

struction?

Specific questions to be answered

How might the use of data flow diagrams in the design
of a particular secondary vocational data processing
course provide information about the relationships
between major chunks of instruction, that is courses,
units, chapters, and lessons; or the major cognitive
processes within the chunks?

How might data flow diagrams used to design a particu-
lar secondary vocational data processing course indi-
cate what information might be needed by students at
various points of the instructional program?

How was the use of data flow diagrams to design MIS
systems modified to use data flow diagrams to design a
particular data processing course?

How might data flow diagrams, used to design a particu-
lar instructional program to teach the problem solving
skill, computer programming, indicate potential points
in the instruction where expert systems might be used
to provide students with expert help?

How were steps used to develop MIS expert systems
modified to develop an expert system to help teach
students in the data processing course how to debug

Basic computer programs?

SCOPE AND LIMITATION OF THIS STUDY

This feasibility study will seek to demonstrate:

(a) that data flow diagrams might be used in instructional
design to provide information that is useful in the anal-
ysis, design, and development of instruction: (b) that data
flow diagrams might indicate where expert systems may be
appropriate in an instructional program involving the teach-
ing of higher order intellectual skills: and (c) that expert
systems might be used to deliver expert instruction for
secondary students. To show that these benefits are pos-
sible, specific examples using a vocational data processing
program and an interactive video course on pain control in
veterinary medicine were developed.

The study presented in this paper has four major limit-
ations: First, only two examples of the use of data flow
diagrams were presented and only one expert system was
developed. The limitations of generalizations from one or
two examples is obvious. The two demonstrations presented
involved computer applications. Since the tools used in the
instructional design were adapted from the field of computer
science, the question of the influence of common domain
specific characteristics must be raised. Third, the study
was concerned with feasibility. There was no attempt to
test empirically the efficiency of the use of data flow

diagrams or the effectiveness or generalizability of the

8
specific expert system designed. Fourth, only the develop-
ment of a data processing curriculum was examined to deter-
mine the problems with instruction developed with the limi-
tations of the current instructional design and analysis

tools. These issues will be left for additional study.

OVERVIEW OF THE DISSERTATION

This dissertation is concerned with the feasibility of
transferring system design techniques from MIS to the design
of instructional systems. It does not involve any empirical
test of these techniques. Consequently, the format differs
from the format followed by the typical empirical research
dissertation. First, the inadequacies of current instruc-
tional design techniques used to develop the State of Michi-
gan's Vocational Data Processing Curriculum Guide are pre-
sented. Then each of the two techniques from MIS that are
being considered for transfer to instructional design are
presented, along with a demonstration of how each might be
used in the design of instruction. A discussion of the
modifications that this researcher found necessary to trans-
fer the techniques to the instructional design of the two
systems considered and the benefits of the techniques when
used in those instructional designs are presented. Specifi-
cally:

Chapter 2 discusses the problems with the current in-
structional system analysis and design techniques that were
found when the development of a data processing curriculum
was examined.

Chapter 3 describes the MIS structured design tech-
nique, data flow diagrams, indicates how they are used in

information systems design, and demonstrates how they might

10
be used to design a vocational data processing instructional
system. In addition, a brief summary is given of the use of
data flow diagrams in the design of instructional courseware
using interactive video. A demonstration is presented of
the use of data flow diagrams in the development of inter-
active video courseware for pain relief in veterinary medi-
cine.

Chapter 4 describes the MIS delivery technique, expert
systems, indicates the different types of expert systems and
their uses, and indicates how expert systems are developed
and used by industry. Then the business use of expert sys-
tems is contrasted with potential instructional usage and
the design and development of an expert system for use in a
vocational data processing instructional system is demon-
strated.

Chapter 5 presents the conclusions and suggestions for
further study.

A Glossary of terms used may be found before the appen-

dices.

CHAPTER 2

PROBLEMS WITH THE CURRENT INSTRUCTIONAL ANALYSIS TECHNIQUES

W

Education has always sought to provide effective and
efficient instruction, but with the entry of our society
into the Information Age, pressure increased for education
to communicate new knowledge at higher levels and increasing
rates. Instruction, according to R. Gagne (1985), deals
with the deliberate arrangement of events in the learner's
environment for the purpose of making learning happen effec-
tively. Therefore, to meet the instructional challenges of
the Information Age, educators must develop efficient and
effective ways of arranging the instructional events in the
learner's environment, including those events that will lead
to the development of higher order thinking skills.

Efficient instruction is dependent not only on the
sophistication of underlying theories, but also on the tech-
nology for applying these theories. Although behavioral
learning theories predominated in American educational
psychology for most of this century, in recent years learn-
ing theories incorporating cognitive theories have been
developed. These theories provide descriptions of effective
instruction that include information processing and higher

order thinking skills (Ausubel, 1968: Bruner, 1960;

11

12
R. Gagne, 1985). Instructional design, the technology that
applies learning theory to instruction, has also shifted
from a behavioral science orientation, where the emphasis
was to promote a student's overt performance by the manipu-
lation of stimulus materials, to cognitive science orienta-
tion, where the emphasis is to promote cognitive processing
(Merrill, Kowallis & Wilson, 1981). Currently there are
several good instructional design theories that include
techniques for dealing with higher order intellectual skills
(Collins & Stevens, 1983; Gagne & Briggs, 1979; Landa, 1982;
Merrill, 1983: Reigeluth, 1983; Reigeluth & Stein, 1983:
Scandura, 1983).

Since good learning and instructional design theories
exist, the problems encountered in attempting to design
efficient instruction appear to lie not in the theories, but
in the tools and techniques developed to apply those
theories. As Merrill, Kowallis and Wilson (1981) noted,
”models for the development of instruction are surprisingly
lacking in prescriptions that suggest how to execute the
various steps in the model" (P. 300).

To examine more clearly the limitations of the tools
used by current instructional design techniques, this chap-
ter discusses the development of the Michigan Department of
Education's Data_2rgQgggipg_gg;;igglum_§uig§ using an in-
structional systems model modified for vocational courses.

As a vocational data processing instructor in Michigan, this

13
researcher took part in the development of the Curriculum
Guide. After discussing the process of developing the
Guide, selected portions of the curriculum produced are
examined and the following problems are discussed: (a)
inadequate consideration for need for expertise and know-
ledge, (b) insufficient focus on needed information, (c)
limitations created by expressing cognitive skills in a task
format, (d) lack of consideration for the interrelation-
ships among topics and processes in the instruction, and (e)
lack of convenient ways to explain a course to interested,
content-area-naive, parties. Finally this chapter discusses
a possible source of instructional analysis and design tools

and techniques that may alleviate these problems.

,- a; - opuen of e tic f... u-.. u'! 9 _1- . on's
s'n r ' u u Gu
The development of the Michigan Department of Educa-

tion's Dutu Processing Qurriculuu Guide is described by the
Instructional Systems Model shown in Figure 1. Note that
the main components in that model are (a) needs assessment,
(b) analysis and formulation of the program's goals and
objectives, (c) occupational analysis, (d) analysis and
formulation of learning tasks, (e) design of the course, and
(f) implementation and evaluation. To indicate that the

Instructional System's Model is typical of current

14

 

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instructional systems design models, a representative set of
instructional systems design models can be found in Figures
12-16 respectively in Appendix A: (a) Richey's (1986) core
elements compared to Andrews/Goodson's tasks (1980); (b)
Briggs and Wagner's (1981) stages of design: (c) Roblyer
and Hall's (1985) courseware design model: (d) Hamreus's
(1968) instructional systems procedure model: and (e) Davis,
Alexander and Yelon's (1974) information relationships among
learning system design procedures.

In order to show that even though the Instructional
Systems Model was followed completely, there were still
problems with the curriculum produced, each component of the
process is discussed in detail:

(a) Needs assessment. Surveys of randomly selected
employers taken for the needs assessment component of the
development of the Data Processing Curriculum showed that
the number of new jobs in the data processing field was
increasing each year and that employers anticipated that the
number would continue to increase in the foreseeable future.
Thus, from both the employee and the employer's prospective,

there was a need for a vocational data processing curricu-

lum.
(b) a s's r ram' als
and ngaatives. The Data Procesaiug Durriculum Guide did

not contain a clear statement of the program's goal. In-

stead it made the statement that the program's ”focus" was

16

 

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17
occupational preparation in the areas of data entry, com-
puter operations, and computer programming. From this,
statement, the course objectives were inferred. In no place
were they directly stated.

(c) Dgguparigual and (d) learning task analyais. The
two analysis processes were combined and the resulting
process is shown in detail in Figure 2. The outcomes of
these processes were the data entry, computer operations,
and programming task lists presented in Appendix A.

(e) Dasign of rhe course. The details of how the
occupational analysis was then used in the course develop-
ment process are shown in Figure 3. Vocational Data Proces-
sing teachers throughout the State of Michigan were asked to
provide appropriate learning and teacher activities to teach
students the occupational tasks. This researcher was part
of a three member team that reviewed some of the data entry
activities and selected those believed most appropriate.
After testing in several schools and skill centers, the
learning tasks were revised where necessary. Some of the
curriculum worksheets that were developed for the program-
ming portion of the data processing curriculum guide are
presented in Appendix A.

(f) Winn- Except in those
schools that tested the materials, the implementation and
evaluation of the data processing course was left to the

schools and skill centers that used the curriculum guide.

zo-dp-mommo GOG

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— DUTY STATEMENT ‘A'I

 

 

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18

    

All duty statements
are considered as

input for developing
program description
and program goals.

  

     

   

Some of the duty
statements are
considered as input
for course description

  
 
    
   

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statements will be
incorporated in other
courses in the
program.

   

   
     

 
 
   

      
 

These same duty
statements are

reflected in the units
of instruction.

    
   
    

  
 

Tasks associated with
these duty statements
provide input for
developing pert. obj.
and identifying
content (what is to be
_ taught).

 
 
   

and course objectives.

   

 
   

 
    
  

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Course Description

 

 

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Figure 3: Relationships between Occupational Analysis and Program 8- Course Development

19

Clearly the development of the Dara Erocessiug
Qurrigulum_§uiua followed the steps of sound instructional
design and development theories. In addition, the materials
developed were tested by many experienced teachers with many
different types of equipment and students with varying de-
grees of ability. Informal discussions between this re-
searcher and, on the one hand, axpariaugaa data processing
teachers, and on the other hand, course advisors, who are
businessmen experienced in the area of data processing,
indicated that the curriculum guide was thorough and help-
ful. However, when working with inexperienced teachers,
counselors, administrators, and parents, this researcher
found that they do not understand the guide and they can not
properly use it.

The different reactions to the Curriculum Guide by
experienced and inexperienced people can not be ascribed to
inadequate underlying theory. An alternative explanation is
that the developmental process is inadequate in that the
design and developmental tools used did not produce suffi-
cient information for the inexperienced user. This suggests
the need for information in a usable form for the inexper-
ienced user.

The specific inadequacies of the design and development

tools are now discussed.

20

meatless:
Most cognitive psychologists agree that experts and

novices in any field differ in the amount of domain-specific
knowledge they possess and in the strategies that they apply
to the knowledge base in solving problems (E.D. Gagne, 1985:
Glaser, 1984; Mayer, 1983: Merrill, Kowallis, & Wilson,
1981). During the learning processes, practice with succes-
sive presentations of novel problems is necessary for stu-
dents to develop progressively more expert cognitive strate-
gies and teachers must provide students with feedback as to
the efficiency and effectiveness of the strategies used
(Collins 8 Stevens, 1983: Landa, 1982: Reigeluth & Stein,
1983). But this implies that when practice exercises for
cognitive strategies are developed, instructional designers
must attempt to locate the points in the instructional
process where the typical learner must be supplied with
expert help to efficiently complete the problem solution.
Thus, it is necessary to satisfy the student's need for both
expert knowledge and problem-solving strategies guring the
W.

Notice that the curriculum worksheets for programming
in the Guide attempt to tell teachers how to do this. In
addition, note the use of the action verbs in the teacher
activities: assign readings, provide examples, describe the

process, hand out samples, explain the use, lead a

21

discussion, demonstrate, place the solution on the chalk-
board. For experienced teachers, this listing of activities
with action verbs is sufficient. But for inexperienced
teachers attempting to teach cognitive skills such as pro-
gramming, presenting the activities alone misses the criti-
cal information of uaau to provide students with expert help

e e in e task.

However, when most inexperienced teachers attempt to
teach students behavioral skills such as data entry, then
having only activities with action verbs is not a problem.
For example, consider the tasks for data entry. The major-
ity of the tasks begin with "manipulate". The few that
begin with "analyze" are really only comparing a given
activity to a list of possible activities and picking the
ones that match. These are skills that can easily be des-
cribed and taught using behavioral models and techniques.

It is difficult to develop an instructional guide for
teaching cognitive strategies. One difficulty stems from
the fact that cognitive operations are unobservable and
automated to the extent that their performers are often
unaware or only partially aware of them (Resnick, 1987).
Thus, although vocationally certified teachers have adequate
practical content area experience, they often lack experi-
ence in teaching the cognitive skills involved. In fact,
they are often unaware of the cognitive skills that are

involved in programming, and usually are unaware of the

22
points within the instructional process at which students
need the teachers' help in developing those cognitive
skills. Yet nowhere do the curriculum worksheets tell
teachers of that need.

A second difficulty stems from the fact that students
are not passive receptors of knowledge, but actively inter-
pret incidents in the learning situation with a large set of
preexisting ideas that impose some kind of meaning on what
they are learning (Norman, 1980: Resnick, 1976). Therefore,
instructional methods must be adapted to the individual stu-
dent's interpretations of that instruction. Experienced
teachers know the points at which to watch for student
misinterpretations of the instruction. Inexperienced teach-
ers often fail to note the occurrence of student misinter-
pretations that will make learning more difficult for the
students as they progress to more challenging material.
Designing instruction that takes into account the points at
which students need help and students' idiosyncratic inter-
pretations of the instruction is one of the greatest chal-
lenges for educators.

But, despite these difficulties, some researchers have
developed instructional methods that provide students with
expert help as students develop cognitive strategies (Baker
8 Brown, 1984; Bereiter, 1985: Palincsar, Brown, 8 Martin,

1987). In addition, Collins and Stevens (1983) have

23
developed a theory of instruction, called Inquiry Teaching,
that provides students with expert help when it is needed.
A major characteristic of inquiry teaching is that a des-
criptive theory of expert performance, that is a detailed
report of what, how, and why something is done, is in fact a
prescriptive theory of instruction, that is a set of direc-
tions for the learner to follow to reach the desired goal of
learning, for the non-expert performer.

These theoretical developments are a further indication
that the problem is not the fault of instructional design
theory, but that instructional design tools and techniques
are needed that systematically indicate the specific points
in an instructional program where expert help is likely to
be required. Unfortunately, even if inexperienced teachers
know where students are likely to require expert help, often
they can not find time to provide this help. Instructional
delivery methods are needed that can make that help avail-

able to students in a timely manner.

MW

In today's Information age society, there is simply too
much to know for people to keep current on everything.
Instead of attempting to "know" everything about a given
subject, it makes sense to consult up-to-date references

(Adams & Imhof, 1987). For example, modern data processing

24
shops provide their programmers, who are professionals, with
manuals, standards, and libraries of existing code.

However, consider how the vocational Data Processing
Currigulum_§uiga handles the information that students must
have in order to program. Note the key phrases concerning
needed information in the programming tasks described on the
worksheets in appendix A: "using a knowledge of data pro-
cessing equipment and techniques" (CP-Z), "using a knowledge
of programming techniques" (CP-5), and "using a knowledge of
the specific language" (CP-11 and CP-15). These phrases
imply that it is necessary for students to know this infor-
mation in order to perform the task, that is, knowing this
information is prerequisite to completing the tasks. In
other words, students must know this information instead of
being provided with the information when it is needed.

Carroll (1976), Scandura (1983), and Snelbecker (1983)
all stressed the need in instruction to consider the infor-
mation students need in order to process new knowledge and
apply existing knowledge. Moreover, when information is
presented within the context of its use, students are likely
to store that information in a manner consistent with the
subject matter structure (Bruner, 1960). Therefore, it may
be inferred that not only is it But necessary for students
to know all the information necessary to complete tasks
Dafgra they attempt to complete the tasks, learning the

information before it is used may even be detrimental to

25
cognitive processing. However, nowhere in the Dara Drocess—
1ng_§urr1gu1um_§uiga is there any indication of what infor-
mation should be ayailable to the students as they attempt
to program.

u 1 ct: -a -- 3 ex-ress . use, v- :ki a: . . ask
IQIEQI_

. Olson (1973) pointed out that cognitive skills such as
making discoveries, speaking convincingly, writing effec-
tively, and social and ethical skills--cannot be taught
gxpligirly because the algorithms underlying them are not
known, or where known, are too complex to communicate effec-
tively. Yet certainly these important skills can be taught
by using instructional techniques such as "thinking out
loud", modeling, demonstrating, and providing feedback in
practice sessions (Baker & Brown, 1984: Bereiter, 1985:
Gagne, 1985: Palincsar, Brown, & Martin, 1987: Resnick,
1987). A common characteristic of these instructional
techniques for teaching cognitive skills is that they teach
the skill as a whole.

However, the Curriculum Guide lists tasks that are
components of cognitive skills without any indication of how
they work together to form a complete skill. This may not
be a problem for experienced teachers, but inexperienced
teachers may teach only the component tasks instead of the

skill as a whole.

26

Experienced teachers know that for cognitive skills,
instruction should start with a broad description of the
skill and then, level by level, should establish the com-
ponent subskills within the context of the complete skill
until eventually the students are presented with the lowest
level of tasks. To help inexperienced teachers teach this
way, instructional design should use techniques that analyze
the cognitive skill level by level, focusing on information
needed, cognitive processes, that is points where students
store, retrieve, organize, apply, or transfer information,
and the relationships among the processes. In addition,
instructional guides thus developed should convey this
information to teachers. This level by level approach is
the type of instructional design technique prescribed in
Reigeluth and Stein's (1983) Elaboration Theory. If the
Curriculum Guide were to convey component skill information
using a technique that clearly showed the part that each
task played in forming the complete skill, then inexperienc-
ed teachers might more effectively teach complex cognitive

skills such as programming.

‘_-. 0! 0 1‘ 1‘ ' a _- S 0‘ iJJ'l'

Most of the learning and instructional design theorists
consider interrelationships among the topics of instruction,

the structure of the subject matter, and previous knowledge

27
of the students very important (Ausubel, 1968; Bruner, 1960;
R. Gagne, 1985: Landa, 1982: Knirk & Gustafson, 1986:
Scandura, 1983; Reigeluth & Stein, 1983). Bruner (1960)
stated the importance of relationships in instruction most
succinctly with the comment that "To learn [subject matter]
structure, in short, is to learn how things are related" (p.
7). Therefore, instructional design should use techniques
that clearly show the interrelationships among the topics
and processes.

Yet nowhere in the Data Processing Curriculum Guide are
any of the relationships among the topics and processes
shown. There is no indication that data entry, computer
operation, and programming skills share common components.
There is no indication of the sequence in which the tasks
should be taught. Experienced teachers know the importance
of such interrelationships and convey them to their
students. Determining the interrelationships should be an
important part of the instructional design process and
conveying those interrelationships to teachers should be a

routine part of instructional development.

,_. -' 0! e_'- W. s o x-U. I a ou_ e to t- -: e-
- e - t e
In the section of this chapter where the development of
the Curriculum Guide was discussed, this researcher noted

that inexperienced teachers, counselors, administrators, and

28

parents do not understand the Guide and can not properly use
it. But these parties are the stakeholders in the course.
Inexperienced teachers need to present instruction to stu-
dents before they can become experienced. Counselors must
help students decide if they should take the vocational data
processing course. Administrators must make both resource
allocation decisions and decisions about what course offer-
ings should be made available to the students of their
districts. Parents need not only to help their children
make intelligent choices as to what courses they should
take, but they must also support their children if they
encounter difficulties in learning the skills presented in
the course.

Each of these stakeholders mug; be able to understand
what is involved in a vocational data processing course.
Yet a thick curriculum guide is an improbable medium for
explaining the course to these stakeholders. Moreover, the
brief "focus" statement and the task lists available in the
Guide are almost meaningless to a person with no experience
in data processing. Even experienced teachers who do under-
stand the Curriculum Guide have difficulty explaining the
course to people who have limited knowledge of the typical
data processing professional's vocabulary or cognitive
style. The designers and developers of the Dara_£rgga§§iug
Durrigulum_§uiga made no attempt to provide users with a

reasonable way of understanding the course.

29

W

In this chapter the development of the Michigan Depart-
ment of Education's Data Processing Qurriculuu Guide was
discussed as an example of a typical instructional develop-
ment process. Then selected portions of the Guide were
examined and the following problems were discussed: (a) the
Guide did not provide adequate information about points
within the instructional program where students typically
required expert help, (b) the Guide did not indicate the
location and type of information that was needed by the
students as they attempted to learn cognitive skills, (c)
the Guide did not indicate the relationships among the
topics and processes in the instruction, (d) The Guide
listed tasks in a way that might limit the instruction
presented by some inexperienced teachers, and (e) the Guide
did not give interested persons, who had little knowledge of
data processing, any convenient way to understand the data
processing curriculum. After examining several instruc-
tional theories the conclusion was reached that the problems
above were not caused by the underlying theories, but were
the result of the limitations of the tools and techniques
used in designing and developing the curriculum.

To alleviate these limitations, instructional design
must incorporate techniques that allow developers to apply
learning and instructional theories effectively. As many

leaders in the field of instructional theory have stated,

30
the practice of designing and implementing instruction is
greatly influenced by the tools used by instructional de-
signers (Glaser, 1976: Gropper, 1983: Kowallis & Wilson,
1981; Mayer, 1983).' The tools used by instructional design—
ers affect the implementation of the instruction. Instruc-
tional designers need to examine the tools they now use and
determine if an improvement in the tools used to analyze and
design instruction might not lead to improvements in the
implementation of instruction, especially in the areas

presented as problem areas in this chapter.

A EgaaiDle Sgurge gf Instrucrionai Analysis ang Daaign Toois

It is not sufficient merely to recognize that the
Information Age has created a need for improved instruction-
al design tools and techniques; the improvements must be
made. In doing this educators should note that business and
industry have also been affected by the Information Age.
Therefore, one source of possible improvement in the tools
used to design instruction for the Information Age is the
information management sector of the business world. Recent
changes in instruction have been facilitated by the use of
advanced information technology to design, manage, and
deliver instruction customized for the individual learner
(Perelman, 1987). But everything known about technology,
innovation, and productivity in other fields needs to be

reinterpreted in light of this cardinal fact: Educatigu is

31
Eh: gnly Duainess whare tue gousumer goes most of the work
(Perelman, 1987, p. ES-l).

The next chapter examines some tools currently being
used by Management Information Systems (MIS) that may have
potential to alleviate problems with current instructional
analysis and design techniques. However, as these MIS tools
are examined, care will be taken to "reinterpret" their use

in the light of Perelman's warning.

CHAPTER 3

INSTRUCTIONAL DESIGN USING DATA FLOW DIAGRAMS

IDLIQQBQLIQD

In the preceding chapter, several problems with current
instructional design techniques were discussed. In this
chapter the alleviation of those problems through the use of
data flow diagrams in the instructional design process is
discussed.

First, the purpose, conditions, methods, and outcomes
of instructional analysis and design using data flow dia-
grams are discussed. Second, the use of data flow diagrams
in Management Information Systems is reviewed. Third, an
example is presented of instructional analysis and design
using data flow diagrams within a vocational data processing
course. Fourth, an example is presented of instructional
design using data flow diagrams for an interactive video
course in veterinary medicine. Last, the advantages of the
use of data flow diagrams in instructional analysis and

design are discussed.

Inarrugrignai Dualysis and Design Daing dara fiow Diagrams

A data flow diagram is a graphic tool that could be
used in instructional design to alleviate some of the prob-

lems that may be found with instruction designed with the

32

33
current design tools. Data flow diagrams might do this in
many ways: (a) they might help to locate the points in the
learning process where teachers' help may be needed for
students to master the cognitive task: (b) they might show
the type and position of information needed for each process
within the instructional system; (c) they might aid in
analyzing the cognitive skill to be taught, identifying the
cognitive processes for higher order thinking skills, and
presenting the cognitive skill as a whole; (d) they might
show the interrelationships among topics and processes of
instruction at various levels from course to lesson: and (e)
they might provide a convenient way to explain a course to
interested, content-area-naive, parties.

Since data flow diagrams are used for many different
types of systems in MIS, data flow diagrams probably could
be used for designing instruction for many levels of know-
ledge. However, since current instructional design tech-
niques are adequate for behavioral and lower level intel-
lectual skills, the technique would probably be most effi-
cient when applied to instructional design involving higher
order thinking skills, such as problem solving, or when
applied to the development of computer aided instruction.
In problem solving, the complexity of the task and the
difficulty in designing instructional guides for teaching
cognitive strategies would warrant the extra effort neces-

sary to use data flow diagrams. In computer aided

34
instruction, such as interactive videodisc courseware, the
structure of the data flow diagrams developed in designing
the instruction corresponds to the structure necessary for
programming the instructional system.

This researcher's experience in developing data flow
diagrams as an instructional design technique has shown that
the designer must have certain information: (a) clearly
stated goals of the course or lesson; (b) access either to
subject matter content experts or content analysis in the
form of job, task, or cognitive analysis information; and
(c) access to expert instructors in the subject matter
content area. Also, the designer must know the level of
detail desired by the teachers or instruction developers.

The methods for using data flow diagrams in instruc-
tional design closely resemble the methods employed in the
design of Management Information Systems. Using the goals
as a guide, the designer analyzes existing real world pro-
cesses, consults reference and/or research information, and
seeks the advice of content and instruction experts to
determine the major components of the system and their
interrelationships.

The levels of the analysis/design should be determined
in consultation with the developer or instructor to deter-
mine the appropriate level of detail, but should normally
start at the course level to establish the major interrela-

tionships. Other possible levels of detail are (a)

35
curriculum, (b) program, (c) course, (d) section, (e) unit,
(f) chapter, (g) topic, (h) subtopic, (i) lesson, (j) lesson
component. Each level should be constructed using data flow
diagrams and should include: (a) the starting and ending
points: (b) no more processes, that is points where informa-
tion is organized, transformed, or applied, than the number
that could be stored in short term memory at one time; (c)
an indication of what strategies and knowledge are necessary
for each process point; (d) points where inputs from outside
the instructional program, such as expert help, are needed;
and (e) descriptions of the information passed from process
to process to the level of detail needed by the developer or
instructor‘. For example, prerequisite job skills may be a
sufficient identifier for an experienced developer or teach-
er, but for a different developer or teacher the designer
may need to specify prerequisite abilities, such as able to
read at the fifth grade level, able to write or print legi-
bly, able to communicate with supervisors and other workers,
able to follow simple directions, able to tell time and
monitor time on task, etc. At each level at least one
expert content specialist, one expert teacher, and one

potential teacher should review the analysis with the

 

1If the instructor is not available or the instruction is to
Ibe designed for more than one instructor, random samples should
Ibe:taken of potential instructors to determine what level of
detail is needed. When in doubt, designers should select more,
not less detail/levels.

36
designer and modifications should be made, if necessary,
before the next level is analyzed.

The outcome of the data flow diagram design technique
is a graphical representation of the instructional system at
as many levels as desired by the teacher. Each level graph
shows the major information processes involved, the informa-
tion and knowledge necessary for these processes, the inter-
relationships among the processes, a potential sequencing of
the processes, and points where the student is likely to
need expert help in mastering the instruction.

A checklist of this researcher's instructional design
process using data flow diagrams is presented in Appendix D.

'a ms ' Ma a m t a 'on s s

Using data flow diagrams to analyze systems is not
unique to instructional design. It addresses the broader
problem of analyzing a process or system to determine what
is needed to manage information. People involved with
management and Management Information Systems (MIS) have
been analyzing systems since the early part of this century.
Recent emphasis in MIS has focused on the data to be col-
lected and the information to be manipulated (Lord, 1983).
The data flow diagram is one of the most commonly used
analysis tools for this task (Davis & Olson, 1985). Data
flow diagrams have proven effective in industry to emphasize

the sequence, connectivity, and type of data and information

37
utilized by the system. Therefore it would appear that they
have potential to enhance the instructional design process
as well.

Gane and Sarson (1979) provide a detailed explanation
of data flow diagrams and how they are used in analyzing
information processing systems. The following description
summarizes the technique, showing the basic symbolism, with
the intention of providing only sufficient information for
the reader to understand how data flow diagrams might serve
as an instructional design tool.

Data flow diagrams show the information flow in a
system by using four major symbols: (a) a shadowed square to
indicate an entity external to the system, (b) a rounded
rectangle to show processes, (c) arrows to show the flow of
information, and (d) open rectangles to show data stores.
[See Figure 4]. When the same symbol is redrawn in a dia-
gram to simplify the diagram, extra bars are placed in the
symbol to show that it is repeated. All data in the diagram
are represented in a data dictionary that describes the data
in detail.

To use the data flow diagram technique in instruction,
this researcher modified the meaning of the symbols. The
data flow diagrams show the design of the instructional
system by using the four major symbols:

(a) a shadowed square to indicate points that can not

be completely created in advance of the delivery of the

38

Label for the Process

 

 

 

# . #
Process, often can be broken downinto
Name subprocesses.
. Physical location
._.

 

Entity external to the system but

necessary at least Under some circumstances.
Can be start and exit points of the system,
other systems that contribute, outside

consultants, outside evaluations, etc.

. Flow of information from one point to
Label , ‘ another. Label Should be explained in
detail in data dictionary.

Data store. Could be files, reference
materials, computer programs, etc.

 

 

| * Name I

 

_.#...#_". An indication that a symbol has been

redrawn to make the diagram less
complicated. Both symbols represent

, _ j the same single entity. More lines are

added for additional symbols repeating.

 

 

 

 

[* | Name

 

Label

Gene and Sarson (1979)

FIGURE 4: Commonly used symbols in data flow diagrams

39
instruction. For example, a point at which expert, individ-
ualized instruction is likely to be required, such as an
experienced teacher helping a student find and correct
errors in a program the student is attempting to write:

(b) a rounded rectangle to indicate processes, for
example, points where the student needs to organize, inter-
pret, or transform information or instruction:

(c) arrows to show the passing of information and
instruction between processes; and

(d) rectangles to show stored information, either
externally, as in a reference book, or internally as in an
acquired strategy.

All information that passes from one processes to
another is listed in an instruction dictionary that des-
cribes the information in more detail. For example, the
diagram may indicate input standards, but the instruction

dictionary would specify those standards.

Dia a ' t'o
In the preceding chapter, the development of the voca-
tional Dara Drggaasiug Curriculum guiga using instructional
systems-design techniques was discussed. To show how data
flow diagrams could be used in instructional design, the
same vocational data processing course will be analyzed by
this researcher using data flow diagrams. The State of

Michigan's Data Processing Curriculum Guide (1983) was used.

40
The instructional design process given in Appendix D was
followed.

In designing the instruction, this researcher performed
two other functions: subject matter content expert and
expert instructor. This researcher's expertise in these
areas is indicated by: (a) certification by the Institute
for the Certification of Computer Professionals in Data
Processing (CDP), Systems (CSP), and Computer Programming
(CCP): (b) eight years of experience teaching vocational
data processing; and (c) a nomination for teacher of the
year by the researcher's District.

I To design the vocational data processing course using
data flow diagrams as a tool, first the course goals were
established and verified. The goals for this vocational
data processing course were (a) to prepare students for
entry level positions in the data processing field; (b) to
prepare students for post secondary instruction in the data
processing field.

Using content matter and instructional expertise, this
researcher then determined the course components. In this
case, these were: (a) the operation of computers; (b) busi-
ness applications of the use of the computer, including the
entry of data into the computer; (c) the programming of a
computer; (d) the role of computers in business and society;
(e) the skills necessary to obtain and maintain a job in the

data processing industry.

41

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42

Once the goals and course components were established,
they were represented in a data flow diagram. [See Figure
5]. Note that at this overview design stage, no attempt was
made to identify specific information needed or the sources
of that information since the diagram would then be so
complex that it would no longer be a useful tool. Also note
that the numbers used to label the processes served only as
a means for linking each process to the more detailed data
flow diagram that might be made of that process. Although
in MIS the process labels normally designate processing
sequence, when this researcher developed the data flow
diagrams included in Figures 5 through 29, the numeric
process labels were not used to indicate a fixed sequence.

The course overview diagram shown in Figure 5 can be
used to_show the interrelationships between the course goals
and the major course components. For example, by looking
only at the major symbols, that is the external entities and
the processes, one can see that the major goals of the
course are to prepare a student for a job or for higher
education. One can also see that there are five major
components in the system.

Note that using data flow diagrams, all the information
that would be available to the designer using the current
technology is still available to the designer. However,
notice the additional information that this diagram pro-

vides: (a) there are prerequisite skills for each of the

43

five major components of the course; (b) the job skills of
teamwork and following standards are a part of each of the
other four components; (0) there are computer operations
skills, job skills, programming prerequisites, and business
application and data entry skills that are inputs into the
programming process; (d) the choice of work or school after
completing the course is a matter of personal preference.

To follow the format of the use of data flow diagrams
in MIS, a further explanation of the related information in
the form of an instructional dictionary should now be devel-
oped for each point where information is passed from one
item to another on the data flow diagram. For example, the
prerequisite programming skill, "understanding elementary
algebraic concepts", would be listed in the instructional
dictionary as containing the following components: (a)
understanding the concept variable; (b) knowing the symbols
for and the usage of the relational operators (less than,
greater than, equal, greater than or equal, less than or
equal, and not equal); (c) knowing the symbols for arith-
metic operations (+, -, /,*, ), and ‘); (d) knowing the
rules of order for arithmetic operations: (e) knowing how to
solve simple algebraic equations with one unknown; and (f)
knowing how to use scientific notation for numbers.

The complete instructional dictionary has not been
included in this example for the sake of brevity. In prac-

tice, this researcher would include elements in an

44
instructional dictionary only if the target teachers had
some question about the element. For example, most educat-
ors interested in teaching computer programming at the
secondary level probably have very similar concepts of what
”understanding of elementary algebraic concepts” means and
the designer would probably not define the term. However,
if parents, students, or even counselors wanted clarifica-
tion, the design tool provides a mechanism for more precise
specification, and the designer would be able to add this
level of detail to the design without altering the existing
structure.

One of the greatest strengths of a data flow diagram
design tool is the hierarchical nature of its development.
The designer can proceed to the lowest level and specify the
smallest fact needed as a part of the instructional package,
or can stop at a much higher level if that level is suf-
ficient for the instructional program to be developed and
implemented.

The next step in the development process, after the
components of the course are identified, is to analyze each
of the components of the course and to construct data flow
diagrams for each. For the sake of brevity and simplicity,
we will focus only on the programming component. Program-
ming was selected since it entails higher order thinking

skills of problem solving.

45

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47

A learning objective of programming instruction may be
stated as follows: given a problem not previously seen, the
student will design and produce a program that meets all the
given conditions of the problem and follows the course
programming standards for both design and production. The
evaluation of the performance of the objective is consistent
with standards used by actual data processing shops. These
are given to the students and demonstrated. The course
programming standards are uniform throughout the entire
course, but more detail is added to the standards as the
course progresses.

The next step in system design is to break programming
skill into its component parts or tasks. Figure 6 shows an
overview level of a data flow diagram for the component
skills needed for designing a computer program. Once again
note that the major symbols indicate that there are nine
major components in the designing of a computer program.
These are: (a) define the problem, (b) define the specific
outputs, (c) define specific inputs, (d) define processing
sequence and detail process, (e) represent process specifi-
cations graphically, (f) develop program detail code, (g)
test the program, (h) debug the program if there are errors,
(1) evaluate the program.

With this data flow diagram, all the design information
that is available with current analysis techniques is avail-

able. However, in addition, more information is readily

48
available. For example, there are 16 different types of
information the programmer will need, some more than once.
Expert problem solver, expert debugger, and user/problem
designer are entities external to the programmer's problem
solving process that contribute to the programmer's design
and development of the program. As can be seen from the
numerous arrows between processes, some of the processes are
interrelated. For example, the arrows from 2.0, 3.0, 5.0,
and 8.0 respectively pass to process 6.0 the information:
output specifications, input specifications, process speci-
fications and graphic representation of process specifica-
tions, and correction specifications. In addition proces-
ses are interrelated in that several information stores
provide information to more than one processes. For ex-
ample, D4 and D5 both provide information to processes 2.0
and 3.0; and D3 provides information to 1.0, 6.0, and 8.0.
The data flow diagram also shows that the program design
process is not linear, but contains loops as shown by arrows
from process 4.0 to process 5.0 and from 5.0 to 4.0 as well
as the arrow from 8.0 to 4.0 and 8.0 to 6.0.

Although the additional information provided by the
overview of the instruction might be enough so that the
instruction could be implemented without further analysis,
this is unlikely. This researcher would anticipate the need
to provide at least one more level of diagrams to clarify

the instructional needs for each of the major processes.

49

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51

Each of the processes shown at this level is analyzed
to determine the component tasks and the relationships among
them. Then a data flow diagram is developed for the next
lower level for each process. Figure 7 shows the data flow
diagram for process 1.0, define the problem.

Note that there are no data stores or external entities
on this level that were not on the previous level. However,
the use of those stores is shown in more detail. In addi-
tion, the role of the individualized instruction in the
computer program design process can be more readily seen.

This researcher believes this level of detail would be
sufficient for developers to develop instructional materials
or for teachers to design the lessons to teach students how
to define the problem, especially if an instructional dic-
tionary were also developed. However to determine whether
even more detail is needed, the designer would present the
design to the developer or instructor for evaluation.

Figure 8 shows the data flow diagram that resulted from
another analysis and design level for process 1.2, determine
the type of output. Again, note that the data flow diagram
not only shows what is necessary to complete a task, it also
shows how each subtask, or component, is related to all the
other components. It shows not only where information is
needed, but separates the information into different types,
which, according to Gagne (1977), is important to the devel-

opment of the final lesson.

52

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53

This level-by-level analysis and design should continue
until the point where the person who actually develops or
implements the lesson for the task has as much information
as is needed to create or teach the lesson. The set of data
flow diagrams developed for experienced teachers would
probably not need to show as many levels as a set of data
flow diagrams developed for inexperienced teachers. If the
experience level of the target teachers is not known or the
instruction is designed for teachers of varying degrees of
experience, the instruction should be designed to the lowest
level that may be needed by the target teachers.

Appendix B contains the complete example of using data
flow diagrams to analyze and design the programming portion

of the vocational data processing class to the second level.

d flow ia rams to si n active V'deo C u se-

EQLQ

The preceding sections of the chapter demonstrated how
data flow diagrams could provide useful information when the
technique was used to design a course including problem
solving in computer programming. Data flow diagrams could
also provide useful information when used to design interac-
tive video courseware. Figure 9 shows the first level data
flow diagram this researcher's design group developed for an
interactive video course for teaching the role of pain and

its control in veterinary medicine. Although the course was

54

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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55
still under development at the time of the writing of this
dissertation, the data flow diagrams had been presented to
the client who not only approved of their accuracy, but
indicated approval of the level-by-level design approach by
saying "I can see the whole course now, layer by layer," and
"I knew where I wanted to go with this material, but now I
feel as if I have been given a road map showing me how to
get there". In addition, the menus that will be used to
control the presentations have been developed from the data
flow diagrams and an estimate of the amount of time neces-
sary to the complete the project has been make.

Note the different kinds of information that are pro-
vided at the first level data flow diagram. [See Figure 9].
The diagram shows that learners can enter the course at any
of the four major course processes. The first three proces-
ses are designed to add to the learner's knowledge base,
while the fourth process requires that the learners use
their knowledge bases, along with cognitive strategies and
reference materials, to solve problems. The information
that the learners will process in order to add to the their
knowledge bases is separated into attitudes, facts, con-
cepts, and principles since each of these major types of
information needs to be presented to learners using dif-
ferent instructional techniques (Gagne, 1985; Gropper, 1983:
Landa, 1982; Reigeluth & Stein, 1983; Scandura, 1983). If

the course is to have learner control of the pace and

56
sequence, the instruction will need to provide learners
access to information from the previous sections. In the
first level data flow diagram shown in Figure 9, the infor-
mation that is presented in one section and then used to
build the knowledge in another section is shown by the
connecting arrows. For example, note that arrow W4 between
81.0, stored principles from process 1, and process 2, shows
that principles 8, 10, 11, 12, 13, and 14 are presented in
the process 1, PAIN, but the learner will also need those
principles to process information presented in process 2,
BUTORPHANOL. By using this data flow diagram, the developer
of the instruction knows where the courseware must be able
to either branch back to previous information or provide the
previously presented information in a different format. The
principles represented by W4 are listed in the instructional
dictionary for the course in Appendix E.

Since information provided by the first level data flow
diagram includes the number of major processes, the number
of.instructional events of each type, and the number of
links between sections that must be provided, it can be used
by the instructional designer to make rough estimates of the
cost and time necessary to develop the course. However,
sophisticated estimates of development costs can not be made
until the content expert provides information as to the
importance and difficulty of each event in the instructional

dictionary.

57

Appendix E contains the data flow diagrams for the
first section of the course, Pain, and the instructional
dictionary for the section. When the course is authored,
each of the processes from the data flow diagrams will
become a menu selection for the course. Appendix F contains
the procedures developed by the CAI group at Michigan State
University for using data flow diagrams to develop interac-
tive video courseware. The complete process, including the
relationship between the instructional dictionary and the
developmental worksheets is being readied for separate

publication and will be available in the future.

f e o a a f a s
The preceding chapter presented several problems with
the current instructional design techniques. In the preced-
ing sections of this chapter, data flow diagrams were dis-
cussed and a demonstration was made of their use in instruc-
tional design and analysis. In this section we will focus

on the advantages of using this technique.

Qete flex diagzams help locete the peints in the leezh-
ing pteeese whete help hay be heeded. In the data flow

diagram developed for computer programming, three external
entities, expert problem solver, expert debugger, and user/-
problem designer, contributed to the process of the design
and development of the program that solves the problem.

These entities indicated the points of the process where

58
students often need help when they are learning to program
computers. Even an inexperienced teacher using this data
flow diagram would be able to determine where special effort
may be required to help students learn to program properly.
By using symbols to designate information sources within the
instructional system that are different from the symbols
used for information sources outside the system, data flow
diagrams make it easy to see points where teachers should

consider making expert help available for their students.

Qete flow diaggggs show the type and positipn pf integ-
WMW- Since

the data flow diagrams provide graphic indications of the
points within the instruction where information is needed
and, if necessary, the instructional dictionary shows spe-
cifically what is needed, it is easier for teachers to pro-
vide students with the information during the instructional
process instead of requiring students to know the informa-
tion before they attempt the task. In addition, teachers
have a concrete way of determining what media would be most
appropriate for presenting the information to the students.
The potential of existing instructional packages to meet
students' instructional needs could be measured by comparing
the information the packages deliver to the information the
instructional dictionary specified. Hamreus (1968) stated
that if the instructional technologist is to get maximum use

from media in improving learning outcomes, he must be able

59
to determine how, what, and when media can most effectively
be employed. By focusing on the information and sequencing,
data flow diagrams can help designers and teachers determine
where some of the teaching might be relegated to self-paced,
programmed, and computer aided instruction.

1. a o. . -- .u: .fd ' .1: ,. 1- ..,' 'v- :.f
te_he_tepght. By stressing which data, information, and
strategies are needed at different points of the process,
data flow diagrams help the instructional designer focus on
all the information and interrelationships as a complete
skill. This allows the designer, developer, and instructor
to work at a higher cognitive level. Compare the informa-
tion about the programming process provided by the data flow
diagram in Figure 6 with the task list on computer program-
ming provided in Appendix A. Using the data flow diagram,
even inexperienced teachers could see the part each of the
tasks in computer programming played in making up the com-
plete cognitive skill, yet they could also see the entire,
complete task as an organized whole. Thus they would be
more likely to present the instruction to their students as
a complete cognitive processes, not merely a collection of
behaviorally oriented tasks.

Derry (1984) pointed out that in teaching cognitive
strategies, there must be a taxonomy of curriculum-relevant
component strategies. The data flow diagram can be a tool

to help the instructional designer see the taxonomy of

60
strategies and also see where those strategies are needed in
the instructional program. Therefore the probability is in-
creased that those strategies will be correctly addressed by
the instructional program and will be deve10ped by the
student.

Higher level thinking skills are represented by data
flow diagrams by focusing on goals, information, and needed
expertise instead of focusing on specific tasks that make up
the skill. By examining the different levels of the pro-
cess, the instructional designer can see where cognitive
strategies or diagnostic knowledge are required.

ow ia a s show e t a ' s ' am
tepiee end pzoeesses of instppctipp. When data flow dia-
grams are used to design the instruction, even inexperienced
teachers can become more aware of sequencing alternatives in
the presentation of the components. In the discussion of
Figure 6, the specific ways that the data flow diagram
showed the interrelationships among the topics and processes
of instruction were indicated. Since the graphical repre-
sentation of the instruction system produced with data flow
diagrams contains lines showing the passing of information
between components, it is easy to see interrelationships
among components of the system, to identify components that
require the same information, and to note any necessary se-

quencing of components.

61
1. a _ow -°.- .us 9 ov'd— a ., e e - . -.- .f,

o- :< . - 0: -- co - -. :;-1-iv- 9-_ '-=. One of
the strengths of data flow diagrams stems from the graphic
nature of its representation. Polhemus (1987) states that
the use of graphics provides a very efficient medium for
exchange of information because graphics are easily explain-
ed, have strong impact, and permit multiple dimensions to be
displayed concurrently.

Using data flow diagrams to represent a system graphi-
cally allows even a relatively inexperienced person to
recognize the critical elements of the instructional design.
Thus more of the stakeholders in the instructional program
could have a better understanding of courses designed using
data flow diagrams. Since the design provides multiple
levels of representation of the system, each level provides
an advanced organizer for the following level. In addition,
since data flow diagrams show one complete level of a system
at a time, an examination of the system could range from
looking at the first level for an overview of the entire
system to carefully analyzing the lowest level of a module
for a detailed analysis of the components, depending on the

needs or desires of the person using the data flow diagrams.

Summary

In this chapter the purpose, conditions, methods, and

outcomes of instructional analysis and design using data

62

flow diagrams were discussed. The use of data flow diagrams
in Management Information Systems was reviewed. The in-
structional analysis and design of a vocational data proces-
sing course using data flow diagrams was developed using the
techniques that were presented in Appendix D. Where ap-
propriate, the results were compared to the results from
Chapter 2. Figure 10 summarizes the major differences. An
example was presented of an instructional design using data
flow diagrams for an interactive video course in veterinary
medicine. The response of the client and the strengths of
the technique were discussed. Finally, the advantages of
the use of data flow diagrams in instructional analysis and
design were discussed. The following advantages were noted:
(a) the location of the expertise needed by students to
learn higher order thinking skills is presented; (b) the
type and position of information needed for each process
within the instructional system is indicated; (c) the com-
ponents of the cognitive processes for higher order thinking
skills are presented as a whole; (d) the interrelationships
among topics and processes of instruction are graphically
shown at as many levels as are needed; and (e) a convenient
way to explain a course to interested, content-area-naive,
parties is available.

Thus, using data flow diagrams to analyze and design an
instructional process provides more information in a readily

usable form than the current systems design technology. In

63

addition, since the symbols used to designate information

sources within the system are different from the symbols

used to designate information sources outside the system,

data flow diagrams also indicate points where expert systems

could be of use to deliver needed information. Expert sys-

tems will be discussed in the next chapter.

Information about the
teaching of programming
provided by the Qutpic-
ulum_§uids

 

tasks that make up pro-
gramming

 

Figure 10: Qurrigulum
Quid:

Information about the teaching
of programming provided by data
Flow diagrams

 

the processes that make up pro-
gramming

the points within the instruc-
tional program where students
may need expert help

the type and location of
information needed within the
instructional program

a presentation of the cognitive
skill as an organized whole

the interrelationships among the
processes

a convenient way to explain the
course to content-area-naive
stake holders

 

compared to Data Flow Diagrams

CHAPTER 4
EXPERT SYSTEMS

IDEIQQHQLiQB

In the preceding chapter the use of data flow diagrams
for instructional design was discussed. It was demonstrated
that data flow diagrams not only emphasize information,
processes, and interrelationships, but also show points in
the instructional program where individualized expert help
may be needed by typical students. In this chapter the use
of expert systems to provide that help is discussed, fol-
lowed by a discussion of some concerns educators might have
when considering the use of expert systems within instruc-
tional programs.

First, expert systems are defined and their use by
business and industry is discussed. Next, the limitations
of expert systems are discussed, followed by a discussion of
some reasons for developing expert systems, despite their
limitations. Examples are presented of expert systems that
have proven to be valuable within instructional programs.
Then the theoretical potential for the use of expert systems
in education is discussed, followed by a discussion of steps
involved in developing expert systems in both business and

education. Finally, an example of the development of an

64

65
expert system within a vocational data processing program is

discussed.

Mining);

Expert systems are computer programs that make the
expertise of an experienced worker available to a novice.
An expert system consists of three parts: (a) a knowledge
base composed of production rules, semantic networks,
frames, relational database, and inference rules: (b) an
inference engine, which consists of the procedures that
generate the consequences, conclusions or decisions from the
existing knowledge; and (c) a working memory, which is a
temporary storage area to hold the immediately relevant
portions of the knowledge base, the user's responses, and
the current inference. An expert system must also have an
user interface, a way of communicating with the user (Boose,
1986; Hayes-Roth, Waterman, & Lenat, 1983).

One of the simplest types of expert systems to develop
is the production-rule system. F. Hayes-Roth (1985) cites
many advantages to using rule-based systems. First, since
they incorporate practical human knowledge in conditional
if-then rules, it is possible to develop production-rule
systems to help supply novices with the expertise of ex-
perienced workers in any situation where the expertise could
be expressed by algorithms. Second, since the skill neces-

sary to design production-rule systems increases in direct

66
proportion to the size of the knowledge bases, relatively
inexperienced programmers could develop small systems con-
taining the most critical rules and then add the more com-
plex rules as their programming skills improve and they gain
more knowledge about the content area. Third, by determin-
ing the best sequence of rules to execute, selecting rele-
vant rules, and then combining the results in appropriate
ways, production-rule systems could solve a wide range of
complex problems. In addition, production-rule systems
could help the novice understand the rules the expert used
by explaining their conclusions, retracing their lines of
reasoning, and translating the logic of each rule employed
into natural language.

Since production-rule expert systems are relatively
simple to develop, but still have many advantages, the
development of this kind of expert system should be con-
sidered in situations where the expertise needed could be

expressed in a production-rule format.

2W

When considering the development of expert systems, it
is important to realize that not all expert systems are
designed to do the same type of tasks. Expert systems are
applicable to three generic classes of problems: analysis,
synthesis, and a combination of analysis and synthesis

(Hayes-Roth, Waterman, & Lenat, 1983).

67

The simplest class consists of analysis problems.
Analysis problems require classifying a set of objects based
on their features. Typical expert systems designed to solve
analysis problems classify items, provide help in debugging
processes, aid in deriving diagnosis, identify unknown
items, or aid in the interpretation of output from some
system. Currently most of the cost effective expert systems
used by businesses are designed to solve analysis problems
(McCorduck, 1987).

More complex than analysis problems are problems of
synthesis. Synthesis problems are generative problems in
which a solution must be built up from component parts.
Typical expert systems designed to solve synthesis problems
determine the configuration of systems, design systems, and
develop plans for courses of action. Although production-
rule expert systems that are capable of forward chaining
have been developed to solve synthesis problems, most pro-
duction-rule expert systems solve analysis problems.

The most complex problems for which expert systems are
used consist of a combination of analysis and synthesis.
Typical expert systems designed to solve combination prob-
lems are used for command and control, making management
decisions, monitoring complex physical processes, predicting
future events based on current and past events, and deter-

mining components needing repair.

68

In developing expert systems, it is important that the
type of expert system chosen to solve the problem matches
the class of the problem. For example, if the problem
involves synthesis, an expert system that could only do
backward chaining, working from the goal toward the given
data, could not possibly solve the problem. A general
heuristic for planning the development of an expert system
is that the more complex the class of problem, the more

resources will be required to develop the expert system.

Limitetiehs of Expert Systems

The discussion of the limitations of expert systems in
this chapter is not designed to be either detailed or ex-
haustive. Rather the intention is to provide some insight
into the problems that may occur with the use of expert
systems. A detailed discussion of the limitations of expert
systems and the concerns that potential developers of expert
systems should consider is provided by Hayes-Roth, Waterman,
and Lenat (1983).

To be effective, expert systems must contain a substan-
tial amount of domain expertise organized for efficient
search (Klahr & Waterman, 1986). To model the thinking of
experts, expert systems must be able to use heuristics, that
is, rule-of-thumb knowledge that enables experts to make
educated guesses when necessary, and to deal with incomplete

or inconsistent information (Boose, 1986).

69

Expert systems must be able to contain the problem-
solving knowledge of the expert, whatever its form or degree
of complexity (Hayes-Roth, 1985). For example, doctors
doing a diagnosis of a patient must not only classify symp-
toms of the patient, but must also infer the most probable
cause of those symptoms. Experts in the area of finance
must not only know what types of investments are available,
they must also have preferred strategies for reducing the
risk of the investment. They must know how to eliminate the
uncertainty of the effects of future events. Expert repair
persons must not only know how to repair the product, they
must also know the likeliest places to look for relevant
information about the cause of the problem.

In general, experts in all fields must observe events
and make specific inferences based on the observations. In
addition they make abstractions from which they form gener-
alizations and categorizations (Hayes—Roth, 1985). Larkin,
HcDermott, D. Simon, and H. Simon (1980) provide an example
from solving algebra problems. Suppose the problem

A board was sawed into two pieces. One piece was

one-third as long as the whole board. It was

exceeded in length by the second piece by 4 feet.

How long was the board before it was out (p. 207)?
was given to both novice and expert algebraic problem
solvers. The typical novice sets up the equation x/3 +

(x/3 +4) = x and solves for the value of x. However, the

expert problem solver almost immediately states that the

70
answer is 12. If pressed to explain the reasoning used, the
expert will note that if one piece was 1/3 of the board, the
other piece 2/3 of the board. Since the second piece, 2/3
of the board, was the length of the first (1/3 of the
board) plus 4 feet, 1/3 third of the board was 4 feet long
and the entire board was 3 times 4 or 12 feet long. Thus by
making abstractions, generalizations, and categorizations
instead of following the ”rules for solving word problems”,
the expert could almost instantly "see" the answer while the
novice was still attempting to express the problem using
mathematical symbols. Experts used the formal "rules for
solving word problems" only when they could not "see" rela-
tionships within the problem that readily lead to the
solution. Thus, experts not only know many ways to reach a
desired goal such as the solution to an algebraic problem,
they also know which ways are necessary and sufficient
conditions for goal achievement under the given conditions
(Hayes-Roth, 1985).

One of the most complex types of knowledge that experts
possess is the knowledge of the limitations of their know-
ledge (Hayes-Roth, 1985). For example, expert doctors not
only know how to make diagnosis and inference of probable
cause, they also know when to tell the patient to seek the
advice of a specialist, an even more knowledgeable expert.

From the preceding discussion it could be seen that the

expertise possessed by experts could represent a wide range

71
of complexity of many different types of knowledge. As
noted by B. Hayes-Roth (1985), the difficulty of modeling
many of those forms of knowledge within an expert system is
obvious.

In addition to difficulty of modeling many types of
knowledge possessed by experts, most expert systems have
other limitations (Hayes-Roth, Waterman, & Lenat, 1983).
Although many expert systems could list the rules used by
the system to reach the solution, most could not explain
their results in a manner suited to the particular audience
using the expert system. The novice then could not get the
same benefit from the answer provided by the expert system
that could be obtained from a human expert-even if they both
provided identical solutions. This may limit the usefulness
of the expert system as a training tool.

Also, human experts learn from their experiences. Most
expert systems could not learn from the problems they solve,
stretch their own rules, or restructure their knowledge
(Hayes-Roth, Waterman, & Lenat, 1983). Thus, most expert
systems could not improve their performance. To improve the
performance of the expert system, a human expert must deter-
mine what changes must be made and the expert system pro-
grammer must then modify the system. Perhaps the greatest
limitation of expert systems stems from their lack of self
knowledge (Boose, 1986). Expert systems are not able to

determine the relevance of their knowledge to the current

72
problem and they can not degrade gracefully at problem
boundaries. Thus it is quite likely that a novice, giving
an expert system a problem that was not the type for which
the system was developed, might still get a plausible solu-
tion that was very much in error. This could, of course,
cause many problems for the novice.

The final limitation to be considered stems from the
inability of expert systems to engage in the higher levels
of reasoning (Boose, 1986). Expert systems could not reason
about space and time, or reason from underlying problem
domain principles, or reason analogically. These higher
order reasoning abilities are currently only produced by

human experts.

ev o n d xam

Despite their limitations, there are many situations in
which it is useful to develop expert systems (Boose, 1986).
Within the business environment, expert systems may be
developed to help the replacement worker when experts re-
tire, taking their knowledge with them. In some areas, such
as determining the best configuration for a computer net-
work, expertise may be scarce or not available. Often when
experts are available, their expertise may be very expensive
to obtain. When expertise is scarce, an expert system may
help to deliver a product or service in a more timely manner

than would be done by a human expert, because the human

73
expert is not always immediately available. One of the most
common reasons for developing an expert system is that
experts, being human beings with human limitations, are not
always consistent (Boose, 1986).

HcCorduck (1987) has researched the current uses and
effectiveness of expert systems in business. She visited
companies in both Japan and the United States and only
considered systems that were actually being used. She cited
numerous examples of large productivity gains or cost reduc-
tions effected by the use of expert systems. She summarized
the information she had gathered in six good reasons for
developing and implementing expert systems:

1. e o e o dif' at

nd 'str butio o 'se. If the expertise
of a key person is captured in an expert system, the reason-
ing is coded in a systematic manner that will give consis-
tently identical output for identical input. The expert's
reasoning could then be used by more than one decision maker
in more than one geographical area.

Examples of this effective use of expert systems are:
(a) Nippon Kokan Steel developed an expert system to "clone"
their best blast furnace controller and allow inexperienced
controllers to use his experience: (b) Dupont offered early
retirement to experienced workers to cut costs only to
discover that they needed their expertise! The experts were

brought back and expert systems were developed to nOt only

74
recapture that lost expertise, but also to increase its
continuity in the company; (c) Texas Instrument was able to
keep an old and ”temperamental" machine running by develop-
ing an expert system to help the repair persons quickly to
repair the machine when it broke down.

2. t e s cou d dev 0 ed for mbin'n
expe1tiee_fitem_mehy_epnzeee. It is not uncommon for busi-
ness decisions to require input from more than one expert.
If an expert system is developed to aid in the decision
making, it could include the expertise of more than one
expert in both its knowledge base and its inference engine.
Thus the combination of the experts' reasoning could be used
without the difficulty of assembling all the experts in one
place.

Examples of this effective use of expert systems: (a)
Digital Equipment Corporation developed the EXpert CONfigur-
ation system EXCON to determine computer configurations.
They also used EXCEL to help salespersons to present the
product more effectively. DEC estimated that the use of
these two systems provided an annual savings of $25,000,000.
(b) Kajima Construction Co. developed an expert system to
determine how to sink the pylons for their construction
projects. The expert system not only saves $200,000 per
year, but also improves the quality of the work.

B-ExWMeumio—W

:: 2!! -9 9 01- e 0.2m: _ -a 15 _n °r°duc iv: 0 :1

75

the greetieh of new tasks, prpddcts, end services. Almost
all experts in business are called upon to provide expertise
at a variety of levels. If an expert system could be built
to provide expertise at some lower levels, a resident expert
might have more time to use his expertise at a higher lev-
els. This, in turn would increase the expert's productivity
and allow more time for work with new developments.

Examples of this effective use of expert systems: (a)
Cannon used expert systems to set up simulation runs to test
new camera lens. As a result, one person now could do in
two weeks the design testing that in the past took several
experts months of work. (b) Arthur Anderson developed
expert systems to help with the auditing of financial sys-
tems, allowing high level consultants to aid in more consul-
tations. (c) American Express developed an expert system
that could authorize credit limits in under 90 seconds based
on information in 13 different data basses. It is estimated
that the use of this expert system saved American Express
millions of dollars in credit card fraud each year and also

reduced the time pressure on workers when making credit

 

decisions.
4. Expert systems eould be developed to avoid signifi-
s w sted esources ca a . Texas InStru-

ments developed an expert system to help engineers prepare
presentations for documenting capital investment procedures.

This new system took one twelfth of the time of the previous

76

system and saved the company an estimated 500,000 dollars
annually.

5. s ems on v d t e e com-

3 ea evenue. In Japan, a bank developed

an expert system for investment portfolios that analyzed the
customer profile and recommended investments based not only
on current and projected market trends, but also on the
personal philosophy of the investor. The pleased investors
spoke so highly of the investment service that customers
without investment portfolios started using the bank because
it was perceived as modern and good. Three hundred thousand

yen was added to the average amount invested with the bank

annually.
6. s d so v -
WW. Dupont developed

a system that helped local managers to determine how to pay
taxes across different geographical regions. Because the
tax codes are readily available, this was not a difficult
task, but was so time consuming that managers often took the
easiest options, even when other options might have been
more cost effective. With the expert system, it is estimat-
ed that the corporation saved $2,000,000 per year. IBM
developed an expert system that greatly increased the pro-
ductivity of their engineers by helping them complete the
documentation required. Another expert system used by IBM,

which had a very high payoff in cost savings, helped move

77
capital equipment from one geographical region to another.
These expert systems solved problems that were more a matter
of expertise in knowing what was wanted than expertise in
higher order thinking skills. Such tractable problems tend
to consistently have high returns on investment when expert
systems are developed to solve them.

The use of expert systems by business continues to
grow. Coopers & Lybrand of New York recently surveyed the
Nation's leading insurance companies and found that 65 per
cent of the companies are either currently using or are
developing expert systems, twice as many as were using
expert systems a year ago. David Shpilberg, their head of
Decision Support Services, says "insurers are realizing that
expert systems technology offers a way to harness knowledge
efficiently in an industry that is extremely knowledge-
intensive" ("Insurance embraces”, 1988, p. 39).

The reasons for developing expert systems in the busi-
ness environment also apply for developing expert systems
within the educational environment. Yazzdani (1987) pointed
out that after an expert system has been developed, the line
of reasoning, knowledge, and organization of the expert
could made available for observation by trainees. In
school, the expertise of the teacher is continually avail—
able, but it must be allocated among many students within a
limited time period. By providing students another source

of expertise, the computer program, not only is the

78
available time teachers have to work with students, a scarce
resource, increased, but students have access to the exper-

tise whenever they need it during the learning process.

{JLP :: 1.. Il tat U - . .10- — ‘11: 1 0.- -. .-
As in business, instruction is knowledge intensive, and
the development of instructional technology has shown a
steady advancement in the level of skills that could be
taught using technology. The evolution of present-day
teaching programs consists of: (a) Pressy's linear frames
(1926), (b) Crowder's scrambled textbooks or branching
frames (1962), (c) adaptive systems that branch based on a
history of responses, and (d) generative systems that use
algorithms to generate problems and answers (Gable & Page,
1980). At present, specialized programs designed specifi-
cally for education that use artificial intelligence and
expert systems to aid in student acquisition of some ele-
ments of an expert's knowledge, could be added to the list.
Currently several intelligent tutorial systems are
being used primarily as experimental vehicles in instruction
(Sleeman & Brown, 1982). Two examples that use artificial
intelligence in the instructional process are SOPHIE, which
is an operational intelligent computer aided instructional
(ICAI) system designed to provide tutoring in the domain of
electronic troubleshooting, and BUGGY, which is an instruc-

tional game that helps students and inexperienced teachers

79
understand the student's misconceptions in mathematics, by
analyzing errors the student is making (Suppes, 1979).

SOPHIE provides students with simulations in electronic
troubleshooting. Students could enter a board configuration
and the measure of energy to be applied to the board into
SOPHIE and SOPHIE will tell them what output will result.
Students could "experiment" with different board configura-
tions and energy inputs without the risk of damaging the
board components and without expending the large amounts of
time required physically to construct the boards. In addi-
tion, SOPHIE could present students with boards that have
"bugs” in them and require the student to determine what
component is malfunctioning. Students could use different
inputs or even change components on the board as they seek
to find the causes of the malfunctions. Students using
SOPHIE took less time to gain a higher level of expertise in
troubleshooting electronic circuits than students who worked
only with actual circuits.

BUGGY trains student teachers to examine surface mani-
festations of students misconceptions in mathematics and use
the results of that examination to determine the deep-struc-
ture misconceptions in a student's knowledge. When BUGGY
was used with students, the students began to study and
understand the underlying procedural skill instead of merely

performing the behavioral operation (Brown & Burton, 1978).

80

Such programs as BUGGY and SOPHIE come closer to in-
structing students with a degree of the skill of a good
teacher than the mere branching capabilities of programed
instruction. One of the most important of these skills is
the teacher's ability to synthesize an accurate "picture,"
or model, of a student's misconceptions from the meager
evidence inherent in the student's errors. If instructional
programs are designed to provide the student with the expert
help that teachers normally supply, they will also need to
be designed to respond appropriately to errors that students
make.

As one example of such an instructional program,
Sebrechts, Shooler, LaClaire and Soloway (1987) created a
computer-based expert system called GIDE which interprets
students' statistical errors. GIDE is a goal-driven diag-
nostic system that analyzes answers to statistical problems
and presents that analysis in a form that is designed to be
used by the student to improve performance in working that
type of problem. Currently, it could evaluate a student's
solution to a statistical problem specifically requiring a
repeated-measures T test. Testing showed that the program
was capable of interpreting over 90% of the student solu-
tions and print out a report of the "bugs", that is, errors
in computation or solution approach. In comparing the
expert system to the work of teaching assistants, the GIDE

program was found to do a consistently better job than the

81

T.A.'s in identifying all the areas of error in the solu-
tion. Although teaching assistants ”interpreted” all the
solutions, over 10% of the solutions graded by the teaching
assistants fell into the category of "I do not understand
what you were attempting to do" as the T.A.'s evaluation.

One of the fastest areas of growth in the development
of expert systems is the use of expert system shells.
Shells are expert systems for which the inference engine has
been designed, but the knowledge base and the rules are left
blank so that applications could be developed by entering
the domain specific application knowledge base and rules.
Lee (1987) reported the use of an expert shell written in
the PROLOG computer language to help students learn con-
cepts, think analytically, and test ideas. The shell creat-
ed a versatile way for the students to explore knowledge
about number theory, or other subjects, and encouraged
students to learn actively and to think logically. Lee
taught the students to program the domain they were explor-
ing using PROLOG and then to see what other information was
true, given the information that they placed in the domain.
Unfortunately, the fact that the students must have communi-
cated with the expert system using PROLOG decreased the
usefulness of the system as an instructional tool, since
learning to use this complex language effectively took a

substantial amount of time.

82

Expert systems are also being designed to teach problem
solving skills. Many areas addressed by emerging technology
in the area of expert systems are those very areas defined
as important areas of problem solving (Newell & Simon,
1972). For example, consider this information processing
definition of problem solving by Anderson (1985, pp.198-199)
which states:

Problem solving is defined as a behavior
directed toward achieving a goal. Problem
solving involves decomposing the original goal
into subgoals and these into subgoals until
subgoals are reached that can be achieved by
direct action...Problem solving can be conceived
of as a search of a problem space. The problem
space consists of physical states or knowledge
states that are achievable by the problem
solver. The problem-solving task involves
finding a sequence of operators to transform
the initial state into a goal state, in which
the goal is achieved...The working-backward
method for problem solving involves breaking

a goal into a set of subgoals whose solutions
logically imply solutions of the original
goal...The knowledge underlying problem

solving can be formalized as a set of productions
that specify actions that will achieve goals
under particular conditions.

Boose (1986); Hayes-Roth, F. Hayes-Roth (1985); and
Waterman, & Lenat (1983); all described expert systems that
use proposition-rules to make available to novices the
domain specific problem-solving knowledge of an expert.

Many of these systems use backward chaining and most provide
explanations to the user as to the reasoning used by the
system. O'Shea and Self (1983) observed that expert systems

could be used for imparting knowledge from an expert in a

83
field to a large number of trainees. Waterman (1986) stated
the diagnostic function of a human tutor seems ready to be
attacked with the well-established methodology of expert

systems.

1- ,-. - a_ '0 en a for - s: o oe ; en: .n

mm
In addition to the four examples of how expert systems
are being used in educational research and a look at how
expert systems could be useful in problem solving, it is
equally important to note that the theoretical body of
knowledge of expert systems also supports their potential
use in the instructional environment.
eti bod o kn w ed e of e .

Wensley (1987) pointed out that there are two broad fun-
ctions for expert systems: expert replacement and user
support. But the potential function of the expert system as
a training tool should not be overlooked. Our current
method of training experts, extensive experience under
apprenticeship, has not changed in centuries. With expert
systems, the experience of an expert is imbedded in the
system. Thus the novice should be able to use the system
and gain expert experience at an accelerated rate (Abdol-
mohammadi, 1987; Wensley, 1987). Thus while replacing an
expert or providing user support, the expert system could

also provide training for a novice to become an expert.

84

As regards the support function, Wensley suggests the
following uses that would be applicable to education:

First, expert systems could serve as an ”intelligent assis-
tant" to experts to check their conclusions. If the con-
clusions arrived at by the expert are different from the
conclusions produced by the expert system, the human expert
is alerted to double check the reasoning by which the con-
clusion was reached.

Second, expert systems could be used to investigate,
expand, and develop expertise. The process of developing an
expert system requires that the expert or team of experts
analyze their expertise closely and actually determine how
that expertise is applied. In the process of developing the
expert system, experts often expand their expertise and
develop expertise at a higher level. As an added benefit,
the experts might be able to spend less time checking their
conclusions, leaving them more time to work on more dif-
ficult problems.

As a third support function, expert systems could
provide users with advice. For example, IBM's expert system
that aided in troubleshooting customer complaints provided
advice to the troubleshooting consultant as to probable
cause and remediation. The expert consultant then used the
expert system's recommendation as one of the factors to be

considered when giving advice to the customer.

85

Lastly, expert systems could serve in a support func-
tion by being one of a set of learning tools to help develop
expertise in a domain. For example, an expert system devel-
oped to help students correct errors in a computer program
could not only help the student learn to correct the errors,
it could also show students the steps that an expert uses
when correcting the errors.

In summary, the theoretical body of knowledge of expert
systems indicates that a broad function of expert systems is
to provide user support. In the discussion of the user
support function of expert systems it was noted that they
help in the development of expertise, provide checks for
conclusions, provide insight into expertise, and provide ad-
vice. Note that most of these ”user” support functions are
similar to the types of support systems that good teachers
provide in an educational environment. Thus, the theoreti-
cal body of knowledge concerning the use of expert systems
supports their potential use in the instructional environ-
ment.

e ' bod w e of l a i theo .
According to cognitive psychologists, the study of higher
order thinking skills must include both the observable
actions of students and their cognitive processes (Anderson,
1985: Ausubel, 1968: Mayer, 1987). For example, how stu-
dents perceive and reason about the subject matter domain in

which they are learning must be considered along with what

86
they are learning. Experts and novices differ in their
cognitive processes. Experts do not simply have more knowl-
edge than novices, they structure the knowledge differently
and apply their knowledge using different problem-solving
strategies (Anderson, 1985). Both Ausubel (1968) and Bruner
(1960) stressed the importance of structuring the subject
matter in instruction. Keravnou and Johnson (1986) noted
that expert systems include the structure of the body of
knowledge and the domain strategies. Thus, expert systems
not only contain the knowledge of an expert, but also the
higher order rules by which that knowledge is manipulated by
the expert. Therefore, it is reasonable to attempt to use
an expert system within an instructional program to train
novices to develop both the expert's knowledge and under-
standing of the structure of the subject matter.

The body of knowledge of inexperienced problem-solvers
is relatively unstructured. As a person gains experience in
problem-solving in the knowledge domain, he gradually im-
poses more structure on this knowledge. The structure re-
flects the strategies and heuristics which have been demon-
strated as effective by experience. On the other hand,
experienced and competent problem-solvers have a knowledge
structure and a set of compatible problem-solving heuris-
tics. They have structured their factual knowledge in the
most efficient and effective way for the subject matter

domain.

87

Therefore, the potential use expert systems in educa-
tion is supported by the theoretical body of knowledge about
learning theory because expert systems contain both the
knowledge of a domain expert and the heuristics that a
domain expert would use to search the knowledge base for the
correct solution to a problem. Thus, a properly designed
expert system might enable novices to structure their knowl-
edge bases in a more effective and efficient manner and
decrease the amount of experience that a novice would need

to become an expert.

Gpidelines for Selecting Bolpts fp; Expert System Usage

Since developing an expert system as a learning tool or
for another purpose takes time, requires additional soft-
ware, and restricts the use of the computers for other
purposes, before an attempt is made to develop an expert
system, it should be determined that the expertise repre-
sented in the expert system fills a need in the complete
process for which an expert system could be developed. In
industry or business, locating the point in the process
where an expert system could be used is not conceptually
complex: use and organizational chart to locate an expert
within the process and determine whether the expert's con-
tribution could be increased or replaced by an expert sys-

tem. However, Bosse (1986), presented several points that

88
should be considered in the actual application of this
principle:

1. The end user of the expert system should be an
apprentice in the same field who would take three to five
years to become an expert. Since expert systems contain the
structured knowledge of the expert, they also use the spe-
cial vocabulary of the domain expert. Since this special-
ized vocabulary is often meaningless jargon to people with
little or no knowledge of the field, it is necessary that
the users of the expert system already have some experience
with the subject matter domain before using the expert
system. Also, if training the novice is not a lengthy
process taking years to complete, it would be more cost
effective to merely train the novice than to develop and use
an expert system as an aid to learning to be an expert.

2. There should be someone who knows how to solve the
problem already. Expert systems capture the expertise of an
expert. If there is no existing expert, there is no source
for obtaining the expertise to place in the system.

3. The problem should not require team effort or more
than a single expert who could currently solve the problem.
Although expert systems could be developed to hold the
expertise of more than one expert, such systems are very
complex. A team approach to solving a problem may be used
when the problem is so ill-defined that it requires a group

effort to determine what is needed to solve the problem. As

89
a rule, the development of an expert system should not be
attempted unless the problem is well defined and sufficient-
ly limited so that a single expert could solve it.

4. The expert should be available to consult with
users. Expert systems, even extremely well constructed
systems, are computer programs and thus severely limited in
their ability to communicate with human beings. As users
work with the expert system, their skill will increase in
using the system, but there will be many times when the
inexperienced user will not be able to determine what input
to give to the expert system. Contact with the expert is,
therefore, essential, to provide the support that only a
human expert could give to a novice.

5. There should be a clear justification, based on
monetary, liability, or safety considerations, for develop-
ing an expert system. Expert systems should not be built
simply because the expert is available. The development of
an expert system should meet the same cost-benefit criteria
that other projects must meet.

6. The expert should be available for a sufficient
period of time during development and testing of the expert
system. If the developer of the expert system does not have
sufficient access to the expert, the information extracted
from the expert will probably be incomplete and improperly

structured. In addition, during the testing stages of the

90
system, there will need to be frequent comparisons of the
output of the expert system with the output of the expert.

7. The expert should have a collection of real cases
readily available. Such cases are necessary for both the
development and testing of the expert system because an
expert's expertise often is difficult to capture. If the
developer could observe the expert solving real cases, the
developer could gain insight into the expert's problem solv-
ing tactics. Also, the alpha testing of a system requires
many cases to test all aspects of the system.

Chaturvedi (1987) takes a structured approach to the
problem of selecting points in processes to develop expert
systems. He proposes two broad categories of problems with
which expert systems could be used: (a) those that could be
solved with an analysis approach, in which a complex problem
could be successively broken down into a number of subprob-
lems until the subproblems could be solved directly: and (b)
those that could be solved with a synthesis approach, in
which the system starts with solutions to subproblems and
combines those solutions to get a solution to the complex
problem.

Analysis is used for problems such as classification,
interpretation, evaluation, assessment or diagnosis. Ex-
amples of the types of problems requiring synthesis are
design problems and program construction problems. The

primary problem with the synthesis approach is that it is

91

necessary to search through all possible paths, which could
become explosively large in number as the number of starting
subproblems increases even slightly. Consequently solutions
for problems involving synthesis must involve heuristics.

Current expert system technology has had very limited
success with solving problems involving synthesis. Such
solutions rely very heavily on estimations and the mathe-
matics of probabilities and combinations. Currently there
are no mathematical rules for combining the probabilities of
events which are not independent. Until there are, there
probably will not be many successes with systems requiring

synthesis.

.. 1e: o_ : e tin- 'oints . 'go- ; en :a-- n

W
v 'nst . Researchers such as

Boose (1986), Chaturvedi (1987), and Davis (1987) provide
criteria for determining where the use of an expert system
would be beneficial within the business environment. How-
ever, there is currently little research on where the use of
expert systems is appropriate within the instructional
environment. In business the function of the expert is to
reach some goal. In education the function of teachers, as
experts, is to help students reach some goal, not to reach
the goal for them. As Perelman (1987) points out, in educa-

tion the student must do the work. Thus, subject matter

92
expertise must be integrated into the instructional program
to aid students to arrive at solutions, not to provide
solutions. Such integration could be done by analyzing the
instructional task to determine both where and what type of
expertise is needed.

A specific exemple from voeatiohel data ptocessing. In
the previous chapter it was shown how the analysis technique
of data flow diagrams might help the instructional designer
determine the points within the instructional system at
which an expert system might be useful. By looking at
successive levels of the analysis, the characteristics of
the expert system could be determined.

For example, the overview of the instructional unit for
teaching students to design a computer program, [see Figure
6], indicated three points at which an expert might have
input into the system: (a) in defining the problem; (b) in
defining the processing sequence and detail process; and (c)
in debugging the program. The more detailed analysis shown
in Figures 7 and 8 indicated that expert systems for the
first two points would be synthesis systems or a combination
of analysis and synthesis. Since synthesis systems are very
difficult to develop and have been shown in the past to be
of only limited success, it seemed that an attempt to devel-
op either of these two systems would not have been desira-

ble.

93

 

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94
However, the third point, shown in Figure 11, indicated

an analytic system involving classification and diagnostic
skills. Therefore, it was decided to develop an expert
system designed to aid or replace the expert debugger.
Before describing the steps in developing an expert system
for the instructional program, the process of developing
such a system in business will be described in order to

provide a context.

e o ' x

Several experts in the area of expert systems have
stated the steps necessary to develop an expert system
(Boose, 1986; Buchanan & Shortliffe, 1984: Hayes-Roth,
Waterman, & Lenat (1983); Tanimoto, 1987). Although the
approach of each of these experts is different, there is
general agreement among them as regards the basic steps.
These are: (a) Identify and clearly define the problem that
the expert system is to solve; (b) locate existing experts
that could be assigned to provide the expertise in solving
the problem; (c) develop the knowledge base and the rules
for applying the knowledge base; (d) develop a prototype
of the expert system; (e) alpha test the prototype using
actual cases; (f) make any modifications necessary to the
prototype until it appears to produce consistently the same
solutions as those produced by the human experts; (9)

document and field test the system; (h) iterate through

95
steps (a) - (g) as often as necessary; (i) release the

system for general use.

f Shells in evelo E e S stem

The many complex steps in the development of an expert
system cause most developers to attempt to simplify the
process by the use of an expert system shell. A shell for
an expert system refers to all the system's procedures but
not the application-specific knowledge: for example, the
procedures for accessing the knowledge and procedures that
generate the consequences, conclusions or decisions from the
existing knowledge base (Tanimoto, 1987). Shells are used
for rapid prototyping and could facilitate the construction
of knowledge bases. However work of formulating the knowl-
edge requires extensive interactive dialogues between a
knowledge-base building tool and one or more human experts.
Waterman (1986) listed many of the commercially available
shells and explained the differences in the way they were
designed.

Because of the complexity of analyzing and obtaining
expertise, most developmental experts agree that if there is
an expert shell available that will meet the requirements
for the system to be designed, that shell is the best choice
for developing the expert system. Ruth (1987) suggested
that two good shells for instructional systems are EXUS and

FIRST CLASS because both are goal driven, rule-based shells

96
with backward and forward chaining. Boose (1986) provided a
relatively simple description of this type of expert system.
In a simple goal driven backward chaining system, the user
picks a goal, with or without the help of the system. The
inference engine looks through all the rules that lead to
that goal and queries the user about the most direct rules
leading to that goal. This process is repeated until the
truth of the goal is established.

In a simple data driven forward chaining system, the
user gives the system certain facts and the system draws
whatever conclusions that it could from those facts. The
queries to the user are based on the traits or attributes
characteristic of the given problem domain which are stored
in the knowledge base. Also stored in the knowledge base
are appropriate goals, the heuristics of what to query, and
the desired sequencing. This information is loaded into the
expert system shell through the cooperative efforts of the
knowledge engineer and the domain expert. The knowledge
engineer must not only elicit rules from the expert, he must
also determine all the traits of the propositions and their
characteristics as well as the accompanying control informa-
tion.

Potential sources of expert knowledge for the expert
system include human experts, textbooks, data bases, ex-
amples, case studies, and personal experience. The transfer

of knowledge from human experts to knowledge bases is called

97
expertise transfer. The knowledge transferred consists of
facts, procedures, and judgmental rules in the problem
domain.

In some situations, it may be difficult to obtain
knowledge from experts because their explanations may be in
terms of idealized verbal descriptions. Also much expertise
seems to be compiled in heuristics that are accumulated over
the years and it may be difficult for experts to talk about
these compiled patterns. In such situations, knowledge
extraction techniques may be necessary.

A detailed discussion of knowledge extraction tech-
niques was presented by Waterman (1985) from Clancey (1981)
and reported by Boose (1986). They are summarized as fol-
lows: (a) observe the expert as he actually solves problems
on the job; (b) talk to the expert about the problem and
what he is doing as he solves it; (c) develop an extensive
description of the problem, with or without the help of the
expert, and have the expert react to and improve the des-
cription; (d) do a detailed task analysis of the problem;
(e) develop a prototype of the system and refine it until
the expert and the user agree that it produces the same
results as the expert; (f) examine the system objectively to
determine whether there are any weaknesses, and (g) validate
the system by comparing the system's results with the ex-
pert's results in existing documented cases, or by having

other outside experts use the system and compare its results

98
with the results they would produce for the same problem
input. Host of these techniques are usually needed when an

expert system is to be developed for a complex problem.

e n evelo 'n an E ert s n ns ct'

1p geyeloping an expert syspgm, the puppose must bg
Lgpt_glgazly_in_mipd. As discussed previously, the purpose

of an expert system in the instructional environment is to
provide students with the expertise of an expert so that
students could both accomplish some task requiring expertise
and could also acquire the expertise of the expert. Thus,
an expert system in instruction must not only provide the
student with expertise, but also with an understanding of
the structure of the knowledge of the expert and the heuris-
tics used by the expert. At any point in the use of the
system, the student should not only be able to query the
system to find what knowledge is necessary, but also to find
why it is necessary, and how it fits into the whole problem.
ngjg: spepg pf developmenp. Drawing from the steps
used by business to develop expert systems and considering
the unique needs of instruction, this researcher proposes
the following steps in the development of an expert system.
First, the steps will be described generally and then they
will be applied specifically to the Vocational Data Proces-

sing course.

99

1. Select the point in the instructional program where
an expert system might be of use. Using an analytical
technique such as data flow diagrams, determine the points
in the instructional program at which the student may need
individualized expertise. Carefully examine the charac-
teristics of the students who will use the system and ana-
lyze the instructional program to determine the points where
expertise is likely to be needed. These points are the
points where an expert system is likely to be effective.

2. Determine if the problem is appropriate for the use
of an expert system. Determine if the expertise needed by
the student requires analysis, that is classification,
debugging, diagnosis, identification, or interpretation. As
discussed earlier, expert systems from the analysis class
are the simplest systems to develop and proposition-rule
expert systems are the simplest types of analysis systems to
develop. Because of the time and cost constraints of a
typical instructional program, educators should be wary of
attempting to design an instructional expert system that is
not from the analysis class and proposition-rule based. If
an attempt is made to develop a complex expert system, the
costs are likely to be very high and the success is less
likely.

3. Select an appropriate shell for the expert system.
As previously stated, the shell should have procedures for

accessing the knowledge base and inference procedures that

100
are appropriate for the intended application. Appropriate-
ness of shells is estimated by comparing existing applica-
tions using the shells with the task for which the expert
system is being developed. The more characteristics the
systems have in common, such as type of analysis, structure
of the subject matter, apparent heuristics for accessing the
knowledge base, the more likely it is that the shell is
appropriate. Because of time and cost constraints of a
typical instructional program, developers should be wary of
attempting to design an instructional expert system for
which there is not an appropriate shell. Expert systems
could be developed most efficiently if access and inference
procedures already exist.

4. Establish sources for the expertise to be loaded
into the expert system. Locate available reference mater-
ials which indicate how to perform the task under considera-
tion. Also locate at least one expert instructor who has
extensive successful experience with providing expert help
to students attempting to learn the task under considera-
tion, and who is willing to spend time working in the devel-
opment of the expert system. If more than one expert is to
be used, and if there is likely to be disagreement as to how
to do the task, determine in advance the criteria to be used
to determine which advice to follow.

Be certain that the expert agrees as to the correctness

of any reference materials that may be used as a guide.

101
However, if the expert differs from the reference material,
follow the advice of the expert. If the expertise of a
human expert is loaded into the expert system, the expert
system is most likely to provide the type of instructional
support that the human instructor would give.

5. Create the rule base. Work with the expert and the
reference materials to construct the rule-base in the if-
then format. Not only should the expert be asked, but, if
possible, the expert should be observed actually instructing
students in the task. Experts often do not know, or could
not tell, the heuristics that they use in performing a
complex task or instructing students in that task. By
observing the expert, comparing the expert's actions to the
reference materials and the expert's stated rules, and
querying the expert on the actual instructional content, the
rule base of the expert system is much more likely to be
accurate.

6. Create a prototype of the system and test it for
programming errors. Once the system has been programmed and
modified until there are no syntax errors, test the program
by having the expert run the program to see if the expert
agrees with the instructional aids provided by the system,
and make any changes the expert recommends. Then ask anoth-
er expert to test the system. Discuss the recommendations

of the second expert with the developmental expert.

102

When the developmental expert approves of the system,
test it on a representative sample of the target students
who will be using the system and correct any problems that
they may have with the user interface. Check to see that
the results that the students get from the expert system are
the same as the results that the expert said they should
get. When the system appears to be working properly, test
the system, comparing the outcome with a control group
receiving instruction from the expert. Make any necessary
adjustments to the system. By prototyping, testing, and
modifying the system, the expert system is most likely to be
effective as an instructional aid.

7. Continue to monitor the expert system. Use the
system with additional students and add rules or modify
existing rules as indicated. The design of expert systems
is rarely considered to be finished because the situations
for which they were designed tend to change over time.
Therefore, there should be periodic reviews built into the
use of expert systems in instruction so that the systems

will be kept current.

W. The steps in the

development of an expert system within instruction could be

more clearly seen in their application to the program

103

debugging example. Having determined where in the instruc-
tional program expertise was necessary (see Figures 6-8,11)
and having determined that the expertise needed to aid the
student in learning to debug computer programs was an an-
alytic, diagnostic system (see A_§pggifig_gxamplg_fppm
ypggtipnal data pzoggssipg within the section gpigglipg§_fpg

. z ,. -. m; . .g-e - -._. n _ s to 0,)
the next step was to find a shell that would be both reason-
ably priced and effective.

t n s e . Since the objective of the system
was to help the user to debug computer programs as an expert
would, it was necessary to find a shell that would permit
the designer to use production rules that followed closely
the top down, goal driven, breath-first problem solving
techniques used by an expert programmer (Anderson, 1985).
The top down, goal driven approach is represented by back—
ward chaining. Therefore, the shell to be chosen needed to
be capable of backward chaining and be able to group choices
into logical arrangements similar to the breath first tech-
niques used by expert programmers. In addition, the shell
had to allow explanations as to the reasoning behind the
choices, because the objective was not only for students to
be able to debug like an expert debugs, but also to under-
stand the line of reasoning involved so that the knowledge

gained would be properly structured.

. 104

Considering these requirements, this researcher chose
the shell INSIGHT, published by Level Five Research, which
was reCommended by Blaisdell (1985). Although INSIGHT was
limited to only backward chaining, it was reasonably priced
and met all other necessary requirements. Also Level Five
Research was willing to give permission to use an education-
al version of the program for testing with no additional
cost.

nd at s . The
goals and rules were determined by this researcher with the
aid of IBM's basic manual, and with the aid of a student
from a vocational data processing course who had graduated
at the top of the class. The functions of subject matter
content expert and expert vocational data processing in-
structor were performed by this researcher. Three major
goals within the area of logical errors and fifteen major
goals within the area of language errors were identified.
The production-rules were based on the expertise of this
researcher.

Czeatipg a prototype. A prototype was developed by
this researcher and the graduate student in about forty
hours of programming time. The prototype was initially
tested for appropriateness by two graduate students who were
very competent programmers. Subgoals were added as soon as
the primary goals were working properly. The prototype was

modified as new points were noted. An additional ten hours

105
were needed to test and modify the system. After the system
was tested with students, the final count was sixty-eight
goals.

The rules were grouped so that related goals would
appear on the same screen and multiple possibilities as to
the error conditions would also be displayed on one screen.
To make the system as useful as possible for students, the
system was loaded into the background of the computer's
memory as students programmed in the foreground. If stu-
dents encountered problems for which help was desired, they
switched to the background expert system, found the desired
help, and switched back to the foreground programming ses-
sion to correct the error.

Igstipg_phg_gxpg;p_§y§pgp. The prototype was tested
with secondary vocational data processing students who were
learning to develop programs using the BASIC programming
language. Before going to the computer room, students used
Input-Process-Output sheets, layout sheets, and program
flowcharts to design their programs. In a typical computer
session, the student placed a system disk containing the
expert system, Double Dos, which is a program which parti-
tions computer memory and permits more than one program to
run on the same computer concurrently, and BASIC into the
system drive of an IBM compatible computer and turned on the
computer. The auto—execute file on the disk loaded Double

Dos. The Double Dos program partitioned the computer's

106

memory so one part contained 250,000 bytes of memory and the
other portion contained whatever additional memory the
computer had available. Double Dos then loaded the expert
system into the 250,000 byte portion of the memory and made
that portion inactive, or background. Double Dos loaded
BASIC into the other portion of the computer's memory, made
that portion active, set the switch between memory portions
to be the combination of the ALT and ESC key, executed BASIC
so that the ready prompt was displayed, and turned control
of the computer over to the student. This entire process
took approximately one and one-half minutes. Loading BASIC
directly took the typical student approximately one minute.

If students were continuing from earlier computer ses-
sions, they would load their existing BASIC program and con-
tinue their work. If students were starting new programs,
they would start typing a new program into the computer.
When students reached the point where they were ready to
test their programs, they typed RUN, causing one of three
actions to occur: (a) the program ran as the student an-
ticipated: (b) the program ran, but did not run as the
student anticipated: or (c) the program would not run.
To clarify the interface between the student and the expert
system, two examples of how a student might interact with
this expert system are given. The first example will be of a
logical error and the second example will be of a syntax

error .

Ci

t}.

th

107

1. Having entered a portion of the program to test,
the student typed RUN and pressed enter. However, instead
of running properly, the program continued to execute and
did not stop. Being inexperienced and not knowing how to
handle this problem, the student activated the expert system
by pressing ALT and ESC together, a key combination the
student often used in other computer classwork to change
between applications. The student was asked by the expert
system to indicate whether the problem was a logic error or
a language error.

For each question the expert system asked, there were
expand screens that could give the student more information.
These expand screens could be activated from a menu of func-
tion keys that always appeared at the bottom of the stu-
dent's screen. In addition, for each question the student
could indicate that the answer to the question was not
known, and the expert system would then ask a series of
questions to help the student answer the question.

For this example, the student either indicated direct-
ly, or by answering a series of determining questions, that
the error was a logic error. The expert system then dis-
played information about logic errors and their typical
causes. The student was asked to indicate whether or not
the program stopped. In this case the student indicated
that the program did not stop. The expert system asked if

the program had a menu or used the KEYWORD INPUT. If the

108
student indicated that there was no menu and INPUT was used,
the expert system displayed information about the use of the
INPUT statement and the function of trip data. Then the
expert system asked the student if the trip data check was
the line of code immediately following the INPUT line. If
the student indicated that it was not, a screen was dis-
played that explained the function of the check for a trip
data and provided two examples of the proper use of trip
data. The student was then told a logic error in which the
program did not stop had occurred and to correct the error
by checking for trip data input. If the student indicated
that there was a trip record in the program, the expert
system displayed two screens explaining the use of GO TO
statements and explained how to use the trace function to
locate the line numbers that were being executed in a loop.
The student was then told that a logic error in which the
program does not stop had occurred and to correct the error
by changing the GO TO statement.

Having been told the probable cause of the error, given
examples of the proper use of the KEYWORD causing the error,
and told how to correct the error, the student pressed the
ALT and ESC key together and returned to the basic program,
which was still running. The student then made the correc-
tion suggested by the expert system and executed the program

again.

109

2. Having entered a portion of the program to test,
the student typed RUN and pressed enter. However, instead
of running properly, the program executed for a short time
and then printed the message "out of data in line xxx." The
student followed the same procedures followed by the student
in example 1, except that for this example, the student
either indicated directly, or by answering a series deter-
mining questions, that the error was a language error. The
expert system then displayed information about language
errors and their typical causes. The student was given a
list of language errors and asked to indicate the one given
by the program in error. In this case, the student selected
the out of data error. The computer then displayed a screen
containing an explanation of the six most common programming
mistakes that could cause this error. The expert system
then asked the student to indicate which of these six errors
had caused the error message. If the student selected an
error, two screens were displayed which explained the func-
tion of the READ statement and how to check for trip data.
Examples were provided of the proper use of READ and DATA
statements or of matching the DATA and READ variables. The
student was then told that a language error in which an out
of data message had occurred and to correct the error for
whichever of the six methods the student had indicated

caused the problem.

110

If the student indicated that the cause of the out of
data error was not known, the expert system displayed two
screens that explained the characteristics of the six most
common programming mistakes that could cause this error.
The expert system then asked the student a series of ques-
tions that helped determine which specific error had caused
the problem.. For example, first it asked if there was a
check for trip data after the READ statement. Although trip
data was explained on the screen that described the most
probable cause of the out of data error, expand screens were
available so that if the student asked for help, the term
trip data would be explained and several examples of the
proper use of trip data with a READ would be given. If the
student indicated that there was a check for trip data, the
expert system asked the student if the trip data were in the
DATA statement. If the student indicated that trip data
were in the DATA statement, the expert system asked the
student if the value of the data in the check trip data
statement matched the value of the data in the DATA state-
ment. If the student indicated that it did, the expert
system asked the student if the trip data were being as-
signed to the same variable that was being used in the trip
data check. If the student indicated that it was, the
expert system asked the student if for every variable in the
READ statement there was a value in the data statement. If

the student indicated that there was, the expert system

111
asked the student if the variables in the READ statement
matched the data in the DATA statement.

If the answers to any of the above questions would have
been no, the error would have been located and the expert
system would have displayed a screen telling the student how
to correct that particular error. The student would then
have been told that a language error in which there was an
out of data message had occurred and to correct the error by
whichever of the six methods the student had indicated
caused the problem.

Having been told the probable cause of the error, given
examples of the proper use of the KEYWORD causing the error,
and told how to correct the error, the student pressed the
ALT and ESC key together and returned to the basic program.
The student then made the correction suggested by the expert
system and executed the program again.

However, if the student indicated that the last ques-
tion to be asked did not indicate the error, the student was
told that a language error in which there was an out of data
message had occurred but that the expert system could not
determine the correction for the error. The student could
then ask the expert system what reason it had for asking all
the questions. The expert system would then step through
each of the inference rules the system had used and list the
goal to which it was directed. In this example the explana-

tion would be: The question "the program runs is true or

112
false" was asked to determine that ”the error belongs to
language errors." The list of possible syntax errors was
presented to determine that "the error was out of data".
The question "the error is no check for trip data after the
READ” was asked to determine "correct error by checking for
trip data after the Read." The question "the error is no
trip data in the Data statements" was asked to determine
”correct error by adding trip data to DATA statements".
This display of the questions asked and the conclusion that
would have been given if the answer had been no would con-
tinue until all the questions asked by the system had been
displayed. Then the expert system would have printed "the
information provided was not sufficient to reach a conclu-
sion." The student would have gone through this presenta-
tion of questions and their possible conclusions to see if
the answer given had been incorrect or if the cause of the
error could be determined by merely using the expert sys-
tem's line of reasoning. If the student could not determine
the error after asking the expert system to explain its
reasoning, the student would need to ask a human expert for
help.-

0 n h ex e s . As students used the
system, some situations occurred for which the expert system
did not have rules or where the rules were unclear. In such
situations, new rules were added or existing rules modified.

The final system required seventy-two rules. In addition,

113

several points were discovered where the students did not
understand the system's questions and needed more informa-
tion. Expand screens were made available for these more
complex situations. Displays were added for each goal and
subgoal, that explained the rationale underlying the solu-
tion. The modifications took approximately ten additional
hours of programming time, making the total programming
hours approximately sixty. A printout of latest version of

the expert system is given in Appendix C.

CHAPTER FIVE

DISCUSSION AND RECOMMENDATIONS

Spmmazy pf the Study Reported

This dissertation discussed the increased need for
efficient and effective instruction of high level intellec-
tual skills in order to meet the challenges of the Informa-
tion Age. It was noted that learning theories and instruc—
tional design theories had been developed that dealt with
cognitive processing, but that the tools currently used by
instructional designers did not readily facilitate the
teaching of cognitive processes. Several specific problems
with one current design technique were identified and dis-
cussed. These were: (a) inadequate consideration for need
for expertise and knowledge, (b) insufficient focus on
needed information, (c) limitations created by expressing
cognitive skills in a task format, (d) lack of consider-
ation for the interrelationships among topics and processes
in the instruction, and (e) lack of convenient ways to
explain a course to interested, content-area-naive, parties.
Thus, the conclusion was reached that there is a need for
instructional design techniques that permit developers to
apply learning and instructional theories more effectively,

especially in the indicated problem areas.

114

115

Next it was noted that business and industry had also
been affected by the Information Age. The suggestion was
made that data flow diagrams and expert systems, two tools
and techniques developed by HIS to handle information, might
also be of use within instructional design. The broad
questions were addressed within the discussion of the spe-
cific questions. The five questions about the use of these
tools were addressed as follows:

1. How might the use of data flow diagrams in the
design of a particular secondary vocational data processing
course provide information about the relationships between
major chunks of instruction, that is courses, units, chap-
ters, and lessons: or the major cognitive processes within
the chunks? By using data flow diagrams to develop part of
the design of a secondary vocational data processing course
and examining several levels of the design, the answer was
determined that data flow diagrams indicated the passing of
information between the units of instruction and processes
within the programming unit as well as indicating the se-
quencing among the units and processes. This information
was not available in the Michigan Vocational Data Processing
Curriculum Guide designed using current design techniques.

Before attempting to address the first broad question,
part of a set of data flow diagrams used to design an inter-
active video unit for veterinary medicine was examined. It

was noted that the data flow diagram of the entire course

116
structure showed that three units of the course would add to
the students' knowledge bases, while a fourth unit would
require students to access information from their knowledge
bases. In addition, it showed that information developed in
some units of the course was needed in other units. Thus it
showed some of the ways that the units were interrelated.

After examining these two demonstrations in which data
flow diagrams were used to design very different types of
instruction, the answer for the first broad question was
determined: the MIS design tool, data flow diagrams, might
provide information in the instructional design process.

2. How might data flow diagrams used to design a particular
secondary vocational data processing course indicate what
information might be needed by students at various points of
the instructional program? The data flow diagrams that were
developed to answer the first specific question also indi-
cated the location and various types of information that
might be needed by students for each of the major processes
and also indicated where the same information was needed for
more than one process.

When the data flow diagrams for the design of the
veterinary medicine courseware were examined they provided:
a structure that corresponded to the presentation format
used in instruction developed for interactive video: a
graphic representation of points where the instruction

needed to provide opportunities for remediation: a way of

117
classifying the instructional events as attitudes, facts,
concepts, and principles for appropriate presentation for-
mats: and the data necessary to estimate the potential cost
of developing the system.

After examining these two demonstrations in which data
flow diagrams were used to design very different types of
instruction, the answer for the second broad question was
determined: the MIS design tool data flow diagrams could
indicate what information might be needed by students at
various points of the instructional program. In addition,
data flow diagrams could provide information that might be
used to develop interactive video courseware.

3. How was the use of data flow diagrams to design HIS
systems modified to use data flow diagrams to design a
particular data processing course? To use the data flow
diagram technique to design the course this researcher
modified the technique to use: (a) the shadowed square to
indicate points that were dependent on the individual stu-
dents: (b) the rounded rectangle to indicate points where
the students organize, interpret, or transform information;
and (c) rectangles to show internally stored information as
well as external stores. In addition, this researcher did
not use the instructional dictionary if the information it
contained was probably known to the developer or teacher.

The third broad question was discussed in the context

of how data flow diagrams were used in business and how they

118
might be used in instructional design. One modification
that might be made is that the symbols used in business to
show activities that were not directly a part of the infor-
mation system might be used in instruction to show points
that are dependent on the individual students or where
expert help might be needed. A second possible modification
might be that the data dictionary used by business is always
developed to show the specific details about the informa-
tion, but the instructional dictionary might not always be
used. For example where the need for cognitive strategies
was shown in the design of the instruction for the cognitive
skill programming, the instructional dictionary was not
used, but the dictionary was very important when it con-
tained the specific instructional events that were a part of
the interactive video course in pain control. A third
possible modification might be that when the purpose of the
instruction is to use interactive video courseware to add to
students' knowledge bases, the information stores might not
be grouped by topic, but might be grouped by type of in-
structional events to facilitate the development of the
presentation modules and to estimate developmental costs.

4. How might data flow diagrams used to design a
particular instructional program to teach the problem sol-
ving skill, computer programming, indicate potential points
in the instruction where expert systems might be used to

provide students with expert help? Through the development

119
and examination of data flow diagrams for the problem solv-
ing skill, computer programming, the answer was determined
that points in the instructional program were indicated
where expert systems might be used to provide the expert
help needed by the students. From this example the answer
to the fourth broad question was determined: when the
objective is to teach complex cognitive processes such as
problem solving, data flow diagrams might indicate points in
an instructional program where individualized expert help
typically might be provided. I

Having discussed the use of data flow diagram in in-
structional design, the second tool from business, expert
systems, was examined to address the fifth specific ques-
tion:

5. How were steps used to develop HIS expert systems
modified to develop an expert system to help teach students
in the data processing course how to debug BASIC computer
programs? After discussing several examples of expert
systems in both business and education, the differences
between expert systems designed for businesses and expert
systems designed for instruction were discussed. The steps
required to develop expert systems in business were dis-
cussed and a specific example of the development of an
expert system for debugging BASIC computer programs was pre-
sented. The development of this expert system took seven

steps: select the point in the instructional program where

120
an expert system might be of use: determine if the problem
is appropriate for the use of an expert system: select an
appropriate shell for the expert system: establish sources
for the expertise to be loaded into the expert system:
create the rule base: create a prototype of the system and
test it for programming errors: and continue to monitor the
expert system.

By comparing the development steps of this expert
system for debugging to the general steps for developing an
expert system for business, the answer to the fifth broad
question was determined. The development of the expert
system used as a tool within an instructional program might
be different from the development of an expert system for
business use in several ways:

1. In business applications, the problem is clearly
defined and the expert is located as the first steps. In
instruction, the need for expert help is not as discernable
and the first steps are to locate the need and see if the
problem is appropriate for the use of an expert system.

2. In business applications, expert systems are built
using whatever techniques the developers think are appro-
priate. In instruction, the financial constraints suggest
the selection of an expert shell for typical classroom
usage.

3. In business, expert systems can be built that have

extensive knowledge bases and rules for applying the

121
knowledge. In instruction, financial and time constraints
might limit the development of expert systems to systems
that can be built from rule bases.

4. In business, the expert system must be extensively
tested and documented before being released for general use.
In instruction, the expert system supplements rather than
replaces the expert teacher so that the testing process
might be less extensive before the system is used.

5. In business, the expert system is released for use.
In instruction, continued monitoring of the system might be

established to keep the system current.

W

Despite the limitations to this study, it was demon-
strated that an instructional developer can examine and
improve the tools and techniques currently used to design
instructional systems. The discussion and examples pre-
sented suggested that data flow diagrams and expert systems
might provide some improvement. Several areas of study
might prove to be beneficial. One of the greatest research
needs in this area is to determine the impact of data flow
diagrams and expert systems in a wide variety of instruc-
tional systems, especially in those that do not involve com-
puters. Specifically:

1. Do data flow diagrams provide equally useful

information for more structured subject matter areas than

122
for less structured subject matter areas: for example,
mathematics/science, on the one hand, versus language arts
and the social sciences on the other hand?

2. Do data flow diagrams provide useful information to
teachers of different levels of subject matter experience
and expertise?

3. Do data flow diagrams provide useful information
for instruction for students of different grade levels?

4. Can teachers with limited experience with systems
analysis techniques use data flow diagrams without extensive
training in their use?

5. Can instructional designers with limited experience
with systems analysis techniques develop data flow diagrams
without extensive training in their use?

6. Will the information provided in data flow diagrams
enable teachers to determine appropriate media for the‘
delivery of the instructional events?

7. Will non-instructional stakeholders understand data
flow diagrams of instructional programs? If so, will their
understanding depend on the subject matter content or with
their familiarity with the subject matter content?

8. Will inexperienced teachers teach higher order
cognitive skills more effectively if they are given data
flow diagrams of the known processes that compose these

skills than if they are given only conventional information

123
about the skills, such as task lists and lists of objec-
tives?

9. Will students that are provided help by an expert
system learn to do the task as well as students that are
provided help by a human expert? Will there be an interac-
tion with grade level?

10. Will students want to get help from an expert
system or will they want their help to come from a person?

11. Will students using expert systems learn the pro-
cesses involved in a higher order cognitive skill in addi-
tion to demonstrating the behavioral manifestation of the
skill?

12. When applied to different subject matter areas,
will data flow diagrams indicate points at which students
require help?

13. Will expert systems provide help in diagnostic
areas less structured than computer program debugging, for
example in debugging an English composition or a history
report?

A second major area for additional study concerns the
effectiveness and efficiency of the data flow diagram tech-
nique in instructional design and of the expert system as an
instructional delivery tool. Specifically:

I. Will the extra time needed to develop data flow
diagrams as a part of instructional design improve the

instruction sufficiently to justify the additional cost?

124

2. How effective and efficient is the use of data flow
diagrams to design instructional systems compared to other
HIS structured system design techniques (Davis & Olson,
1985) such as top-down design with stepwise refinements
(graphically illustrated with hierarchy charts), Structured
Analysis and Design Technique (SADT), and Hierarchy-Input-
Process-Output (HIPO), or with the new Computer Aided Soft-
ware Engineering techniques (CASE)?

3. Will teachers use data flow diagrams to make in-
structional decisions?

4. Will providing students with expert systems be cost
effective? If it costs more to provide students with expert
systems than it did to provide them with competent tutors,
would there be any advantages to using expert systems?

5. Would parents, administrators, teachers, and stu-
dents be willing to accept the "expertise" of a machine?

6. Would teachers feel threatened by the use of expert
systems to teach higher order thinking skills?

The use of data flow diagrams in the design of inter-
active video instruction seems especially promising, but
many questions still require more study. Specifically:

1. Will data flow diagrams consistently show where
access to previously presented materials needs to be made?

2. Will the instructional designer be able to make
estimates of the cost and time necessary to develop the

courseware from the data flow diagrams?

125

3. Will the developer be able to maintain the flow of
the instruction when the instructional dictionary treats
each instructional event independently?

4. Will such factors as the importance and difficulty
for each instructional event provide specific information
about the time, cost, and most appropriate media to use in
developing the courseware?

5. Will experienced designers, developers, and authors
be able to use the data flow diagrams effectively when
designing interactive video courseware?

The discussion of problems with current instructional
design techniques was primarily based on the curriculum
produced by one technique in one subject area. More in-
structional design and development systems need to be ex-
amined to see if other systems have problems similar to the
ones found in the development of the data processing cur-
riculum.

One of the unanticipated findings of this study in the
use of data flow diagrams was that the instructional dic-
tionary was different for the two examples given, which
represent the design of different types of instruction,
which represented different cognitive processes. If the
same flexible design tool were used for a variety of in-
structional design problems and the differences among the
different designs were studied, perhaps some insights into

different cognitive processes might be found.‘ Many

126
different types of courses need to be designed using data
flow diagrams and the results compared to see if there are
any observable differences in the data flow diagrams that

suggest possible differences in cognitive processing.

Eugene

Even if expert systems prove to be efficient and effec-
tive instructional tools, their use still should be care—
fully researched. Wensley (1987) pointed out that there are
psychological as well as cognitive characteristics of ex-
perts. Expert systems currently can only attempt to model
the cognitive characteristics. Adams & Hamm (1987) stated:
expert systems work, but they miss much of the subtle,
experience-based wisdom of human experts even as they allow
for acquisition of some elements of an expert's knowledge.
Unfortunately, the best expert systems that could be made
within instructional budgets give only a mechanistic rule-
governed simulation of the lowest stage of an expert's
cognitive skill. Anything approaching higher levels of

human thought is still on the technological horizon.

GLOSSARY

GLOSSARY OF TERMS IN THIS DISSERTATION

Agricultural Age - a period of time in which the economy
is built on the growing of food and the majority of
the workers have jobs working on farms.

Alpha testing: preliminary testing of a computer
program by the developers of the program. Alpha
testing is designed to find any cases that are not
properly addressed by the system so that the system
can be modified to handle all possible cases.

Artificial intelligence (AI) - a field of study that
uses computers to model the information processing
characteristics of humans.

Authoring - the process of writing instructional computer
recognizable code using a language specifically designed
for the development of instructional materials.

Backward chaining: working from the goal toward the
given data.

Breath-first problem solving technique: a technique
where a computer programmer finishes programming
portions of a program that are similar to portions of
programs previously done before even starting
other portions of the program which may be
less familiar.

Chunk: A collection of interrelated facts, concepts, prin-
ciples, attitudes, images, sounds, and feelings that can
be manipulated cognitively as a single unit. "A maximal
familiar substructure of the stimulus (Simon, 1981, p.
80). "any configuration that is familiar to the subject
and can be recognized by him (Simon & Newell, 1972, pp.
780-781).

Computer aided instruction (CAI) - any instruction that
uses a computer for the delivery of the instruction.
(see programed instruction)

Data flow diagrams - A manner of graphically documenting
the flow of data and the procedures used within an
information system using four symbols to show: (1)
source or destination of data, (2) flow of data, (3)
processes which transform flows of data, and (4)
storage of data.

127

128

Debugging - in computer programming, the correction of
logical or syntactic errors in a computer program or
system. In problem solving, the process of locating
and correcting errors in a solution.

Expertise transfer is the transfer of knowledge from human
experts to expert system knowledge bases.

Expert system - a computer program that simulates the
cognitive processes of a human expert. Expert systems
are an applied form of artificial intelligence.

Expert System Shells: expert systems for which the
inference engine has been designed, but the knowledge
base and the rules are left blank so that applications
can be developed by entering the domain specific
application knowledge base and rules.

Forward chaining: a method of problem solving that
starts with the given or input and moves toward the
goal.

Heuristics: rule-of-thumb knowledge that enables experts to
make educated guesses when necessary, and to deal with
incomplete or inconsistent information (Boose, 1986).

If-then or if-then-else format: Rules in the form of
proposition, truth inference, negation inference. For
example: If the program runs, the error is an error in
logic else the error is a language error.

Industrial Age - a period of time in which the economy
is built on the production of goods and a majority of
the workers have jobs directly involved with the
production of goods.

Inference engine: procedures that generate the
consequences, conclusions or decisions from the
existing knowledge base.

Information Age - a period of time in which the economy
is based primarily on information processing and a
majority of the workers have technical, managerial,
and clerical jobs.

Information system - a system to organize data in a
meaningful fashion to produce information. The basic
model consists of input, process, storage, and output,
but in recent years distribution has come to be
considered a part of the system. (see Management
Information Systems)

129
Instructional Design - see instructional systems design.

Instructional Systems Design: the total set of procedures
that are followed in planning, developing, implementing,
and evaluating instruction. The procedures are derived
from knowledge of human learning relevant for instruction
and from the results of empirical data obtained during
tryouts of preplanned instruction. (Aronson & Briggs,
1983, p. 99)

Intelligent Computer Aided Instruction (ICAI)- a form of
computer aided instruction where the characteristics
of human tutoring are incorporated into the program
allowing instruction to adjust to different individual
student aptitudes. (see computer aided instruction)

Knowledge base: production rules, semantic networks,
frames, relational database and inference rules
critical to a specific domain application.

Loading an expert system shell: The process on entering
the knowledge base and rules into a computer program
that already has developed procedures for accessing
the knowledge base and applying the rules.

Natural language is a language that has developed over time
as part of the process of human interaction.

Management information systems (MIS) - a branch of computer
science/data processing concerned with the organization
and coordination of the information owned by a company so
that not only are day-to-day transactions processed, but
all levels of management are supplied with information
and supported in the use of technological tools for
decision making.

Problem solving - a higher order intellectual skill
consisting of the ability to make decisions or choices
by using multiple pieces of information.

Production-rule expert system: a relatively simple
expert system that consists of productions and rules
in the IF...THEN...Else format.

Programed instruction - instruction designed to present
learning in a step/sequence order, accompanied by
reinforcement. In recent years, programed instruction
has often implied drill and practice types of computer
aided instruction.

130

Prototyping: a method of development of computer programs
or systems that avoids extensive analysis and design
phases in development by creating working models of the
program or system. These models are tested and expanded
or modified until the complete system is finished. This
technique is usually significantly faster than any other
design techniques but risk omission of important
functions that were not considered during initial
development. Usually systems built by the prototype
method require frequent modification after installation.

Prototype: a working model of a system based on
information about the functions of the system. It is
the product of prototyping.

Rule-base: the collection of rules that indicate how
decisions are made or conclusions are reached in a
subject matter domain.

Shell: See Expert System Shell

Structured design methodology - the use of systems
concepts to decompose an information system into
functional subsystems and to define the boundaries and
interfaces of each subsystem.

Technological society - a society where the use of
technology has a major role in the performance of
routine activities.

User interface: a way of communicating with the user.
In expert systems, the user interface should close to
the user's natural language.

Working memory: for an expert system, a temporary
storage area to hold the immediately relevant portions
of the knowledge base, the user's responses, and the
current inference.

APPENDIX A

APPENDIX A

CURRENT INSTRUCTIONAL SYSTEMS AND DEVELOPMENTS

This appendix contains:

Five

Task

task

instructional systems models:

Core Elements Andrews/Goodson Tasks (page 132)
Stages of Instructional Design (page 133)
Courseware Design Model (page 134)
Michigan State University Instructional

Systems Procedure Model (page 136)
Information Relationships Among Learning

System Design Procedures. (page 137)
lists from the WW:
Data Entry tasks (page 138)
Computer Operations tasks (page 140)
Computer Programming tasks (page 143)
worksheets from the Guide:

CP-2 (page 146)
CP-S (page 150)
CP-ll (page 154)
CP-lS (page 158)

131

FIVE INSTRUCTIONAL SYSTEMS MODELS

Core Elements

Andrews/Goodson Tasks

 

Determine learner
needs

Assessment of need, problem identification
occupational analysis, competence, or
training requirements

Characterization of learner population

 

Determine goals and
objectives

Formulation of broad goals and detailed
subgoals stated in observable terms
Analysis of goals and subgoals for types
of skills/learning required

Sequencing of goals and subgoals to
facilitate learning

 

Construct assessment Development of pretest and post-test

procedures

Matching goals and subgoals

 

Design/select
delivery approaches

Formulation of instructional strategy to
match subject-matter and learner
requirements

Selection of media to implement strategies
Development of courseware based on
strategies

Consideration of alternative solutions to

-instruction

 

Try-out
instructional
system

Empirical try-out of courseware with
learner population, diagnosis of learning
and courseware failures, and revision of
courseware based on diagnosis

 

Install and
maintain system

Formulation of system and environmental
descriptions and identification of
constraints

Development of materials and procedures
for installing, maintaining, and
periodically repairing the instructional
program

Costing instructional program

 

Richey (1986,p 96) and Andrews and Goodson (1980)

Figure 12: Comparison of Core Elements and Common Tasks

132

10.

11.

12.

13..

14.

15.

Stages of Instructional Design

Assessment of needs, goals, and priorities

Assessment of resources and constraints, and selection of
a delivery system

Identification of curriculum and course scope and se-
quence

Determination of gross structure of courses
Determination of sequence of unit and specific objectives
Definition of performance objectives

Analysis of objectives for sequencing of enablers
Preparation of assessments of learner performance
Designing lessons and materials: (a) instructional
events: (b) media: (c) prescriptions (utilizing ap-
propriate conditions of learning)

Development of media, materials, activities

Formative evaluation

Field tests and revisions

Instructor training

Summative evaluation

Diffusion and operational installation

Briggs and Wager (1981, 5)

Figure 13: Stages of Instructional Design

133

134

 

 

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135

Various curriculum committees state goals in broad
terms

Instructor meets with Instructional Specialist

Instructor assesses course limits, number of students,
available finances, materials, etc.

Evaluation Specialist joins Instructor and Instructional
Specialist to assist in description of specific
objectives, content and behavoir

Instructor and Evaluation Specialist develop testing
situations which measure defined behavior

Instructor and Instructional Specialist compile completed
input information

Instructor and Instructional Specialist decide on group
size, teacher student ratio contact, communication
methods, experience factore, ect., based on theroy of
instruction

Instructor, Instructional Specialist, Media Specialist,
and other resource persons decide on information sources
and exemplars

Instructor and Media Specialist determine best models
based on perception and learning theory

Instructor and Media Specialist determine which of
various media is called for at points within the system

Instructor, Evaluation. Specialist, and Instructional
Specialist conduct representative dry runs of system
packages

Instructor, Instructional Specialist and Media Specialist
check feasibility' of system.‘with live audience and
related test samples

Hamreus, 1968, p. I-59

Figure 15: Legend

136

 

A etermine Broad Educational Goals
College - School - Dept. - Course

 

 

a

 

C [Gather Input Data |

 

 

L ,
D pecify Entry and Terminal Behavior]

 

Develop Rationale fo E
Pre and Post Exams

 

otal Input Data Combined]
Plan Strategies G l

H [Develop Teaching Examples]

 

 

of Determined Content

 

1 ,
| [Choose Representative Information Formq

 

 

1
[Decide on Transmission Vehiclea
I ,

 

 

 

 

 

 

 

J ,
Eollect, Design, Produce Specified Media]
' K [Dry Run-Through]
Develop Evaluation r
Instruments with Field Test Samples
tudent Data as Well L ith Student Group
5 Media Information *

 

 

 

 

 

1
Locate and Correct Flaws]

 

 

ppIication to Course |
J ,

Evaluation and Fla-Cycle
To Refine as Necessary

Note: Information feedback loops have been
deleted from this illustration.

 

 

Hamreus, 1968, p. l-59

Figure 15: Michigan State University Instructional Systems
Procedure Model.

137

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DE-l

DE-2

DE-3

DE-4

DE-lO

DE-ll

Data Entry Task

Ifléh

Manipulate switches, keys and levers using a
knowledge of the device operations to activate
a data entry device.

Manipulate switches, keys and levers using a
knowledge of the device operations to de-
activate a data entry device.

Analyze device malfunctions using a knowledge
of the device operations to identify the cause
of the malfunction as to whether it can be
corrected by the operator or is to be reported
to a service firm.

Manipulate switches, keys and levers using a
knowledge of the device operations to correct
malfunctions on a data entry device.

Manipulate switches, keys and levers using a
knowledge of the device operations to execute
standard service functions, such as changing
ribbons, cleaning screens, emptying chips and
other such services.

Manipulate switches, keys and levers using a
knowledge of the specific device to create a
program to control record format operations
such as skipping and duplicating.

Manipulate switches, keys and levers using a
knowledge of the specific device to load a
program to control record format operations
such as skipping and duplicating.

Manipulate switches, keys and levers using a
knowledge of the specific device to load media
onto or into a device for keying data.

Manipulate switches, keys and levers using a
knowledge of the specific device to select a
program format for a specific record.

Manipulate switches, keys and levers using a

knowledge of the specific device to enter data
onto a media.

138

DE-12

DE-13

DE-14

DE-lS

DE-16

DE-17

DE-18

DE-19

139

Isfik

Manipulate switches, keys and levers using a
knowledge of the specific device to verify by
machine the data previously entered into a
media by a keying device.

Analyze a data field using a knowledge of media
coding to verify visually the data previously
entered onto a media by a keying device.

Manipulate switches, keys and levers using a
knowledge of the specific device to duplicate
data from one record to another.

Manipulate switches, keys and levers using a
knowledge of the specific device to update data
contained in an existing record.

Write job information using a knowledge of
recording procedures to create a log of com-
pleted work.

Analyze written descriptions in technical
manuals using a knowledge of the device to
resolve problems with device operations.

Place media in a storage area using a knowledge
of storage techniques to maintain a media file
library in a logical sequence.

Place media in protective containers using a
knowledge of media storage techniques to store
media.

CO-l

CO-Z

CO-3

CO-4

CO-S

CO-6

CO-7

C0-8

CO-9

CO-lO

Computer Operations Task

11515

Arrange a group of jobs to be executed on a
computer using a knowledge of computer system
performance to minimize the operational steps
and overall run time.

Analyze operating instructions using a know-
ledge of media used with a specific system to
obtain the media needed for a specific job to
be executed on the computer.

Read operation instructions using a knowledge
of computer operations procedures to identify
the sequence of steps to be performed in
completing a specific job on the computer.

Inform persons who are assuming your duties of
the status of operations using a knowledge of
computer console operations and messages to
maintain uninterrupted operations.

Analyze operation instructions using a know-
ledge of peripheral equipment to identify the
media to be used with a specific job.

Analyze operating instructions using a know-
ledge of peripheral equipment to identify the
media to be used with a specific job.

Place media in a storage area using a knowledge
of storage techniques to maintain a media file
library in a logical sequence.

Manipulate protective containers using a
knowledge of data storage techniques to store
media in containers.

Manipulate switches and keys on a computer
console using a knowledge of computer console
operations to power up and initialize a com-
puter system.

Manipulate switches and keys on a computer
console using a knowledge of operating system
commands for a specific system to reassign
control functions such as priorities and memory
allocations.

140

CO-ll

CO-12

CO-13

CO-14

CO-15

CO-16

CO-17

C0-18

CO-19

CO-ZO

141

Ififik

Manipulate switches and keys on peripheral
devices using a knowledge of specific devices
to load media onto the device.

Select job control commands using a knowledge
of job control language to run a specific job
on a computer system.

Analyze messages produced on a console using a
knowledge of messages produced by a specific
operating system to identify the status of a
job being processed by a computer.

Analyze written descriptions in technical
manuals using a knowledge of a specific job
control language to interpret descriptions of
job control statements for a specific computer
system.

Compare computer produced output to a job
description sample using a knowledge of com-
puter media output to verify the accuracy of a
computer run.

Write information in a log using a knowledge of
computer operations to record information about
completed jobs.

Analyze machine generated output using a
knowledge of computer operations to identify
the cause of processing errors.

Manipulate switches and keys on a computer
console using a knowledge of a specific operat-
ing system to restart a program execution in
which an abnormal halt has occurred.

Manipulate levers, keys and switches on media
devices using a knowledge of the specific
devices to adjust operating performance of the
device.

Write information on labels using a knowledge
of cataloging descriptions to identify specific
media as to the data entry thy contain.

C0-21

C0-22

C0-23

CO-24

CO-25

142

11001:

Manipulate levers, switches and keys on media
devices using a knowledge of the specific
device to complete routine servicing normally
performed by the operator.

Interpret device performance indicators using a
knowledge of the specific device to identify a
machine malfunction.

Report verbally or in writing the malfunction
of a device using a knowledge of the reporting
procedure to notify service firms of the
malfunction.

Analyze operating instructions using a know-
ledge of back-up and restorations procedures to
identify files that need back-up.

Interpret system performance using a knowledge
of system performance to identify system
performance inefficiencies.

CP-l

CP-2

CP-3

CP-4

CP-S

CP-6

CP-7

CP-8

CP-9

Computer Programming Task

Task

Analyze a program request using a knowledge of
programming techniques to prepare an estimate

of the time involved in preparing an executing
a computer program.

Analyze a program request containing‘specifi-
cations using a knowledge of data processing
equipment and techniques to prepare program
documentation that describe the parameters
necessary to produce the desired output.

Analyze program specifications using a know-
ledge of file organizational types to prepare
file specifications to be described in the

program.

Analyze program specifications using a know-
ledge of data characteristics to identify
specific data characteristics to be described
in the program.

Analyze program specifications using a know-
ledge of programming techniques to construct a
guide to code the logical steps of a program.

Analyze written descriptions in technical
manuals using a knowledge of a specific
language to interpret descriptions of language
statements and operating characteristics of a
specific computer system.

Write language statements using a knowledge of
the specific language and program documents to
produce a source program coded in a specific
language.

Review a source program using a knowledge of
the specific language to identify coding errors
within the source program prior to compilation.

Key source statements into a device using a

knowledge of the device to produce computer
readable source statements.

143

CP-lO

CP-ll

CP-12

CP-13

CP-14

CP-15

CP-16

CP-17

CP-18

CP-19

CP-ZO

144

I§§B

Write job control statements using a knowledge
of job control language and the specific
operating systems to produce the instructions
necessary to compile a source program into an
object program.

Analyze error notation produced by a computer
using a knowledge of the specific language to
identify syntax errors in the source program.

Write source statements using a knowledge of
the specific language and an error notation
listing to produce corrected statements in a
source program.

Design data using a knowledge of data charac-
teristics to test the logical correctness of a

program.

Write job control statements using a knowledge
of job control language and the specific
operating system to produce the instructions
necessary to execute an object program.

Analyze output data produced by an object
program using a knowledge of the test data to
identify logical errors in the program.

Write source statements using a knowledge of
the specific language and output test data to
produce a corrected logical sequence in a
source program.

Analyze output of a test run with a user using
a knowledge of the program requirements to
obtain approval that the program is producing
the desired results.

Write user instructions using a knowledge of
the program logic and specifications to produce
a user's manual.

Collect program listings, test data, and other
specified documents using a knowledge of
documentation to produce documentation of the
design, coding and operation of the program.

Analyze program documentation using a knowledge
of programming techniques to produce a list of
coding changes to a computer program.

Task Ho.
CP-21

145

1:383

Write operating instructions using a knowledge
of the program logic and specifications to
produce an operations manual.

CURRICULUM WORKSHEET

 

 

Duty No. CP Task No. 2
Duty: Performing Activities Related to Computer Programming
Task: Analyze a program request containing specifications

using a knowledge of data processing equipment and
techniques to prepare program documentation that

describe the parameters necessary to produce the
desired output.

 

Pre-Test (Same as Achievement Indicators):
The learner:

1. Analyze the program request to determine des-
cription of input/output data and major proces-
sing parameters

2. Prepared a written general description of the
input files, output files and major processing
parameters and/or logic

 

References 0 Resources:

See Bibliography Nos. 1, 8, 9, 10, 11, 12, 13, 14, and 19 at
end of section.

 

146

Duty/task Number CP-2

 

BTUDENT LEARNING ACTIVITIES

TEACHER ACTIVITIES

 

1.

Participate in a class
discussion on how to ana-
lyze a program request to
determine description in-
put/output data and major
processing parameters.

Analyze a program re-
quest.

Prepare a written general
description of input/out-
put files and major pro-

cessing parameters and/or
logic.

Read assignments and
handouts to understand
how to accomplish the
task.

Use a flowcharting tem-
plate and flowcharting
instructions to correctly
flowchart a program re-
quest.

Student can describe the
files necessary to pro-
duce the desired output.

147

Take the class through
a simple program re-
quest showing them how
to write a general
description of the in-
put and output files
and major processing
parameters and/or log-
1c.

Assign readings and/or
handouts to accomplish
this task.

Assign readings and/or
handouts to teach sys-
tem flowcharting.

Provide flowcharting
templates.

Describe the input
Files.

Describe the output
files.

Hand out a sample nar-
rative to the class.

Duty/Task Number CP-2

 

TOOLS AND/OR EQUIPMENT

CONDITIONS

 

Central processing unit (CPU)
capable of COBOL, RPG, and
BASIC or access to a time-
sharing computer.

Cathode Ray Tubes (CRT)
devices for input and output.

Printer -- on-site.

An adequate number of work-
stations should be available
so that one half of the class
is involved in hands-on activ-
ities at any one time.

Other off-line data entry
equipment: key-to-tape, key-
to-diskette (floppy disk),
key-to-card.

The activity of writing
general descriptions for
input/output files and ma-
jor processing parameters
could be accomplished most
any place. These are the
kind of activities students
should be involved in when
they can't get on a work-
station.

 

Criteria: Competence in the task will be recognized when to
program documentation describes the data and logic
necessary to prepare file specifications, data
characteristics and a logic guide for the program.

 

148

Duty/Task Number CP-2

 

Post-Test

Q931_§t§;gm§n§_£1 - You will produce documentation that
describes the parameters necessary to produce a desired

output.
Esrfgrmanss_gbisstixs_il - Given a program request. You will

demonstrate the following tasks: (a) analyze the input/output
request and (b) prepare a written description of the input,
output, and required processing. Performance will be accepted
when documentation describes the data and logic completely,
enabling the file specifications to be written without error.

 

Bvaluation/reedback

149

CURRICULUM WORKSHEET

 

 

Duty No. CP Task No. 5
Duty: Performing Activities Related to Computer Programming
Task: Analyze program specifications using a knowledge of

programming techniques to construct a guide to code
the logical steps of a program.

 

Pre-Test (Same as Achievement Indicators):
The learner:

l. Analyze the specifications to determine the
organization of the logic necessary to produce
the desired output.

2. Prepared a guide to the logical structure of
the program by constructing a design document
accepted by the industry.

 

RCIOIODCOE & Resources:

See Bibliography Nos. 10, 11, 12, 13, 14, 15, and 19 at end of
section.

Reference Manuals

 

150

Duty/task Number CP-5

 

STUDENT LEARNING ACTIVITIES

TEACHER ACTIVITIES

 

1. Student can read the text
material.

2. Student can diagram
(flowchart) problems.

3. Student can write the
logic steps in an orderly
fashion (IOP chart).

4. Students can exchange
logic guides and check
for each others errors.

5. Participate in.a class
discussion about program
flowcharting.

6. Write a detailed
flowchart.

7. Determine the necessary
calculations or proces-
sing steps in a program.

8. Determine the logical
steps in a program.

151

Explain uses of flow-
charting symbols (if
used).

Explain a situation
requiring program to
student.

Lead a class discus-
sion about detailed
program flowcharting.

Provide sample flow-
chart.

Provide flowcharting
templates.

Demonstrate the pro-
gramming cycle.

Place solution to the
problem on chalkboard
or overhead projector.

Duty/Task Number CP-S

 

TOOLS AND/OR EQUIPMENT

CONDITIONS

 

Central processing unit (CPU)
capable of COBOL, RPG, and
BASIC or access to a time-
sharing computer.

Cathode Ray Tubes (CRT)
devices for input and output.

Printer -- on-site.

An adequate number of work-
stations should be available
so that one half of the class
is involved in hands-on activ-
ities at any one time.

Other off-line data entry
equipment: key-to-tape, key-
to-diskette (floppy disk),
key-to-card.

Flowcharting template.
Overhead projector.

Chalkboard.

This is an individualized
and/or group activity which
could be accomplished in or
out of the classroom with
no equipment needed. An
appropriate supply of card
layouts and printer spacing
charts are necessary. An
appropriate supply of flow-
charting templates and cod-
ing sheets are necessary.

 

Criteria: Competence in the task will be recognized when the
design of the logic describes the processing needed
to produce the output according to techniques used

within the industry.

 

152

Duty/Task Number CP-S

 

Post-Test

§g§1_§;§;gmgnt_11 - You will construct a guide to code the
logic steps of the program.

W11 - Given a program statement and the

necessary tools, the student will construct a guide to code
the logic of the problem. Performance will be accepted when
the guide correctly describes the logic necessary to solve the
problem and is completed according to techniques used within
the industry. .

 

Evaluation/Feedback

153

CURRICULUM WORKSHEET

 

 

Duty No. CP Task No. 11
Duty: Performing Activities Related to Computer Programming
Task: Analyze error notation produced by a computer using

a knowledge of the specific language to identify
syntax errors in the source program.

 

Pre-Test (Same as Achievement Indicators):

The learner:

l. Matched each error in the error listing with
the source statement

2. Noted the nature of the error in the source

statement according to the specific language
structure

 

References 0 Resources:

See Bibliography Nos. 10, 11, 12, 13, 14, and 19 at end of
section.

Reference Manuals

 

154

Duty/task Number CP-ll

 

 

STUDENT LEARNING ACTIVITIES TEACHER ACTIVITIES
1. Know when, where, and how 1. Describe the common
to get program diagnos- errors encountered in
tics. similar programs and
enumerate the possible
2. Participate in a group reasons for the
discussion on debugging errors.
programs.
2. Help individual stu-
3. ~ Be able to debug a pro- dents find particular-
gram without assistance. ly difficult errors.
4. Correctly use available :1. Demonstrate how to
debugging tools or de- debug a program.
vices.

4. Provide a handout of a
program for debugging.

5. Provide and demon-
strate whatever debug-
ging tools and devices
that are available.

155

Duty/Task Number CP—ll

 

 

TOOLS AND/0R EQUIPMENT CONDITIONS

Central processing unit (CPU) A classroom situation

capable of COBOL, RPG, and should be available that

BASIC or access to a time- allows students the oppor-

sharing computer. tunity to identify and cor-
rect syntax errors. Refer-

Cathode Ray Tubes (CRT) ence manuals and debugging

devices for input and output. templates should be avail—

able.

Printer -- on-site.

An adequate number of work-
stations should be available
so that one half of the class
is involved in hands-on activ-
ities at any one time.

Other off-line data entry
equipment: key-to-tape, key-
to-diskette (floppy disk),
key-to-card.

Debug template.

 

Criteria: Competence in the task will

be recognized when all

errors have been identified as to type.

 

156

Duty/Task Number CP-ll

 

Post-Test

fig;1_§tgtemgnt_11 - You will identify syntax errors in the
source program.

Performance Objective i; - Given a source listing and an error
listing produced by the compiler, you will identify the syntax
errors in the source listing. Performance will be accepted
when all errors have been identified.

 

Evaluation/Feedback

157

CURRICULUM WORKSHEET

 

 

Duty No. CP Task No. 15
Duty: Performing Activities Related to Computer Programming
Task:l Write source statements using a knowledge of the

specific language and output test data to produce a
corrected logical sequence in a source program.

 

Pre-Test (Same as Achievement Indicators):

The learner:

1. Selected the coding sheets for the specific
language

2. Wrote the statements to correct the logical
errors using a source listing

 

References 5 Resources:

See Bibliography Nos. 10, 11, 12, 13, 14, and 19 at end of
section.

Reference Manuals

 

158

Duty/task Number CP-15

 

 

STUDENT LEARNING ACTIVITIES TEACHER ACTIVITIES

1. Students can write the 1. Provide handouts to
language statements in cover the procedure
corrected form, to elim- for correcting a
inate the errors. printout.

2. Using system input device 2. Demonstrate techniques
to correct errors in the for horizontal and
source program. vertical centering.

3. Recompile and execute the :3. Ensure that the stu-
job control statements. dent understands why

the original state-
ments were in error.

159

Duty/Task Number CP-15

 

TOOLS AND/OR EQUIPMENT

CONDITIONS

 

Central processing unit (CPU)
capable of COBOL, RPG, and
BASIC or access to a time-
sharing computer.

Cathode Ray Tubes (CRT)
devices for input and output.

Printer -- on-site.

An adequate number of work-
stations should be available
so that one half of the class
is involved in hands-on activ-
ities at any one time.

Other off-line data entry
equipment: key-to-tape, key-
to-diskette (floppy disk),
key-to-card.

Spacing rulers.

In a laboratory situation
the students will retrieve
their printout, proofread
for logical errors and cor-
rect these errors. Stu-
dents should use vertical
and horizontal rules dis-
cussed in the class.
Printer spacing charts
should be provided for stu-
dent use.

 

Criteria: Competence in the task will be recognized when the
object program is error free and executes as des-
cribed in the program specifications.

 

160

Duty/Task Number CP-lS

 

Post-Test

anl Statement #1 - You will write corrected source code to
eliminate logical errors in your source program.

Earfigzmanca Objectiva £1 - Given a source listing with logical

errors identified, and an output listing with erroneous data,
the student will write the source code correctly to eliminate
all errors. Performance will be accepted when the object
program produces an output listing with correct data.

 

Evaluation/Feedback

161

APPENDIX B

APPENDIX B

DATA FLOW DIAGRAMS FOR DEVELOPING A COMPUTER PROGRAM

This Appendix contains the data flow diagrams showing
the design for the instruction to teach students how to

develop computer programs to solve problems.

Designing a Computer Program

Define the Problem 1.0

Define specific outputs 2.0

Define specific inputs 3.0

Define processing sequence and detailed

process 4.0

Represent process specifications

graphically 5.0

Develop program detail code 6.0

Test program 7.0
Debug program 8.0
Evaluate program 9.0

162

(Page
(page
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(page

(Page

(Page
(page
(page
(page
(page

164)
166)
167)
168)

169)

170)
172)
173)
174)
175)

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APPENDIX C

APPENDIX C

AN EXPERT SYSTEM AID TO DEBUGGING BASIC PROGRAMS

S A M P L E K N O W L E D G E B A S E
D E B U G

an aid to debugging basic programs

.- 0- .- 0- O- 0- O-
O- 0- .- 0- O- 0- 0- 0-

O.

!

TITLE Debugging Aid to basic programs DISPLAY
I

D E B U G
DEBUGGING AID FOR BASIC PROGRAMS

Debugging aid to basic programs is a knowledge base
designed to guide the introductory basic student
through the process of identifying unknown errors in
a basic program. Debug will assist the student in:

- identifying the type of error in the program

- determining the type of language or logical error

- determining the cause of the error

- determining the solution to the error

DEBUG is a prototype system that is restricted in scope to a
number of errors commonly made by introductory basic students.

176

177

NEXT without FOR Syntax error

RETURN without GOSUB Out of data

Illegal function call Undefined line number
Subscript out of range Duplicate Definition

Division by zero Type Mismatch

can't continue Missing operand
Device Timeout Device Fault

FOR without NEXT Out of paper

WHILE without WEND WEND without WHILE
Advanced Feature FILE handling ERRORS

The data contained in DEBUG has been extracted from the
Microsoft Corp. BASIC IBM Personal Computer Hardware
Reference Library, and based on the experience of the
Shiawassee County Vocational Data Processing Instructor:
Mary Garrett.
1
!
THRESHOLD = 60
CONFIDENCE OFF
!
1. The error belongs to Logic errors
1.1 error is program output in error
1.1.1 correct error by reformatting output

1.1.2 correct error by reassigning algorithms
1.1.3 correct error by adding more output lines
1.1.3.1 correct error by adding print lines
to condition.
1.1.3.2 correct error by adding total print
lines
1.1.4 correct error by adding a GO T0 line
1.2 error is program does not stop
1.2.1 correct error by changing the GO TO
1.2.2 correct error by checking for trip data input
1.2.3 correct error by adding end option to menu
1.3 error is program stops but has no output
1.3.1 correct error by adding print (output) lines
1.3.2 correct error by moving print (output) lines

2. The error belongs to language errors
2.1 NEXT .... FOR error DISPLAY fornext
2.1.1 correct error by matching FOR and NEXT

variables

2.1.2 correct error by proper nesting of FOR
...NEXTs

2.1.3 correct error by matching FOR and NEXT
statements

2.1.4 correct error by removing GO TO to a line
inside the loop

2.1.5 correct error by clearing FOR..NEXT variable

Undefined line number DISPLAY undefined line number

RETURN without GOSUB DISPLAY RETURN without GOSUB

MN
UN

2.4 Out of data DISPLAY
2.4.1 correct error
READ
2.4.2 correct error
statements
2.4.3 correct error
2.4.4 correct error
with READ
2.4.5 correct error
2.4.6 correct error

READ variables

178

out of data

by
by

by
by

by
by

2.5 can't continue DISPLAY
2.6 Advanced Feature DISPLAY advanced feature
2.7 Subscript out of range DISPLAY subscript out of

range

checking for trip data after
adding trip data to DATA

matching check with trip data
matching variable in check

adding to the trip data
matching the DATA with the

can't continue

2.7.1 correct error by adding a dimension statement
fixing a logic error

2.7.2 correct error by

2.7.3 correct error
subscipt

2.7.4 correct error

2.7.5 correct error

by
by
by

increasing dimension statement
moving the dimension statement

fixing a typing error

2.8 Division by zero DISPLAY division by zero

2.9 Duplicate Definition DISPLAY duplicate definition
2.9.1 correct error by removing a definition
2.9.2 correct error by moving a definition
2.9.3 correct error by changing a goto

2.10 Missing operand DISPLAY missing operand

2.11 Type mismatch DISPLAY type mismatch
2.11.1 correct error by putting quotes around a

string constant

2.11.2 correct error by putting a $ at the end of a

variable name

2.11.3 correct error by changing print using image
2.11.4 correct error by changing variable type in a

function

2.11.5 correct error by converting a type
2.11.5.1 convert a string to number DISPLAY
string to number
2.11.5.2 convert a number to string DISPLAY
number to string
2.12 WHILE .... WEND error DISPLAY whilewend
2.12.1 correct error by matching WHILE and WEND

statements

2.12.2 correct error by removing GO TO to between

WHILE and WEND

2.13 Illegal function call DISPLAY illegal function
2.13.1 correct error by defining PRINT USING image
2.13.2 correct error by changing values in a

string function
2.13.2.1 assign a value to string variable
in function

I
! RULES FOR DETERMINING LOGICAL

!
RULE
IF
THEN
AND
ELSE
AND
!
RULE
IF
AND
THEN
1

2.13.3
2.13.4
2.13.5
2.13.6
2.13.7
2.14 Device
2.14.1
2.14.2
2.14.3
2.14.4
2.15 Syntax
2.15.1
2.15.2
2.15.3
2.15.4

2.15.5
2.15.6

2.15.7
2.15.8

2.15.9

For determining belongs to

179

2.13.2.2 shorten string length variable in
string function
correct error by changing argument in a
function
correct error by changing negative or large
subscript
correct error by not assigning a negative
record number
correct error by not raising a negative
number to a power
correct error by not trying to delete a
nonexistent line
error or out of paper DISPLAY device error
correct error by turning on printer
correct error by pressing select button on
printer
correct
printer
correct
printer
error DISPLAY
correct error
correct error
correct error
correct error
correct error
correct error by
2.15.6.1 correct
2.15.6.2 correct
USING
correct error by using :
with message
correct error by correctly assigning values
correct error by adding a variable after an
AND or OR
correct error by
function

error by connecting or replacing
cable
error by putting paper in the

syntax error

changing READ and/or DATA
adding a space

fixing the spelling

changing variable name
matching parenthesis

fixing punctuation

error by using , with READ
error by using : with PRINT

2.15.6.3 with INPUT

adding missing term in a

ERROR

Logic errors

The program runs

The error belongs to Logic
DISPLAY CHARACTERISTICS OF

errors
THE LOGIC ERROR

The error belongs to language errors
DISPLAY CHARACTERISTICS OF THE LANGUAGE ERROR

for differentiating Logic error
The error belongs to Logic errors
the program IS has output

error is program output in error

RULE
IF
AND
AND
THEN

RULE
IF
AND
THEN
AND

RULE
IF
AND
THEN
AND

RULE
IF
AND

THEN
AND

RULE
IF
AND
THEN
AND
ELSE
AND

RULE
IF
AND
THEN

RULE
IF
AND
AND
THEN
AND

RULE
IF
AND
AND
THEN
AND

180

for differentiating program output in error
error is program output in error

the program output IS has the correct values
the output does not match the planned output
correct error by reformatting output

for differentiating program output in error

error is program output in error

the program output IS does not have the correct values
correct error by reassigning algorithms

DISPLAY algorithms

for differentiating program output in error

error is program output in error

the program output IS some expected output is missing
correct error by adding more output lines

DISPLAY add print lines to condition

for differentiating program output in error
error is program output in error
the program output IS there is only one line of detail

output

correct error by adding a GO T0 line
DISPLAY add a GO T0 line

for differentiating correct error by adding output
correct error by adding more output lines

the program total lines are not missing

correct error by adding print lines to condition
DISPLAY add print lines to condition

correct error by adding total print lines

DISPLAY adding total print lines

For differentiating Logic error
The error belongs to Logic errors
the program IS does not stop
error is program does not stop

For differentiating program does not stop
error is program does not stop

the program has a main menu.

the menu does not have an end option
correct error by adding end option to menu
DISPLAY end option to menu

For differentiating program does not stop
error is program does not stop

the program uses INPUT to get new data

after the INPUT does not check for trip data
correct error by checking for trip data input
DISPLAY check for trip data

RULE
IF
AND
AND
THEN
AND
1
RULE
IF
AND
THEN
!
RULE
IF
AND
THEN
AND
ELSE
AND
I

181

For differentiating program does not stop
error is program does not stop

the program checks for trip data

there is no menu or a menu with an end option
correct error by changing the GO TO

DISPLAY GO TO

For differentiating Logic error

The error belongs to Logic errors

the program IS no output

error is program stops but has no output

For differentiating program stops but has no output
error is program stops but has no output

the program does not have print (output) lines
correct error by adding print (output) lines
DISPLAY add print lines

correct error by moving print (output) lines
DISPLAY move print lines

1 RULES FOR DIFFERENTIATING LANGUAGE ERROR

!
RULE
IF
AND
THEN
AND
!
RULE
IF
AND
AND

THEN
AND
!
RULE
IF
AND
AND

THEN
AND
I
RULE
IF
AND
AND

THEN
AND
1

For differentiating NEXT .... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE cross

correct error by proper nesting of FOR ...NEXTs

DISPLAY prOper nesting of FOR ... NEXTs

For differentiating NEXT .... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE do not cross

the FOR variable IS does not match connected NEXT
variable

correct error by matching FOR and NEXT variables

DISPLAY match FOR ... NEXT variables

For differentiating NEXT .... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE do not cross

the FOR variable IS is not connected to a NEXT

statement

correct error by matching FOR and NEXT statements

DISPLAY match FOR and NEXT statements

For differentiating NEXT..... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE do not cross

the FOR variable IS extra NEXT is connected to the FOR

statement

correct error by matching FOR and NEXT statements

DISPLAY match FOR and NEXT statements

RULE
IF
AND
AND

AND
THEN

RULE
IF
AND
AND

AND
THEN
AND

RULE
IF
AND
THEN
AND

RULE
IF
AND
THEN
AND

RULE
IF
AND

THEN
AND

RULE
IF
AND

AND

RULE
IF
AND
THEN
AND

182

For differentiating NEXT .... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE do not cross
the FOR variable 18 matches the connected NEXT
variable

the program has IS a GO TO to a line inside the loop
correct error by removing GO TO to a line inside the

loop

DISPLAY removing branch to inside loop

For differentiating NEXT .... FOR error

NEXT .... FOR error

the lines connecting FOR ... NEXT ARE do not cross
the FOR variable IS matches the connected NEXT
variable

the program has IS no Go TO to a line inside the loop
correct error by clearing FOR..NEXT variable

DISPLAY clearing FOR..NEXT variable

For differentiating Out of data

Out of data .
the error IS is no check for trip data after the READ
correct error by checking for trip data after READ
DISPLAY correct Out of Data

For differentiating Out of data

Out of data

the error IS is no trip data in the DATA statements
correct error by adding trip data to DATA statements
DISPLAY correct Out of Data

For differentiating Out of data

Out of data

the error IS is check for trip data not same as in
DATA

correct error by matching check with trip data
DISPLAY correct Out of Data

For differentiating Out of data

Out of data

the error IS is variable READ is not variable in Check
correct error by matching variable in check with READ
DISPLAY correct Out of Data

For differentiating Out of data

Out of data

the error IS not enough data after the trip data
correct error by adding to the trip data

DISPLAY correct Out of Data

RULE
IF
AND
THEN

AND

RULE
IF
THEN
AND

RULE
IF
THEN

RULE
IF
THEN
AND

RULE

AND
THEN
AND

RULE
IF
AND
AND
THEN
AND

RULE

AND
AND

THEN
AND

AND
AND

183

For differentiating Out of Data

Out of data

the error IS what is being READ doesn't match the DATA
correct error by matching the DATA with the READ
variables

DISPLAY matching the DATA with the READ variables
DISPLAY correct Out of Data

For advanced feature

the error message is advanced feature
advanced feature

DISPLAY advanced feature

For can't continue

the error message is can't continue
can't continue

DISPLAY can't continue

FOR undefined line number

the error is undefined line number
undefined line number

DISPLAY undefined line number

For differentiating Subscript out of range
Subscript out of range

there is a dimension statement IS False
correct error by adding a dimension statement
DISPLAY adding a dimension statement

For differentiating Subscript out of range
Subscript out of range

there is a dimension statement IS True

the value of subscript in error < 1

correct error by fixing a logic error

DISPLAY subscript out of range by logic error

For differentiating Subscript out of range
Subscript out of range

there is a dimension statement IS True

the value of subscript in error > value in the
dimension statement

correct error by increasing dimension statement
subscript

or correct error by fixing a logic error

DISPLAY picking the value for a dimension statement
DISPLAY subscript out of range by logic error

RULE
IF
AND
AND

AND
AND

THEN

AND
AND
!
RULE
IF
AND
AND

AND

THEN
!
RULE
IF
AND
AND

THEN
AND
!
RULE
IF
AND

THEN
AND
AND
!
RULE
IF
AND
AND
AND

184

For differentiating Subscript out of range
Subscript out of range

there is a dimension statement IS True

the value of subscript in error <= value in the
dimension statement

DISPLAY typing errors on subscripts

the dimensioned variable IS matches the variable in

error

the dimension is being cleared by a CLEAR or other
statement ‘

correct error by moving the dimension statement
DISPLAY moving the dimension statement

For differentiating Subscript out of range
Subscript out of range

there is a dimension statement IS True

the value of subscript in error <= value in the
dimension statement

the dimensioned variable IS does not match the
variable in error

correct error by fixing a typing error

For differentiating duplicate definition
Duplicate Definition

DISPLAY how to find array being defined twice
duplicate definition IS caused by an array being
defined twice

correct error by removing a definition

DISPLAY other than removing a definition

For differentiating duplicate definition

Duplicate Definition

duplicate definition IS caused by an OPTION BASE
command

correct error by moving a definition

or correct error by moving the OPTION BASE command
DISPLAY moving the OPTION BASE command

For differentiating duplicate definition

Duplicate Definition

duplicate definition IS caused by something else
DISPLAY the two other causes of duplicate definition
the array was IS set to the default size of 10 before

the definition

THEN

correct error by moving a definition

RULE
IF
AND
AND

THEN
AND

RULE
IF
AND
WEND
THEN
AND

RULE
IF
AND
AND
THEN

RULE

IF
AND
AND
THEN
AND

RULE
IF
AND
THEN
RULE
IF
AND
AND

THEN
AND

185

For differentiating duplicate definition

Duplicate Definition

duplicate definition IS caused by something else
the array was IS not set to the default size of 10
before the definition

correct error by changing a goto

or some other method

For differentiating WHILE .... WEND error
WHILE .... WEND error
the lines drawn ARE each WHILE does not connect to a

correct error by matching WHILE and WEND statements
DISPLAY match WHILE and WEND statements

For differentiating WHILE .... WEND error

WHILE .... WEND error

the lines drawn ARE each WHILE connects to a WEND
the program has IS a GO TO to a line inside the loop
correct error by removing Go To to between WHILE and
WEND

DISPLAY removing branch to between WHILE and WEND

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS a PRINT USING image
the PRINT USING image is not defined

correct error by defining PRINT USING image
DISPLAY PRINT USING image

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS a string function

correct error by changing values in a string function

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

correct error by changing values in a string function
the value assigned to the function's string variable
is null

assign a value to string variable in function

DISPLAY value string

RULE
IF
AND
AND

THEN
AND

RULE

IF
AND

THEN
AND

RULE

IF
AND

THEN
AND

RULE
IF
AND
THEN
AND
RULE

IF
AND

THEN

RULE

IF
AND

THEN

AND
U

186

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

correct error by changing values in a string function
the value of the length variable in the function is
wrong

shorten string length variable in string function
DISPLAY length string

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS a function other than a
string

correct error by changing argument in a function
DISPLAY argument

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS contains an arrayed
variable

correct error by changing negative or large subscript
DISPLAY negative subscript

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS a GET or PUT statement
correct error by not assigning a negative record
number

DISPLAY GET/PUT

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS a variable raised to a
power

correct error by not raising a negative number to a
power

DISPLAY negative power

For differentiating Illegal function call DISPLAY
illegal function

Illegal function call

the error line contains IS command to delete a line or

lines

correct error by not trying to delete a nonexistent
line
DISPLAY delete line

RULE
IF
AND
THEN

RULE
IF
AND
THEN

RULE

AND
THEN

RULE
IF
AND
THEN
AND

RULE

AND
THEN
AND

RULE
IF
AND
AND
THEN

RULE
IF
AND
THEN

RULE
IF
AND
AND
THEN

RULE
IF
AND
THEN
AND

187

For differentiating Device error
Device error or out of paper

the printer IS not turned on
correct error by turning on printer

For differentiating Device error

Device error or out of paper

the printer IS on, but the select button is not on
correct error by pressing select button on printer

For differentiating Device error

Device error or out of paper

the printer IS on and the select button is on

correct error by connecting or replacing printer cable

For differentiating out of paper

Device error or out of paper

the printer IS the paper light is on

correct error by putting paper in the printer
DISPLAY out of paper

For differentiating syntax error

Syntax error

the syntax error is on a DATA statement
correct error by changing READ and/or DATA
DISPLAY correct DATA syntax error

For differentiating syntax error

Syntax error

DISPLAY a space may be needed.

there is no space between two variables/commands
correct error by adding a space

For differentiating syntax error
Syntax error

you mistyped the name of a command
correct error by fixing the spelling

For differentiating syntax error

Syntax error

DISPLAY keywords can cause syntax errors
there is a reserved word in the variable name
correct error by changing variable name

For differentiating syntax error
Syntax~error

there is not an equal number of "(" and ")"
correct error by matching parenthesis
DISPLAY matching parenthesis

RULE

AND

THEN

RULE

THEN

RULE

188

For differentiating syntax error

Syntax error

error line has READ or PRINT USING or INPUT with
message

correct error by fixing punctuation

For differentiating punctuation errors
correct error by fixing punctuation
the error line IS has a READ statement
correct error by using , with READ
DISPLAY using a , with READ

For differentiating punctuation errors
correct error by fixing punctuation

the error line IS has a PRINT USING statement
correct error by using ; with PRINT USING
DISPLAY using a ; with PRINT USING

For differentiating punctuation errors

correct error by fixing punctuation

the error line IS has an INPUT with message statement
correct error by using ; with INPUT with message
DISPLAY using a ; with INPUT with message

For differentiating syntax error

Syntax error

there is an expression to the left of an equal sign
correct error by correctly assigning values

DISPLAY how to correctly assign values

For differentiating syntax error

Syntax error

there is constant to the left of an equal sign
correct error by correctly assigning values
DISPLAY how to correctly assign values

For differentiating syntax error

Syntax error

the error was on an IF statement

DISPLAY how to check AND and OR

an AND or OR is missing a value

correct error by adding a variable after an AND or OR

For differentiating syntax error

Syntax error

correct error by adding missing term in a function
or correct error by other

DISPLAY correct syntax error by other

189

RULE For differentiating type mismatch

IF Type mismatch

AND type of values you are working with IS strings

AND you are assigning a constant

AND the constant does not have quotes around it

THEN correct error by putting quotes around a string
constant

1.

RU For differentiating type mismatch

IF Type mismatch

AND type of values you are working with IS strings

AND the variable being assigned the string does not end
with a $

THEN correct error by putting a $ at the end of a variable

name

AND DISPLAY put 5 on all

!

RULE For differentiating type mismatch

IF. Type mismatch

AND error was with a PRINT USING

THEN correct error by changing PRINT USING image

AND DISPLAY correcting PRINT USING image

!

RULE 'For differentiating type mismatch

IF Type mismatch

AND error from function (SWAP, LEFT$, ...) except IF and
LET

AND type of values you are working with IS numbers

THEN correct error by changing variable type in a function

AND DISPLAY changing variable type in a function

AND DISPLAY number to string

!

RULE For differentiating type mismatch

IF Type mismatch

AND error from function (SWAP, LEFT$, ...) except IF and
LET

AND type of values you are working with IS strings

THEN correct error by changing variable type in a function

AND DISPLAY changing variable type in a function

AND DISPLAY string to number

!

RULE For differentiating type mismatch

IF Type mismatch

AND error from function (SWAP, LEFT$, ...) except IF and
LET -

AND type of values you are working with IS mixed

THEN correct error by changing variable type in a function

AND DISPLAY changing variable type in a function

AND DISPLAY string to number

AND DISPLAY number to string

!

190

RULE For differentiating type mismatch

IF Type mismatch .
AND type of values you are working with IS mixed
THEN correct error by converting type

!

RULE For differentiating converting type

IF correct error by converting type

AND You are using IS string with numbers
THEN convert a string to number

AND DISPLAY string to number

L

RULE For differentiating converting type

IF correct error by converting type

AND You are using IS number with strings
THEN convert a number to string

AND DISPLAY number to string

!

DISPLAY syntax error

A syntax error is what the computer uses to say that it has
no better way of describing the error. One of the most
common causes of a syntax error is a typing error. Make
sure that all commands on the line with the error are
correctly spelled.

!

DISPLAY matching parenthesis

If the number of left parenthesis isn't the same as the
number of right ones, then you must find where the extra
or missing one is. When nesting commands and subscripted
variables it is easy to forget to add a ). Start from the
inside and work your way out, writing down the steps on
paper if needed. This way you can find where you are
missing or have an extra parenthesis. Here is an example:

(Y*((3+4)/S(X))/5
(3+4) start from the inside
(3+4)/S(X) and work your way out
((3+4)/S(X))

Y*((3+4)/S(X))

(Y*((3+4)/S(X))/5 <-- Missing a right ). We can

(Y*((3+4)/S(X)))/5 then add the missing ).

!

DISPLAY using a , with READ

There are two ways to get syntax error with a READ.

One is to just have a READ without specifying what to READ
the data into. The other is to use the wrong type of
punctuation with the READ command. Here is an example:

10 READ A$;B$;C$ should be 10 READ A$,B$,C$
!

DISPLAY using a 3 with PRINT USING

The first value after a PRINT USING statement is the

191

format in the form of a string. The format must be
separated from the other values to be printed using a ;.
If you use a comma, it will result in a syntax error.
Here is an example of the correct way to use PRINT USING:

100 PRINT USING” ####.## \ \":N,A$
or

10 Is = " ####.## \ \"

100 PRINT USING I$;N,A$
I

DISPLAY using a : with INPUT with message

Whenever you use the INPUT with Message form of INPUT, you
must place a : between the message and the first variable
that will be input. If you omit the ; or use a comma, the
result will be a syntax error. Here is an example of the
correct way to use INPUT with a message:

100 INPUT ”what is your age"; A

200 INPUT "Enter starting date , ending date";SD,ED

!
DISPLAY how to correctly assign values
A common error to beginning students is to place things
on the wrong side of the equal sign. Whatever is on the
left side of the = is replaced with what is on the right
side after being evaluated. You can not normally have a
command on the left side of the = with the exception of
LET and MIDS. Example:

10 Y + Z = X
This will not work. If you switch the left and right sides
you will get:

10 X 8 Y + Z
and this will cause the computer to replace the old value
of X with the sum of Y and 2 when line 10 is executed.
You also can not assign a value to a constant.
!
DISPLAY how to check AND and OR
If you are using AND or OR, then you might be using it
incorrectly. Here is an example of how it can be used
incorrectly to cause a syntax error:

10 IF A<B OR >C THEN 100
There must be an expression on both sides of an AND and OR.
The line above could be corrected by changing it to:
10 IF A<B OR A>C THEN 100

192

!

DISPLAY correct syntax error by other

If none of the other possibilities are true, then you need
to look up the command that the error occurred on, and check
the syntax of the command. It is also possible that you

put two commands on one line without properly separating
them with a :.

One common mistake is leaving out a term from a command.
Here is an example:

100 IF LEFT$(AS) = "Y” THEN 10
This should be corrected as follows:

100 IF LEFT$(A$,1) = "Y" THEN 10

1

DISPLAY correct DATA syntax error

A syntax error on a data statement is caused by trying to
read a number, when the information on the DATA line
contains a non—number.

You should first find out the location of the READ
statement that is giving the problem. Use TRON/TROFF to
help you find it.

A common cause of this error, is getting the DATA out of
sync with the READ. Check the data statements, and if a
string you wish to read contains either a "," or a ":" then
enclose that part of the data in quotes. Example:

10 Read T$

100 DATA "Subject: Computers"
!
DISPLAY a space may be needed
BASIC requires a space between most variables, keywords
and numbers. If you run things together, the computer will
not be able to pull them apart and break it down. A space
is not needed after a number, and after a special symbol
such as <>()=+-*/‘:. Check the line with the error and see
if you need a space.

Here are a few examples:

Incorrect: Minimum spacing:
10 FORA=1TO3 10 FOR A=1TO 3
20 PRINTA;A*A 20 PRINT A;A*A
30 NEXTA 30 NEXT A

!

DISPLAY keywords can cause syntax errors

Sometimes if you have a reserved word inside of a variable
name, it will cause a syntax error. In some instances it is
allowable to have a reserved word in a variable name. A
reserved word in a variable will give the most trouble if

it starts the variable name. Here is the list of all the

reserved words in BASIC.
variables on the line with the error contains one.

1
!

193

Check and see if any of the

ABS AND ASC ATN AUTO BEEP
BLOAD BSAVE CALL CDBL CHAIN CHR$
CINT CIRCLE CLEAR CLOSE CLS COLOR
COM COMMON CONT COS CSNG CSRLIN
CVD CVI CVS DATA DATES DEF
DEFDBL DEFINT DEFSNG DEFSTR DELETE DIM
DRAW EDIT ELSE END EOF EQV
ERASE ERL ERR ERROR EXP FIELD
FILES FIX FN FOR FRE GET
GOSUB GOTO HEXS IF IMP INKEYS
INP INPUT INPUT# INPUTS INSTR INT
KEY KILL LEFT$ LEN LET LINE
LIST LLIST LOAD LOC LOCATE LOF
LOG LPOS LPRINT LSET MERGE MID$
MKD$ MKI$ MKS$ MOD MOTOR NAME
NEW NEXT NOT OCT$ OFF ON
OPEN OPTION OR OUT PAINT PEEK
PEN PLAY POINT POKE POS PRESET
PRINT PRINT# PSET PUT RANDOMIZE READ
REM RENUM RESET RESTORE RESUME RETURN
RIGHTS RND RSET RUN SAVE SCREEN
SGN SIN SOUND SPACES SPC( SQR
STEP STICK STOP STR$ STRIG STRINGS
SWAP SYSTEM TAB( TAN THEN TIME$
TO TROFF TRON USING USR VAL
VARPTR VARPTRS WAIT WEND WHILE WIDTH
WRITE WRITE# XOR -

DISPLAY type mismatch

A type mismatch error is caused by trying to use one type
variable when the computer is expecting a different type.
The two most common errors, are mixing a string with a
numeric value, and mixing a numeric value with a string.
Another possible cause is trying to SWAP two variables of
different type. If you wish to transfer from one type to
another, then use the conversion functions VAL and STR$.
Here are some examples that will cause this error.

Incorrect Correct Assuming

A = "JOE" As = "JOE"

B$ a A B$ = STR$(A) You want to store the
string equivalent of
the value in A.

A = 3 / C$ A = 3 / VAL(C$) C$ in known to contain

a number, and you wish
to divide 3 by that num-
ber.

194

!
DISPLAY put $ on all
You will need to put the s after all string variables.
Make sure that you add the $ to all locations where you
have string variables in your program. You can
also use DEFSTR to make a variable into a string without
the s, but if you do this, you must treat the variable
as if the variable had a $ at the end of it.
!
DISPLAY correcting PRINT USING image
A type mismatch error will occur with a PRINT USING if the
format doesn't match the type of variables being printed.
Check your format, and compare the types that it defines
with those of the variables. Also, some characters have
special meaning, and if you wish to display them, you must
use the _ (underscore) character.

First character of a string

\n spaces\ A string of n+2 characters

& Variable length string field

# A digit in a number

+ beginning or end of ### format

- beginning or end of ### format
** fill leading spaces with asterisks
$$ floating $
**$ floating $ with leading asterisks

AAAA

specify exponential format
_ (underscore) print next character exactly

If you wish to print something like:

You have $100.00 dollars!
Then your format would be:

”You have $$#####.## dollars_!"
!
DISPLAY changing variable type in a function
Check the reference manual for the type of values that
function expects. Then use the conversion routines
VAL and STR$ to convert an incorrect type to the
correct type, or use a command that matches the
type of variable you want.
!
DISPLAY string to number
If you have a number in the form of a string, and wish to
convert it to a number, then use the function VAL.
Here is an example:

10 INPUT"Enter a number":N$

20 NUMBER = VAL(Ns)

30 PRINT”Number ="; NUMBER
!
DISPLAY number to string
If you have a number, and wish to convert it to a
string, then use the function STR$. Here is an
example:

195

10 INPUT"Enter a number": NUMBER
20 NS = STR$(NUMBER)
30 PRINT"Number ="N$
!
DISPLAY CHARACTERISTICS OF THE LOGIC ERROR

CHARACTERISTICS OF A LOGIC ERROR

The program runs, but the results are not what
the programmer planned or the user expected.

DISPLAY CHARACTERISTICS OF THE LANGUAGE ERROR
CHARACTERISTICS OF THE LANGUAGE ERROR

The program does not run, and the computer prints out
some sort of error message.

I
DISPLAY end option to menu

A menu should always include an option to end the
program. This is usually the last item on the menu.
Choosing this option should cause the program to
branch to an end routine or a line number containing
the word end.

I
DISPLAY check for trip data

In a program that gets its data from input statements,
there must be a statement after the input statement
to determine if it is time for the program to stop.

This is done by comparing the input variable to some
predetermined value, called trip data, that signals
that the user is through entering data. A typical
example is:

100 INPUT"How old are you (enter 0 to end)";X

110 If X = 0 then END

If your program uses arrays, make sure your trip check
uses the same element of the array as the input. A
typical example is:

100 PRINT"Enter 0 to end"

110 PRINT"what is the cost of item"X;:INPUT C(X)

120 If C(X) = 0 then 200 :'processing begins at line 200

196

!
DISPLAY GO TO

Go TO statements that go to a line number smaller
than the line number of the Go TO statement may
set up an endless loop.

GO TO statements that go to a line number smaller
than the line number of the GO To statement should
go to a line number that:

1). Is an INPUT statement

2). Is a read statement

3). Is an EOF(#) statement

4). Is a Menu statement

5). GET # statement

If one of these is not the destination of the GO TO
statement, determine which of the above is the proper
destination for your GO TO statement and change the
line number to match that line number.

If you can not find the GO T0 line that is causing the
problem, type TRON (TRace ON) and then run your program.
Each time the computer runs a line of your program, the
line number will appear on the screen. Watch for repeating
patterns of line numbers. These will show you where your
program is looping. The GO TO that is causing the problem
will be one of those numbers (usually the largest).

Press CTRL BREAK to stop the program and change the GO TO
so it goes to one of the five possible destinations given
on the previous page. You will probably want to type
TROFF (TRace OFF) to turn off the appearance of the line
numbers. If the program still does not stop, repeat

the use of TRON to find the new loop and correct it.

!

DISPLAY add print lines to condition

If some of the detail output (prints each time you get

a new set of input data) does not print even though some
does, the most likely cause is that you have IF...THEN
statements for handling some of the input data in

different ways and that one or more of those routines

do not have the print (output) statements as part of

the routine. If you can not find the routine that is
missing the print (output) statements, type TRON (TRace

ON) and then run your program. Each time the computer runs
a line of your program, the line number will appear on the
screen. Watch for repeating patterns of line numbers that
include the input data lines but do not produce output.
These will show you where your program is looping without
printing the output. Add the print line to the loop before
it goes back to get more data. Type TROFF (TRace OFF)
before running the program again.

197

If the line numbers go by too fast to read, you may find
it useful to hold down the CTRL and SHIFT keys and press
the PRTSC key to print all the output to the screen to the
printer. This will make it easier for you to follow the
TRON line number output. Press the three keys again to
stop sending the output to the printer.

If your program uses arrays and is missing some of the
output, check to see if you are incrementing (adding a
value to) the loop parameter (the variable following the
FOR and the NEXT). ,This will cause the output to skip some
lines as the variable is incremented by both the program
code and the NEXT statement.

!

DISPLAY adding total print lines

After the trip data has been reached, the program should
print the total lines before it ends. The easiest way to
do this is to change the trip data check line so that
instead of ending it will go to a line number which is
higher than any of the other program lines and print

the total line before ending. For example

100 If X = 0 then 900

900 Print"the total XXXXXXX iS”TOTAL
910 END

!
DISPLAY add print lines

Locate the line that contains Go To the line that inputs

the data to be processed. Add a line before the GO T0 line
that prints the detail output (out put each time data is
input). If you can not find the GO T0 line, type TRON
(TRace ON) and then run your program. Each time the
computer runs a line of your program, the line number will
appear on the screen. Watch for repeating patterns of line
numbers that include the input data lines but do not produce
output. These will show you where your program is looping
without printing the output. Add the print line to the loop
before it goes back to get more data. Type TROFF

(TRace OFF) before running the program again.

1
DISPLAY move print lines

Locate the line that prints your output. Locate the line
that has the GO To the line that inputs the data to be

198

processed. Move the PRINT line to the line before the GO T0
line. Delete it from its old line number. If you can not
find the GO T0 line, type TRON (TRace ON) and then run
your program. Each time the computer runs a line of your
program, the line number will appear on the screen. Watch
for repeating patterns of line numbers that include the
input data lines but do not produce output. These will
show you where your program is looping without printing

the output. Move the print line to the loop before it goes
back to get more data. Type TROFF (TRace OFF) before
running the program again.

!

DISPLAY add a GO T0 line

After a program prints the output line, it must go back to
the get input data line to continue processing until all
the input data is processed. Locate the line that prints
the output and add a line following it that contains

GO To and the line number of the input line. This makes a
loop that allows the program to get the input and print
the output until all the input is processed.

!
DISPLAY Algorithms

Algorithms are rules or formulae used to determine values.
For example:

200 AREA = 3.1416 * RADIUS * 2
is the Algorithm for determining the area of a circle. If
your format (layout) of the output is correct, but the
numbers are wrong, the most likely cause is that one or
more of the algorithms are wrong.

When looking for incorrect algorithms, be certain that you
check for variable names that you have spelled wrong. For
example:

199 RADUS = DIAMETER/2

200 AREA = 3.1416 * RADIUS * 2
will give an AREA of zero since the RADUS and RADIUS are
different variables.

1
DISPLAY fornext

Before you attempt to determine the cause of the error,
list your program on paper. Draw a line from each

FOR statement to its Next statement. Use this listing
to answer the questions that follow.

199

 

 

 

 

——--100 FOR X = 1 TO 20 -——-100 FOR X = 1 TO 20

[:150 FOR Y = 3 TO 15 -150 FOR Y = 3 TO 15
200 NEXT Y 200 NEXT X
'——-235 NEXT X b—235 NEXT Y

!
DISPLAY proper nesting of FOR ... NEXTs

When a FOR ... Next loop occurs within another FOR ... NEXT
loop, you must be careful that the loops are nicely nested.
For example:

 

 

NICELY NESTED IMPROPER NESTING
'———100 FOR X = 1 TO 20 '———100 FOR X = 1 TO 20
[:150 FOR Y = 3 TO 15 r—150 FOR Y = 3 TO 15
200 NEXT Y 200 NEXT X
-——235 NEXT X “—235 NEXT Y

 

 

If the lines cross, as in the example of IMPROPER NESTING,
change the code so that they are NICELY NESTED.

!
DISPLAY match FOR ... NEXT variables

Every FOR variable name = start value TO end value

must have EXACTLY one NEXT variable name. There are two
common violations of this rule:

CHANGED VARIABLE NAME TWO NEXT STATEMENTS
100 FOR X = 1 TO 20 100 FOR X = 1 TO 20

 

 

150 IF Z=W THEN NEXT X

 

 

 

 

 

235 NEXT Z 235 NEXT X

If you have changed variable names, change code so the
FOR and NEXT both have the same variable name.

Although some versions of BASIC allow you to have TWO NEXT
statements, IBM version 2.0 -3.2 do not. Change your program
so the IF statement is THEN GO To 235 instead of NEXT X.

I

DISPLAY match FOR and NEXT statements

Every FOR variable name = start value To end value

must have EXACTLY one NEXT variable name. There are two
common violations of this rule:

200

 

 

 

CHANGED VARIABLE NAME TWO NEXT STATEMENTS
'———100 FOR X = 1 TO 20 -———100 FOR X = 1 TO 20
. 150 IF Z=W THEN NEXT X
'——-235 NEXT Z '———235 NEXT X

Although some versions of BASIC allow you to have TWO NEXT
statements, IBM version 2.0 -3.2 do not. Change your program
so the IF statement is THEN Go To 235 instead of NEXT X.

If you have changed variable names, change code so the

FOR and NEXT both have the same variable name.

!

DISPLAY removing branch to inside loop

You must not have a Go T0 line outside of the FOR .. NEXT
loop in your program that GOes TO a line inside a

FOR ... NEXT loop. The Go To must go to the FOR statement
in a loop or not Go To a loop at all.

PROPER GO TO A FOR NEXT IMPROPER GO TO A FOR NEXT
100 FOR x = 1 T0 20 100 FOR x = 1 T0 20

. 120
235 NEXT X I35 NEXT x

 

 

 

*---400 GO TO 100 400 GO TO 100

If you are not certain if there is a GO To a line number
inside the loop, type TRON (TRace ON) and run your program.
The line numbers print on the screen as the program runs
and you can see if there is a line number outside the loop
before the error occurs. Change the GO TO and type TROFF.
!

DISPLAY clearing FOR..NEXT variable-

Sometimes if you have a very long program, even when you
have not changed variable names, have not used improper
nesting, or do not have two NEXT statements, you may still
get either a FOR without NEXT or Next without FOR error.
This can occur when you exit from one FOR ... NEXT loop
without clearing the variable and move into a new loop.
Eventually, the computer runs out of storage places to
indicate where to return. To correct this, Change as shown

ORIGINAL CODE CHANGED CODE
100 FOR X = 1 TO 20 100 FOR X = 1 TO 20

 

150 IF Z = W THEN 310 150 IF Z=W THEN X=21: GO TO 235

 

-—-235 NEXT X 235 NEXT X
250 IF X > 21 THEN 310
310 0...... 310 ......

201

!
DISPLAY RETURN without GOSUB

The program has reached a RETURN statement without

first executing (reaching) a GOSUB. The usual cause of
this error is not having an END to your program. Add

an END statement before the first line of the subroutine.

If the error is not corrected by adding an END statement,
type TRON (TRace ON) to display the lines of codes as they
are run. When the error appears on the screen, the line
numbers of the code run before the error will also appear.
ADD either a GO TO to branch back to the input of data
statement or an END among the lines of code run before the
lines of code that make up the subroutine. Type TROFF
(TRace OFF) to restore the program to normal run mode.

!
DISPLAY out of data

This problem is normally caused by one of six possible

error conditions:

1). forgetting to put a check for the Trip Data after
the READ statement

2). forgetting to add the trip data after all the normal
data to be processed in the DATA statements

3). not having the Trip Data in the data statement match
the check following the read

4). Not having the variable in the check after the READ
match the variable in the READ statement

5). Reading into more than one variable at a time, and
having nothing after the trip data to fill the other
variables being read in

6). Having an error in the DATA causing it to no longer
match the READ variables

Check each of these six and correct any that cause a
problem.

!

DISPLAY correct Out of Data

When using the READ....DATA statements, your program should
resemble this code. Correct your code to follow this
example:

100 READ X$,Y,Z$
110 IF X$ = ”END" THEN END

1000 DATA Joe,34,Doctor,BILL,45,Lawyer,SUE,12,student
1010 DATA Frank,39,teacher,Paul,54,teacher aid
1020 DATA END,-99,END

202

Note that the out of data error would occur if 1020 were
1020 DATA end,-99,END since END does not equal end

!

DISPLAY matching the DATA with the READ variables

You need to first find out how far the DATA matches
correctly with the READ. Add some PRINT statements
after the READ, then run the program and see at what
point incorrect values for DATA start coming up. You
can then check the data around the area where the program
started reading the incorrect data. Here are some
things to look for when checking your DATA:

* Two commas next to each other
* A comma starting or ending a line
* A ":" or a ",” as part of a data element you want to
read (If you wish to read a : or , then enclose that
data element in "quotes."
v

DISPLAY advanced feature

You have chosen an advanced feature such as PAINT or LINE
or CIRCLE or COLOR or some other KEY word or expression
that can only be used with advanced BASIC. SAVE your
program. Type SYSTEM and press enter. You will now be
back at the DOS level. Type BASICA (BASIC with Advanced
features) and press enter. LOAD your program and run it
again. You will not get an Advanced feature error if you
are using BASICA.

!

DISPLAY can't continue

You have typed CONT and the program can not start up again
from wherever it had stopped. On IBM basic, you can not
press the break key when you are LISTing your program and
start it up again by typing CONT. If you want to stop a
LIST, hold down the CTRL key and press NUM LOCK. Start up
again by pressing ENTER.

If you have pressed CTRL Break to look at your program, you
must not type a line number or EDIT. If you do, you will
not be able to start your program up again by typing CONT.
If you try, you will get a can't continue error.

To correct a can't continue error, just RUN your program
again from the start (type RUN and press enter).

!

DISPLAY undefined line number

You have a branching statement (Go T0 or GOSUB) that tells
the program to branch (Go TO) a line number, but the line
number to which it is supposed to go does not exist!!.

203

List your program and find the correct line number. If you
are certain you typed in the line to which the program
should branch, but it is not there, you should not only
type in the line, but you should also check to see if you
accidently typed in the wrong line number when you entered
the line. Common typing errors for line numbers include
typing a 0 for a 9 (or a 9 for a 0): dropping a repeated
digit (4000 instead of 40000): and reversing digits (typing
a 1223 instead of 1232). If you have typed the line number
incorrectly, be certain to remove the incorrect line and
retype any lines it may have replaced before you try to run
your program again.

!

DISPLAY subscript out of range

A subscript out of range error can be caused many different
things. One cause would be misspelling a function such a
LOG(), thus causing the computer to think that you are
using a subscripted variable when you wished to use the
function. Select the option for a typing error if this is
what happened.

Some functions, such as TAB require that there is no space
between the function name and the "(". A common error is
to include a space after the word TAB. If this is what
happened, then select the option for a typing error.

Without using a dimension (DIM) statement, you imply to
computer a DIM variable(10). This will allow you to use
any integral value from 0-10 as the subscript, unless if
you have "OPTION BASE 1” in your program, which will set
the lowest allowable subscript at 1.

!

DISPLAY typing errors on subscripts

Double check that the variables in the dimension statement
are spelled the same, and have the same number of sub-
scripts within the (...). If an array was defined as:

10 DIM A(20,20)

You would not be able to access A(X), but you could access
A(X,Y). If one of the variables is spelled differently,
or has a different number of subscripts, then does not
match.

!

DISPLAY adding a dimension statement

If you are using an array, you should include a dimension
(DIM) command. The dimension is optional if it is a single
subscripted array and will not exceed 10, but it is good
programming practice to include one even if the array will
not exceed 10.

204

When determining the size to use, for an array which you do
not know the maximum subscript needed, it can be set up to
be easy to change as follows:

10 LN=20:OPTION BASE l

20 DIM FIRST$(LN),LAST$(LN)
100 N=O:PRINT"Type x,x when finished."

110 N=N+1 : INPUT"Lastname, First":LAST$(N),FIRST$(N)

120 IF LAST$(N)=”X” AND FIRST$(N)-"X” THEN N=N-l:GOTO 200
130 IF N=LN THEN PRINT"Sorry, no more room.":GOTO 200
140 GOTO 110
200 ...

The size of the array is determined in the first line. If
you decide to change the size of the array, you need only
change the value of LN in line 10.

OPTION BASE 1 is optional, and it's only advantage is that it
saves memory by not allowing you access to element 0 in an
array. If you have double or triple subscripted arrays,
this can save a large amount of memory.

!

DISPLAY picking the value for a dimension statement

You need to either increase the value in the dimension
statement for the variable that caused the error, or change
your program to keep from going outside the range of the
dimension statement. Take the following program as an
example:

20 DIM FIRST$(20),LAST$(20)

100 N=0:PRINT"Type X,X when finished.”

110 N=N+l : INPUT"Lastname, First":LAST$(N),FIRST$(N)

120 IF LAST$(N)="X” AND FIRST$(N)="X” THEN N=N-1:GOTO 200
140 GOTO 110

200 ...

With the above program, if the person tries to enter in 21
names, the computer will respond with a subscript out of
range error. However, by adding two lines and changing a
third, we will eliminate this problem, as follows:

10 LN=20=OPTION BASE l
20 DIM FIRST$(LN),LAST$(LN)
100 N=0:PRINT"Type X,X when finished.”
110 N=N+1 : INPUT"Lastname, First":LAST$(N),FIRST$(N)
120 IF LAST$(N)="X" AND FIRST$(N)=”X” THEN N=N-l:GOTO 200
130 IF N=LN THEN PRINT"Sorry, no more room.”:GOTO 200
140 GOTO 110
200 ...

205

OPTION BASE 1 is optional, and simply helps to save memory
by telling the computer we will not be accessing FIRST$(0),
or LAST$(0). The change in line 20 is made so that if the
array size ever needs to be changed, it can be changed
easily, simply by changing the value of LN in line 10.

Line 130 will stop the person from entering too many names,
thus keeping N from going outside the bounds of the array.

It is also possible that the error may have been caused by
some type of logic error. If so, make use of TRON/TROFF
and PRINT statements to find out what is causing it to go
outside the limit.

!

DISPLAY subscript out of range by logic error
If your program is trying to access an array element that
it should not access to figure out why, here are a few simple
steps that you can take to help find the cause of the error.
1. Place a PRINT before each access of the subscript, and
print the subscript value, and the contents of the
array element if it will help.
2. Place a PRINT after each calculation that is used in
calculating the subscript value. This can be useful
if you are using some sort of hashing technique, and
have an error in your hashing formula.
3. If your program goes through many lines while
calculating the value for the subscript, then use
TRON and TROFF to turn on and off listing the
lines it is accessing.
!
DISPLAY moving the dimension statement
If your array is shrinking in size, then you probably
need to move it. Some commands must be given in a certain
order. A CLEAR command will clear out all variables,
including any definitions for an array. There are other
commands that may cause this to happen such as improper
use of the COMMON and CHAIN commands or RUN your program from
a line other than the start. Also, make sure that you are not
using ERASE to delete the array.

If you have a CLEAR statement in your program, make it the
first thing to be executed.

!

DISPLAY division by zero

A division by zero error will not stop execution of a pro-
gram in IBM basic. It is there as a warning which the
computer displays if you attempt to divide by zero, or
raise 0 to a negative exponent. A division by be zero will
cause that portion of the expression to be evaluated as
machine infinity (+/-).

206

You might want to make sure that there isn't a CLEAR, or
other command wiping out the contents of a variable causing
you to try and divide by zero. You can also put in a check
as in the following program:

10 PRINT"When finished enter -99"

20 INPUT"Number”;NUMBER

30 IF NUMBER = -99 THEN 100

40 TOTAL = TOTAL + NUMBER

50 COUNT = COUNT + 1

60 GOTO 20

100 IF COUNT = 0 THEN PRINT"You did not enter any numbers

to average." : GOTO 120

110 PRINT"The average of the numbers is: ”: TOTAL / COUNT

120 END
1
DISPLAY duplicate definition
You have tried to redefine the size of an array. There are
a number of different possible causes, which include:

* The same array is defined in two DIM statements (or
the same DIM statement is executed twice.)

* The program encounters a DIM statement for an array
after the default dimension of 10 is established for
that array.

* The program sees an OPTION BASE statement after an
array has been dimensioned, either by a DIM statement
or by default.

!

DISPLAY how to find array being defined twice

The first thing that I recommend you do is to examine your
program and see if you are directly defining the array
twice. One way to do this is to save your program in ascii
(EXAMPLE: SAVE"PROGRAM”,A) and load it into a text editor.
You can then use global search commands and look for the key
word DIM. All DIM statements should be near the top of the
program (after a CLEAR statement if you have one.) If you
are defining the size of an array for many variables, you
might have accidently typed in the same variable twice,
even on the same line.

!

DISPLAY other than removing a definition

If you really want to define the array twice (Perhaps to
increase the size of the array) you can use the ERASE
command to clear out one or more arrays. Remember that,

if you do this, the previous contents of the array will be
lost (unless you save the array somewhere else.)

!

DISPLAY moving the OPTION BASE command

Move the OPTION BASE command to the beginning of your
program. It must be in front of any DIM statements, or

207

commands that will use arrays. A clear statement will
reset it back to the default of OPTION BASE 0.

1

DISPLAY the two other causes of duplicate definition

There are two other common causes of a duplicate definition
error. One is initializing the array to something before
the DIM statement as in the following example:

10 A$(1)="RED”:AS(2)8”BLUE”:A$(3)="GREEN”
20 DIM A$(3)

After the computer encounters A$(l)="RED" it notices that

it is a new array, and will assign it a default dimension
size of 10, and when it reaches line 20 the computer

already has it set up for size 10. To solve this sort of
problem, move the dimension statement to the beginning of the
program.

The other common error is shown in the example below:

10 DIM xs(50)
20 CLS

1000 INPUT"Do you wish to run this again?”:Q$
1010 IF LEFT$(Q$,1)="Y" or LEFT$(Q$,1)="y” THEN 10

If the person decided to redo the program, the computer
will encounter the same dimension statement twice. There
are a couple of ways that this can be fixed. You only
need change either line 10, or line 1010 in this case. You
could change line 10 to:

10 CLEAR : DIM xs(50)
or change line 1010 to:
1010 IF LEFT$(Q$,1)="Y" or LEFT$(Q$,1)="y" THEN RUN
or change line 1010 so it jumps to a point after the DIM.

1010 IF LEFT$(Q$,1)="Y" or LEFT$(Q$,1)="y” THEN 20
!
DISPLAY missing operand
You have an expression in your program that is missing an
operand. Having a * (multiply) or the OR operator with
nothing after it, are common causes for this error. Also
some commands like LOCATE and POKE will give this error if
you do not supply all of the operands.

To fix this error, add the missing operand(s) or fix some
sort of typing error that may have caused it. You may need
to look up the command or operator in the reference

208

manual. They will have the format of the command and all
required operands for that command.
I

DISPLAY whilewend
To attempt to determine the cause of the error,
list your program on paper. Draw a line from each

WHILE statement to the nearest WEND, starting with
the WHILE and WEND that are closest to each other.

'———100 WHILE X <= 20

[:150 WHILE Y = 1 AND Z < 10

200 WEND

 

'—-—235 WEND

1

DISPLAY match WHILE and WEND statements

Every WHILE expression must have EXACTLY one WEND
statement. There are three common causes of this error:

MISSING WEND MISSING WHILE TWO WEND STATEMENTS
100 WHILE X = 1 100 100 WHILE X <= 10
. . [—150 IF Z=W THEN WEND

 

235 235 WEND L—235 WEND

If you have left out either a WHILE or a WEND,
rewrite the code so that each WHILE matches a WEND.

If you have two WEND statements, change your program
so the IF statement is THEN GO TO 235 instead of WEND.
I
DISPLAY removing branch to between WHILE and WEND
You must not have a GO T0 line outside of the WHILE...WEND
loop in your program that GOes TO a line inside a WHILE ..
.. WEND loop. The GO TO must go to the WHILE statement
in a loop or not GO TO a loop at all.
PROPER GO TO A WHILE....WEND IMPROPER GO TO WHILE..WEND

 

 

 

100 WHILE X = l [-100 WHILE X = 1
: 120.
235 .WEND l"135 WEND
'——-400 GO TO 100 ‘———400 GO TO 120

If you are not certain if there is a GO TO a line number
inside the loop, type TRON (TRace ON) and run your program.

209

The line numbers print on the screen as the program runs
and you can see if there is a line number outside the loop
before the error occurs. Change the GO TO and type TROFF.
!

DISPLAY illegal function

List the line in which the illegal function Call occurred.

If the line has a PRINT USING statement, print the image.
For Example: 100 PRINT USING Is: X, Y, 2

type ? Is and press enter. If you get a blank line and OK,
15 is not defined! Either add a line defining I$ or move
the existing line so that it is ALWAYS executed before the
PRINT USING statement.

If there is no PRINT USING image or if it is defined, print
any other functions (see pages 4-17 thru 4-22 in the IBM
BASIC manual) until you find the one that is causing the
illegal function Call. If the argument [inside the ()1, is
a variable, print that also. For example:

100 Y = SQR(X)
? SQR(X)
ILLEGAL FUNCTION CALL
? X
-27
!
DISPLAY PRINT USING image

Print the image from the PRINT USING image.
For Example: 110 PRINT USING IS; X, Y, Z
type ? Is “and press enter.

OK

If you get a blank line and OK,
Is is not defined! Either add a line defining IS
109 Is = "##.## ### ###.###"

or move the existing line so that it is ALWAYS executed
before the PRINT USING statement. Make

200 IS = "##.## ### ###.###”

! 5 IS = "##.## ### ###.###"

DISPLAY value string

Print the variable in the string function. For example:
If 100 X$ = RIGHT$(C$,1) then run the program. When
ILLEGAL FUNCTION occurs, print the variable

? C$

OK

210

Change the code so that C5 (or the variable from your
program) has a value before line 100. If there is a chance
that CS (or the variable from your program) might have no
value (might be the null set), make the line

100 IF C$ = "" THEN X$ = "” ELSE X$ = RIGHT$(C$,1)
I

DISPLAY length string

Print the variable in the string function. For example:
If 100 X$ = MID$(C$,S,1) then run the program. When
ILLEGAL FUNCTION occurs, print the variable

? S'Cs

If S<=0 or CS is less than S characters long, you would not
be able to find the middle starting with the Sth character!
Either the value of CS (or your program's variable) is not
being assigned correctly, or the starting position is

not being assigned correctly. Change your code so that
both of these values are properly assigned. If you are
assigning them properly but some of the test data is in
error, change the code to test for valid values:

100 IF S<=0 or LEN(C$)<S then X$="" ELSE X$=MID$(C$,S,1)
n
DISPLAY argument
Print any functions (see pages 4-17 thru 4-22 in the IBM
BASIC manual for a list of possible functions) until you
find the one that is causing the illegal function Call.
If the argument [inside the ()1, is a variable, print that
also. For example:

100 Y = SQR(X)
? SQR(X)
ILLEGAL FUNCTION CALL
? X
-27
If seeing the value of the variable does not show you what
the problem is, look up the function in the BASIC manual
and compare the value of the variable in your program with
the values that are allowed for the argument. Change the
code so that values are being assigned correctly. If some
of the test data is in error, change the code to test for
valid values:

100 If x < 0 then Y = o ELSE Y = SQR(X)

211

DISPLAY negative subscript

If there are no functions (see pages 4-17 thru 4-22 in the
IBM BASIC manual for a list of possible functions), print
any subscripted variables until you find the one that is
causing the illegal function Call. If the subscript [inside
the ()], is a variable, print that also. For example:

100 Y = SUM(X)
? SUM(X)
ILLEGAL FUNCTION CALL
? X
-27
Since you can not have a negative value of a subscript,
change the code so that values assigned to the subscript
are not negative. If some of the test data is in error,
change the code to test for valid values:

100 If x < 0 then Y = o ELSE Y = SUM(X)
!
DISPLAY negative power
If there are no functions (see pages 4-17 thru 4-22 in the
IBM BASIC manual for a list of possible functions) and no
arrays, print any variables raised to a power until you find
the one that is causing the illegal function Call. Print
both the variable and the power:

100 Y = X‘Z
? X‘Z
ILLEGAL FUNCTION CALL
? X
-27
OK
? z
1.34
OK
Since you can not have a negative value raised to a non
integer power, change the code so that values assigned to
the variable are not negative or the power is an integer.
If some of the test data is in error, change the code to
test for valid values:

100 If X < 0 then Y = X‘INT(Z) ELSE Y = X‘Z
!
DISPLAY delete line

List the lines that you are attempting to delete.
If any of them do not list, the lines do not exist.
You can not delete a nonexistent line!

Retype your delete command so that you are using
lines that exist.

212
DISPLAY get/put

Print the variable indicating the record number.
For example:
100 GET #1, RECORD.NUMBER
? RECORD.NUMBER
-8
OK
Since you can not have a negative value for a record
number, change the code so that values assigned to the
record number are not negative. If some of the test data
is in error, change the code to test for valid values:
100 If RECORD.NUMBER < 1 then PRINT"Record number
incorrect":PRINT"Correct data and rerun the program": END
ELSE GET #1, RECORD.NUMBER
!
DISPLAY device error

A device error occurs when the BASIC program attempts
to communicate with one of the hardware devices such as
the printer, disk drive, modem, or cassette recorder.

The most common error is that the printer is not turned
on or that the select button needs to be pressed for the
printer to be ready, although the problem could be that
the printer cable is bad.

After trying to communicate with a device for a preset
number of seconds, BASIC will issue a DEVICE TIMEOUT
error.

If BASIC can tell that there is something wrong with
the hardware, it will issue a DEVICE FAULT ERROR.

!

DISPLAY out of paper

An out of paper error occurs when the BASIC program
attempts to communicate with the printer and fails to
complete the task.

The most common error is that the printer has run out of
paper, but this error can also occur if the printer is not
turned on or that the select button needs to be pressed for
the printer to be ready, although the problem could be that
the printer cable is bad.

Look at the printer and see if the paper light is on.

If so, put paper in the printer or if it has paper, check
to be certain that the paper opens the paper sensor switch.
You may need to move the paper to keep the sensor open.

!

213
EXPAND The error belongs to Logic errors

Before you can determine what is causing an error, you must
determine the type of error that has happened. Errors in
logic occur when the program runs, but the results are not
what you expected. Language errors occur when the code
does not follow the rules for basic code. Language errors
cause the compiler to print out a message to help you
determine the source of the error.

I
EXPAND The error belongs to language errors

Before you can determine what is causing an error, you must
determine the type of error that has happened. Errors in
logic occur when the program runs, but the results are not
what you expected. Language errors occur when the code
does not follow the rules for basic code. Language errors
cause the compiler to print out a message to help you
determine the source of the error.

!
EXPAND there is only one line of detail output

Detail output is the type of output where one line is
output for each set of data input. For example:

100 READ A,B,C
110 IF A=0 THEN END
120 D=A+E/c

130 PRINT A,B,C,D
14o GOTO 100

Line 130 is detail output since it prints each time
A,B, and C are read.

!
EXPAND correct error by reassigning algorithms

Algorithms are rules or formulae used to determine values.
For example:

200 AREA = 3.1416 * RADIUS ‘ 2
is the Algorithm for determining the area of a circle. If
your format (layout) of the output is correct, but the
numbers are wrong, the most likely cause is that one or
more of the algorithms are wrong.

When looking for incorrect algorithms, be certain that you
check for variable names that you have spelled wrong. For
example:

199 RADUS = DIAMETER/2

200 AREA = 3.1416 * RADIUS ‘ 2

214

will give an AREA of zero since the RADUS and RADIUS are
different variables.

!

EXPAND after the INPUT does not check for trip data

Trip data is special data (like -99 or END OF FILE or
sometimes even 0) that could not be ”true" data for a
program. It is used to signal the program that processing
is finished. A program that uses either a READ statement
or INPUT to get the data to process usually has a check
for some special data (trip data) in the line following
the READ or INPUT lines.

!

EXPAND correct error by checking for trip data input

Trip data is special data (like -99 or END OF FILE or
sometimes even 0) that could not be "true" data for a
program. It is used to signal the program that processing
is finished. A program that uses either a READ statement
or INPUT to get the data to process usually has a check
for some special data (trip data) in the line following
the READ or INPUT lines.

EXPAND the program checks for trip data

Trip data is special data (like -99 or END OF FILE or
sometimes even 0) that could not be ”true" data for a
program. It is used to signal the program that processing
is finished. A program that uses either a READ statement
or INPUT to get the data to process usually has a check
for some special data (trip data) in the line following
the READ or INPUT lines.

!

EXPAND the value of subscript in error

Look at the line on which the error occurred. Find which
variable gave the error. If there is more than one
subscripted variable on the line, then use PRINT until
you find which one gives the error. Example:

100 A(X)=B(Z) * C(Y*2)

You could then do, PRINT A(X), and if it returns a value,
that is not the one causing the error. Let's say that
you found C(Y*2) to be the one in error, you would then
”PRINT Y*2", and enter in the value given by the computer.

215

EXPAND value in the dimension statement

Find the dimension statement that defines the array that
is giving the error. If there is a variable in the
subscript, be sure to give the value of the subscript, and
not the contents of the subscript. Example:

10 LN=100 : DIM A(LN), B(LN), C(LN*2)

And C(...) was found to be causing the problem. You would
then respond with 200 for this question.

!

END

APPENDIX D

APPENDIX D

Checklist for Data Flow Diagrams in Instructional Design

I. Have the course goals been identified?
II. Have course goals been separated into nine or less
logical subgroups called course components?
A. Have the components been verified by a subject
matter expert?
B. Have interrelationships between the components
been identified and verified?
C. Has a DFD been made of the course components
and their interrelationships?

1. Have information and processes between
components been explained to the level
required for development and
implementation?

2. Has the correctness of the data flow
diagram been verified by
a). a subject content area expert?

b). an expert content area teacher?
c). a potential instructor?
III. Have the goals of each component been determined?
IV. Have the component goals been separated into
logical groupings called units?
A. Have the units been verified by a subject
matter expert?
B. Have interrelationships between the units been
identified and verified?
C. Has a data flow diagram been made of the units
and their interrelationships?

1. Have information and processes between
units been explained to the level required
for implementation?

2. have necessary knowledge, strategies, and
reference materials been shown and
explained?

3. have points where expert help may be
necessary been identified?

4. Has the correctness of the data flow
diagram been verified by
a). a subject content area expert?

b). an expert content area teacher?
c). a potential instructor?
V. Have the goals of each unit been identified?
A. Have the goals been verified by a subject
matter expert?
B. Have interrelationships between the goals been
identified and verified?

216

VI.

VII.

217

Has a data flow diagram been made of the

goals and their interrelationships?

1. Have information and processes between
goals been explained to the level required
for implementation?

2. have necessary knowledge, strategies, and
reference materials been shown

3. have points where expert help may be
necessary been identified?

4. Has the correctness of the data flow
diagram been verified by
a). a subject content area expert?

b). an expert content area teacher?
c). a potential instructor?

Have the enabling objectives been identified?

A.

B.

C.

Have the enabling objectives been verified by

a subject matter expert?

Have interrelationships between the enabling

objectives been identified and verified?

Has a data flow diagram been made of the

enabling objectives and their

interrelationships?

1. Have information and processes between
enabling objectives been explained to the
level required for implementation?

2. have necessary knowledge, strategies, and
reference materials been shown and
explained?

3. have points where expert help may be
necessary been identified?

4. Has the correctness of the data flow
diagram been verified by
a). a subject content area expert?

b). an expert content area teacher?
c). a potential instructor?

Have the tasks involved in reaching the objectives
been identified?

A.

Components?
1. Starting and ending points?
2. processes?
a). information needed?
b). interrelationship between processes?
c). points were expert help is needed?
Have the tasks and components been verified by
a subject matter expert?
Have interrelationships between the components
been identified and verified?
Has a data flow diagram been made of the tasks
and components their interrelationships?
1. Have information and processes between
tasks and components been explained to the
level required for implementation?

218

2. have necessary knowledge, strategies, and
reference materials been shown?

3. have points where expert help may be
necessary been identified?

4. Has the correctness of the data flow
diagram been verified by
a). a subject content area expert?
b). an expert content area teacher?
c). a potential instructor?

VIII. Does the developer or instructor feel confident
that the lessons can be developed (using Gagne's
(1985) elements of instruction, Reigeluth's (1982)
Elaboration Theory, or Landa's (1982) Snowball
approach)?

APPENDIX E

APPENDIX E

PAIN AND ITS TREATMENT IN VETERINARY MEDICINE:
AN INTERACTIVE VIDEO COURSE

This appendix contains part of the design of an interactive
video course using data flow diagrams.

Data flow diagrams for Pain 1.0 . . . . . . Page 220
Instructional Dictionary for Pain 1.0 . . . Page 226

219

220

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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1.1 1.2 1.3 1.4
*r-——-4
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1.1.1 1.1.2 1.1.3
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1.1.4.1 1.1.4.2 1.1.4.3 1.1.4.4 1.1.4.5
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Figure 26: SPECIFIC RESPONSES TO PAIN 1.1.4

223

 

 

1.2.1 1.2.2 1.2.3 1.2.4
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Figure 27: TYPES OF PAIN CONTROL 1.2

224

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Figure 28: OPIATES AND OPIATE RECEPTORS 1.3

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Figure 29: . AGONIST/ANTAGONIST AND NARCOTIC DRUGS 1.4

INSTRUCTIONAL DICTIONARY
for
Methods of Controling Pain in Veterinary Medicine

Section I: Pain

(num)(level)(sequence)

Part A: 1.1.1 (Pain and the veterinarian's concern about pain)

( 1)

( 2)

( 1)

( 2)

( 1)

( 2)

Part

( 3)

(10)

(42) (1)

(22) (2)

(42) (3)

(42) (4)

(42) (5)

(33) (6)

3: 1.1.2

(33) (1)

(22) (2)
(32) (3)

(32) (4)

(32) (5)

(33) (6)
(33) (7)

(32) (8)

(22) (9)

Pain is a complex physiological phenomenon that is (
difficult to identify and interpret in animals.

No single area of the brain is specifically responsible (
for the perception of pain.

Veterinarians should alleviate pain and suffering in (
animals.

Veterinarians should suspect the presence of pain in (
animals if under the same circumstances humans
experience pain.

The judicious use of drugs for relief of pain can (
significantly reduce animal suffering.

Pain relievers should be selected for animals if (
(a) the animal can, in fact, be made more comfortable.
(b) the pain-relieving drugs will not be detrimental.

(Pain receptors and response levels)

The modifier, PAIN, should not be applied to these (
neurological components because the PERCEPTION of pain
does not necessarily occur with:

(a) stimuli

(b) impulses

(c) pathways

(d) reflexes

Noxious describes stimuli which give rise to pain. (

A receptor is that portion of a nerve which responds to (
a stimulus and causes the transmission of an impulse to
the brain.

Nociceptors are receptors Specifically responsive to (
noxious stimuli.

Nocipceptive threshold is the intensity of stimulation (
of a nociceptor needed to generate nerve impulses.

The pain detection threshold is the strength achieved by(
a noxious stimulus to cause the perception of pain.

The pain tolerance threshold is the highest intensity of(
noxious stimuli a human subject will permit an
experimenter to deliver.

The strength of a noxious stimulus necessary to reach (
the nociceptive threshold varies little among humans
and animals.

The strength of a noxious stimulus needed to cross the (
pain detection threshold is variable.

226

2

2

(reference) type

)2

)2

)1

)1

)3

)3

)3

)2

)2

)2

)2

)2

)2

)2

)2

( 2)

( 4)

( 5)

( 3)

( 3)

Part

( 4)

( 6)

( 5)

( 7)

( 8)

(11)

( 6)

(33) (10)

(32) (11)

(21) (12)

(33) (13)

(32) (14)

(42) (15)

C: 1.1.3

(32) (1)

(41) (2)

(41) (3)

(31) (4)

(31) (5)

(31) (6)

(43 (7)

227

If individuals have experienced pain previously and ( 2
repeatedly, the strength of a noxious stimulus necessary

to cross the pain detection threshold is probably higher

than for individuals who have not experienced pain.

If pain is dull, it is more easily tolerated than ( 2
sharp pain.
A variety of different stimuli evoke pain: ( 2

(a) superficial (skin)
(b) mechanical (pressure)

(c) thermal (heat)

(d) chemical (burns)

(e) visceral (gut).

There are many different types of pain ( 2

(a) the perceptual experience can change dramatically
with variation of the intensity of the stimulation

(b) A needle puncture is not as painful as a skin
incision.

If animals are stimulated at about the same intensity ( 2a
that human subjects first report the detection of pain,
they will begin to escape stimulation.

Veterinarians should not ignore the perception of pain ( 2a
in animals.

(Animal Response to Pain)

If an animal exhibits behavioral changes, the animal may( 3
be experiencing pain.

Behavioral changes indicative of pain range from ( 3
vigorous activity to relative lethargy.

(a) moaning, groaning, crying, mimering, bellowing

(b) looking at a specific area

(c) licking, biting

(d) decrease in physical activity

(e) poor appetite

If acute or sharp pain is identified by palpitation of ( 3
an affected area, the animal may attempt to escape or
attack.

Clinical signs of the presence of pain: ( 3
(a) lameness

(b) shallow breathing

(c) moaning, crying

Signs of localized pain: ( 3
(a) Belly: tense abdominal muscles
(b) Chest: shallow breathing or elbows away from the

body in a distressed manner.

Muscle guarding is tense abdominal muscles due to belly ( 3
pain.

If an animal has experienced pain for many days, the ( 3
animal may tolerate the painful experience and become

quiet or withdrawn with no overt behavioral evidence of
suffering.

)4

)4

)3

)3

)4

)1

)4

)3

)4

)3

)3

)2

)4

228

Part 0: 1.1.4 (Specific responses to pain)

( 9) (42) (1a) There can be a great deal of interspecies and ( 4 )3
individual variability in response to pain.
(a) Hounds seem less likely than poodles to be
sensitive to pain.
(b) Cats may only show visible signs of pain when the
stress becomes more pronounced.
(c) Grinding of teeth and head pressing are probable
signs of pain in runinants.
(d) Profuse sweating may indicate severe pain in a
horse.

(10) (22) (1b) The presence of pain can be inferred from the observing (t1,4 )3
changes in the animal's:
(a) posture
(b) vocalizing
(c) temperament
(d) respiration
(e) other miscellaneous behaviors

(11) (41) (2a) General signs of behavior indicating pain or discomfort (t1,4 )3
in the dog’s posture:
(a) anxious expression;
(b) tail between legs
(c) “hang dog" look
(d) shifts in position
(e) not comfortable

(12) (42) (2b) General signs of behavior indicating pain or discomfort (t1,4 )3
in the dog's Vocalizing:
(a) Howls
(b) Distinctive bark
(c) Noans
(d) Groans

(13) (32) (2c) General signs of behavior indicating pain or discomfort (t1,4 )3
in the dog's Temperament:
(a) Aggression
(b) Cringing
(c) Submissive
(d) Escapes
(e) Licks or bites area

(14) (32) (2d) General signs of behavior indicating pain or discomfort (t1,4 )3
in the dog's Respiration:
(a) Abnormal breathing pattern:
(b) rate and depth altered,
(c) panting, labored

(15) (42) (2e) General miscellaneous signs of behavior indicating pain (t1,4 )3
or discomfort in the dog:
(a) penile protrusion
(b) Frequent urination
(c) Shivering

(16) (42) (3a) General signs of behavior indicating pain or discomfort (t1,4 )3
in the cat's posture:
(a) Tucked in paws
(b) hunched head and neck
(c) Shifts position
(d) Tucked up abdomen
(e) not comfortable

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(32)

(32)

(32)

(32)

(42)

(32)

(42)

(32)

(32)

(42)

(42)

(42)

(3b)

(3c)

(3d)

(3e)

(4a)

(4b)

(4c)

(4d)

(4e)

(5a)

(5b)

(5c)

229

General signs of behavior indicating pain or discomfort
in the cat's Vocalizing:

(a) Distinctive cry

(b) Missing

(c) Spitting

General signs of behavior indicating pain or discomfort
in the cat's temperament:

(a) Ears flattened

(b) Fear of being handled

(c) May cringe

General signs of behavior indicating pain or discomfort
in the cat’s Respiration:

(a) Abnormal breathing pattern:

(b) panting, breathe heavy

General Miscellaneous signs of behavior indicating pain
or discomfort in the cat:

(a) Unsteady gait

(b) limps

(c) Shivering

General signs of behavior indicating pain or discomfort
in the cow's Posture:

(a) Head down - ears limp

(b) Tucked up abdomen

(c) Mead pressing

General signs of behavior indicating pain or discomfort
in the cow's Vocalizing:
(a) Grinding teeth

General signs of behavior indicating pain or discomfort
in the cow's Temperament:

(a) Withdrawn

(b) Depressed

(c) Not active

General signs of behavior indicating pain or discomfort
in the cow's Respiration:

(a) Grunting

(b) Dyspnea

General Miscellaneous signs of behavior indicating pain
or discomfort in the cow:
(a) limp

General signs of behavior indicating pain or discomfort
in the Horse's Posture:

(a) Rolls

(b) Stretches

(c) Looks at area

(d) Kick at area

General signs of behavior indicating pain or discomfort
in the horse's Vocalizing:
(a) Grinding teeth

General signs of behavior indicating pain or discomfort
in the horse's Temperament:

(I) Depressed

(b) Aggressive

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

(t1,4

)3

)3

)3

)3

)3

)3

)3

)3

)3

)3

(29)

(30)

(12)

(31)

(13)

(14)

( 7)

Part

(32)

(15)
(16)

(33)

Part

(34)

(17)

(18)

(19)

(42) (5d)

(32) (5e)

(22) (6a)

(43) (6b)

(22) (6c)

(42) (6d)

(42) (6e)

E: 1.2.1

(43) (1)

(42) (2)
(42) (3)

(42) (4)

F: 1.2.2

(42) (1)

(31) (2)

(32) (3)

(32) (4)

230

General signs of behavior indicating pain or discomfort (t1,4

in the horse's Respiration:
(a) Grunting
(b) Labored breathing

General miscellaneous signs of behavior indicating pain (t1,4

or discomfort in the horse:
(a) limp
(b) Sweat

Even though there is a great deal of interspecies and
individual variability in response to pain, there are
some broad generalizations that can be made about pain
that apply to many species.

Intense emotional reactions by a patient can be
produced by

(a) Levels of pain

(b) above the tolerance threshold.

High levels of pain in animals can usually be observed
through changes in the animal's behavior.

High levels of pain, when associated with human beings,

are said to evoke suffering.

If pain is near-detection level, it

(a) can be tolerated

(b) is not necessarily disruptive

(c) does not produce a high degree of emotional
reactivity.

(Analgesia and Anesthesia)

Drugs acting on the nervous system, particularly the
brain, are the primary agents for the alleviation of
pain:

(a) for use as a central control mechanism

(b) for use as a peripheral control mechanism.

Analgesia is relief of pain without unconsciousness.

(

(

(

(

General Anesthesia is the loss of both sensation to pain(

and consciousness.

Sleep

(a) produces loss of consciousness

(b) increases the pain detection threshold
(c) does not eliminate the response to pain.

(Anesthesia)

The Principle purpose for the use of anesthetic and
analgesic agents is to prevent response to pain

(a) induced from diagnostic procedures

(b) during surgery.

Local anesthesia or local analgesia involves loss of
sensation of a limited area of the body.

Regional anesthesia involves loss of sensation of a
large area of the body such as the hind legs.

General anesthesia provides overall insensitivity of
the whole body and unconsciousness.

I.

)3

)3

)2

)3

)2

)2

)4

)3

)2

)2

)3

)3

)2

)2

)2

(20)

( 8)

Part

(21)

(35)

(36)

(37)

Pll't

(22)

(23)

(24)

(38)

(25)

(39)

Part

(40)

(41)

(22) (5)

(42) (6)

G: 1.2.3

(41) (1)

(32) (2)

(42) (3)

(42) (4)

H: 1.2.4

(32) (1)

(21) (Z)
(32) (3)

(33) (4)

(32) (5)

(32) (6)

I: 1.3.1

(33) (1)

(33) (2)

231

Amnesia is the inability to remember past experiences or(
a loss of memory for a given time period.

If an individual is given a surgical level of general (
anesthesia, the individual will experience
unconsciousness, analgesia, absence of muscle movement
following a noxious stimulus, and amnesia.

(Sedation and tranquilizers)

Sedatives and tranquilizers produce a mild degree of (
central nervous system depression for which the patient
is conscious, but calm.

Sedatives and tranquilizers (
(a) do not relieve pain

(b) may dull conscious perception of pain

(c) relieve tension and anxiety.

Some drugs provide analgesia as well as mild sedation (
in the dog and human, but do not readily produce sleep:
(a) Morphine

(b) meperidine

(c) oxymorphone

Tranquilizers are administered to animals (
(a) to produce a calming effect
(b) providing a chemical restraint.

(analgesia)

Opiates are a group of naturally occurring opium (
compounds and their chemically related derivatives such
as morphine.

An exogenous substance is a substance outside the body. (

An Opioid is an exogenous substance which binds a (
specific type of nociceptor called opiate receptors.

Opioids (

(a) attach to the opiate receptors.

(b) At least partially block the sensation of painful
stimulus

Nonopioid antinfalammatory agents such as flunixin (
(banamine) and analgesics such as xylazine (Rompun)
have no affinity for opiate receptors.

Opioids produce their major effects on the central (
nervous system:
(a) analgesia
(b) sedation, with variable side effects of
respiratory depression
(c) decreased gastrointestinal motility
(d) nausea and vomiting

(Opiate receptors, Enkephalins and beta-endorphins)

The relative analgesic potency of opioids appears to be (
related to their attraction to receptors in the body.

Densities of opiate receptors are high in anatomical (
areas associated with physiologic functions that are
altered by opioids.

)2

)4

)2

)3

)3

)3

)2

)2

)2

)3

)2

)3

)3

)3

(42)

(26)

(43)

(44)

(45)

(46)

( 9)

Part

(47)

(48)

(49)

(50)

(51)

(33) (3)

(31) (4)
(33) (5)

(33) (6)

(42) (7)

(43) (8)

(44) (9)

J: 1.3.2

(32) (1)

(32) (2)

(32) (3)

(33) (4)

(42) (5)

232

There appears to be a correlation between the site of
action and the opioid effect.

Endogenous substances are produced inside the body.

Opiate receptors appear to be associated with specific
areas in the brain that function as sites of action for
a number of endogenous substances.

Enkephalins and beta-endorphins:

(a) are endogenous opioid-like compounds which

(b) appear to function as a built-in protective
mechanism of the body to

(c) help relieve pain.

It is assumed that exogenous opioids produce their
effects by mimicking some of the actions of enkephalins
and beta-endorphins

Some injured animals may not appear to be in pain
because of the production of endorphins.

If phenothiazine tranquilizer is administered to a
recently wounded animal, the treatment might actually
enhance pain by inhibiting the endorphin system-even if
the animal looks pain-free.

(Classification of Opiate Receptors)

The three major opiate receptors are Mu, Kappa, and
Sigma. The Mu receptors mediate analgesia and euphoria
and:

(a) respiratory depression

(b) dilation of the pupil

(c) sedation

(d) physical dependence

(e) abuse potential

The three major opiate receptors are Mu, Kappa, and
Sigma. Kappa receptors are primarily responsible for:
(a) analgesia

(b) pupillary constriction

(c) a modest degree of sedation

(d) a mild respiratory depression

The three major opiate receptors are Mu, Kappa, and
Sigma. Sigma receptors cause:

(a) restlessness

(b) mental anxiety

(c) hallucinations

(d) respiratory and circulatory stimulatory effects.

Two receptor types found in selected tissue:

(a) Delta receptors which appear to be selective for
enkephalins.

(b) Epsilon receptors which have a high selectivity
for -endorphins but lack affinity for enkephalins.

Most opioids
(a) have different affinities for different receptors
(b) are called drugs of the attracted receptor

(i.e. kappa drugs or mu drugs).

(

(

(

10

10

10

10

10

)3

)2

)3

)3

)3

)3

)4

)3

)3

)3

)3

)3

Part

(52)

(53)

(27)

(28)

(10)

(54)

Part

(55)

(11)

K: 1.3.3

(33) (1)

(44) (2)

(32) (3)

(32) (4)

(43) (5)

(41) (6)

L: 1.4.1

(43) (1)

(32) (2)

Part M: 1.4.2

(56)

(57)

(42) (1)

(43) (2)

233

(Classifying Opioid Drugs)

Opioid drugs are categorized as agonists, antagonists, ( 11 )3
or mixed agonist-antagonists depending on their actions

at the receptor sites. Opioid agonist acting at mu,

kappa, and sigma receptors:

(a) morphine

(b) meperidine

(c) fentanyl

(d) oxymorphone

Opioid drugs are categorized as agonists, antagonists, ( 11 )3
or mixed agonist-antagonists depending on their actions
at the receptor sites. Opioid antagonists, which exert
little or no physiological affect on their own:
(a) act at opiate receptors
(b) block the effects of the opioid agonist by its
displacement from the receptors.

Drugs are referred to as kappa agonists or mu agonists ( 11 )2
if they activate either kappa or an receptors
respectively.

Drugs are antagonists if they reverse the effects of the( 11 )2
opioid agonist by its displacement from the receptors.

If opioid agonists that produce their effects at only ( 11 )4
kappa receptors are used, analgesia can be achieved

without the side effects seen when mu receptors are also
triggered.

Naloxone ( 11 )3
(a) is a pure opioid antagonist which
(b) attaches to all opiate receptors.

(Agonist/Antagonist Drugs: Butorphanol)

Drugs classified as agonist/antagonist analgesics may ( 12 )3

bind to the mu receptors and either exert no action or

have only limited effects while exerting agonist action

at the kappa receptors to provide analgesia and varying

degrees of sedation.

(a) Butorphanol (stronger agonist than nalbuphine,
weaker antagonist)

(b) Nalorphine (weak agonist - strong antagonist)

(c) levallorphan (weak agonist - strong antagonist)

(d) Nalbuphine (weak agonist but stronger antagonist)

(e) Pentazocine

If a drug has a selective nature as a kappa agonists, ( 12 )4
fewer side effects are associated with its use.

(Uses of Agonist/antagonist Drugs: Butrophanol)

Agonist/antagonist analgesics may be used alone to ( 13 )3
(a) provide analgesia
(b) produce the effects of an opioid agonist.

Agonist/antagonist analgesics may be used after the use ( 13 )3
of a pure opioid to

(a) return the patient to consciousness

(b) relieve the opioid induced respiratory depression

(c) and to enhance analgesia.

(12)

(13)

Part

(29)

(58)

(30)
(59)

(14)

Part

(31)

(60)

(61)

(62)

(32)

(43) (3)

(42) (4)

M: 1.4.3

(42) (1)

(32) (2)

(32) (3)

(32) (4)

(31) (5)

0: 1.4.4

(21) (1)

(21) (2)

(32) (3)

(32) (4)

(32) (5)

ATTITUDES: 3

234

If a pure opioid such as fentanyl or oxymorphone has (
been used as a component of an anesthetic procedure and
analgesia is desired for postsurgical pain, an
agonist/antagonist analgesic such as butorphanol may be
given to return the patient to consciousness and relieve
the opioid induced respiratory depression while
enhancing analgesia.

If all the effects of an agonist/antagonist analgesic (
are to be reversed, a pure antagonist such as naloxone
may be given.

(Control of Agonist/antagonist Drugs)

Agonist/antagonist opioids have strong analgesic (
properties but have little propensity for physical
dependence or abuse.

Butorphanol and nalbuphine are not listed as controlled (
substances by the Federal Drug Enforcement Agency since:
(a) little propensity for physical dependence,

(b) however, they have a strong analgesic property.

Pentazocine is included as a class IV drug. (

The addictive properties of opioids is of little direct (
importance in the treatment of animals
(a) because veerinary patients are not usually given

opportunity to develop drug dependence
but are often restricted because of human

dependence.

If a drug such as the opioid agonists has a liability of(
addiction or physical dependence by humans, drug control
regulations may restrict veterinarians from using that
drug; especially for practices without good security and
record keeping systems.

(b)

(Narcotics)

The term narcotic, which originally designated drugs (
which stupify, now designates any substance which can
cause physical dependence or abuse.

Narcotic no longer denotes a pharmacological class, but (
designates any substance which can cause physical

dependence or abuse.

A narcotic may be an analgesic, but an analgesic may (
not be a narcotic, even if it affects opiate receptors.

Butorphanol is a agonist/antagonist with low potential (
for physical dependence because:

(a) even though symptoms resembling those of opiate
withdrawal were observed,

addictive behavior indicating a psychological

need was not exhibited.

(b)

Dutorphanol is not a Controlled substance and therefore (
is NOT classified as a narcotic drug with abuse
potential.

FACTS: 32 CONCEPTS: 62

PRINCIPLES:

13

13

14

14

14

14

14

15

15

15

15

15

14

)4

>4

)2

)3

)2
)3

14

)2

)3

)3

)3

)2

APPENDIX F

APPENDIX F

PROCEDURES FOR DESIGNING AND DEVELOPING INTERACTIVE VIDEO

1).

2).

3).

4).

INSTRUCTION

Determine that there is sufficient time to take on a
new project.

a).

b).

c).

Meet
a).

b).

It there is, check that there are not other pro-
jects to which you have future commitment or other
projects more worthy to do.

If there is not time available, check whether any
of the current projects that are less worthy can
be temporarily set aside to work on this project.
If so, reschedule them, do not just forget them.
Do not undertake a project, no matter how worthy,
if there will not be sufficient time to do a
thorough job with the project.

with the potential client

Determine his perceived needs, target audience,
and project expectations.

Explain the CAI groups role (if the project is to
be undertaken) and explain, as much as possible,
the CAI groups expectations of the client.
Collect copies of any relevant resource materials
the client may have available for the project (or
a working outline of what the course materials
will be).

Review and organize the data from the client.

a).

b).

c).
d).
Meet
a).
b).

c).

If the need for the project is not readily
apparent, do an needs analysis, otherwise merely
state the need for the project in instructional
format.

Reviewing notes from the meeting with the client
and at least skimming the materials the client
presented, determine the course, major section,
and unit goals.

Prepare an instructional needs report and an unit
level instructional goals outline.

Develop a unit level data flow diagram WITHOUT
INSTRUCTIONAL EVENT INFORMATION.

with the potential client

Verify that the materials developed so far are
correct.

Provide a rough estimate of the amount of time
involved with the project.

Establish deadline for a go/no go project deci-
Sion.

235

5).

6).

7).

8).

9).

236

Using the materials given by the client or meeting with
the client or associate, determine the instructional
events for each unit. Enter into a word processor with
10/70 margins. Save in ASCII (to end each line with a
line feed) with extension .seq. (see Sawyer.seq as an
example).
a). Course Title
b). Section heading
c). Unit information (repeat for each unit)
1). Part name (repeat each change in subpart)
2). Subpart name (if applicable)
A. lst Instructional event
1). (sequence number) First line
2). indent, rest of lines
B. 2nd Instructional event
1). (sequence number) First line
2). indent, rest of the lines
C. Etc.

Check the instructional events against the source
materials. Make sure all were entered. Determine the
reference of the instructional event. Determine the
type of each instructional event:

1. Attitude

2. Fact

3. Concept

4. Principle

Reload the instructional event file with margins 10/80.
Add the reference to the first line of each instruc-
tional event so that it takes a maximum of 5 spaces and
ends at 77. Add the number for the type of instruc-
tional event so that it ends at 79. Save in ASCII with
extension .iev.

Change the names of the files Run Instrdic.bas to
create the instructional dictionary. The output should
be an ASCII file ending with the extension .dic.

Using the instructional dictionary as a guide,

(a) complete the Data Flow Diagrams at least to the
Part level. Complete a subpart level data flow
diagram if:

(1) any part appears to have natural subdivisions
or

(2) any part has more than 15 events and the
amount of information presented needs group-
ing to aid in both comprehension and recall

(b) Indicate instructional events introduced in one
section and used in another on the data flow
diagram

237

(c) Recheck the instructional dictionary and data flow
diagram with the original source of instructional
material
(1) making any necessary changes

(a) omissions of materials
(b) sequencing errors
(c) misread materials
(2) prepare suggestions for the client for
changes where materials
(a) seem to be missing for good instruction-
al flow
(b) seem to be redundant
(c) seem to be extraneous

10). Meet with the client to
(a) verify the work completed:
(1) data flow diagram is correct at all desired
levels
(2) the instructional dictionary is complete
(3) the suggestions for client changes need to be
made
(b) ask client to
(1) determine the level of importance and dif-
ficulty for each instructional event
(leveldir.wp)
(2) fill out course and section worksheets
(Course.out).
(c) Provide followup support for activities in (b)
where necessary.

11). When client has completed (b) from 10)

(a) Enter the two digit level importance/difficulty
number into the data dictionary and save it in
ASCII.

(b) After changing the names, Run INSTRWRK.BAS. The
result will be:

(1) filename0.wrk containing all the low level
instructional events

(2) filenames.wrk containing the medium level
instructional events

(3) filenamel.wrk containing the high level
instructional events.

(c) Using the importance/difficulty number as a guide,
give the client an estimate of the amount of time
the project will take for each of the interested
parties.

12). While the client is filling out the instructional
events worksheets the authoring should begin for the
courseware
(a) create Menus from the Data Flow Diagrams

(b)

(C)
(d)

238

(1) Each process symbol should be a menu item

(2) Use models from the authoring system Library.

set up course introductions (If the video is not

developed yet, merely access dummy points on any

available disk and change frame numbers when the

video is available)

program the low level worksheets

If possible, start filming video segments from the
course and section outlines.

13). Encourage the client to "turn in" the worksheets after

each

(a)
(b)

(C)

(d)
(6)

part is completed (or at most, each section).
suggest improvements to the client if the materi-
als on the worksheets seem in ANY WAY inadequate.
Program complete parts whenever possible.

(1) Have a member of the staff check it.

(2) Make corrections/modifications

Have the client ”look over” each part (if pos-
sible) as soon as it is developed. (This will not
only allow for formative feedback as to how the
course is progressing, but will also help to keep
the client enthusiastic as he sees concrete prog-
ress being made.)

make modifications the client thinks important.
Verify!

Have students from the target audience check each
part upon completion for formative feedback.
Check any MAJOR recommendations by the student
evaluators with the client before programming the
"improvements”.

14). Check on the video production (if not completed ear-
lier).

(a)
(b)
(C)
(d)
(e)
(f)
15). When
(a)
(b)
(C)

Check that the storyboard has all necessary ele-
ments for the instruction

Check that the storyboard is arranged and organ-
ized efficiently

Check that all instructional elements were actual-
ly taped. If not, schedule taping OR consult with
client to modify the instruction

Check editing of master video tape

Review the final version with the client

Repeat (c)-(e) for mastered video disk

all the course programming is completed,
completely test the course with CAI staff member
with little contact with the development of the
course.

Modify any problem areas. Repeat (a) G (b) as
needed.

have the client test the program completely at the
CAI offices, if possible.

239

(1) Solicit feedback NON-JUDGMENTALLY. Provide
information when requested ONLY.

(2) Watch for non verbal feedback as the client
works through the complete system. Solicit
feedback on any areas that appear to be
problem areas for the client.

16). When the client is satisfied with the program, two or

17).

13) .

19).

20).

21) .

three students from the target student population

should run the program while being observed at the CAI

offices.

(a) Watch for nonverbal feedback as the students work
through the complete system.

(b) Solicit feedback on any areas that appear to be
problem areas for the students AFTER they have
finished the complete course.

(c) students should also fill out formative evaluation
forms that help determine areas that may be im-
proved in the courseware.

When the improvements suggested by the students are
incorporated in the course (if they are considered
improvements by the instructional designer and the
client),

(a) the course should be tested by four or five
students from the target student population in
the setting that will be used for the target
population.

(b) Students should fill out formative evaluation
forms that help determine areas that may be im-
proved in the courseware

(c) students should be debriefed, if possible, to see
if there are other possible areas of improvement.

When the improvements suggested by the students are

incorporated in the course (if they are considered

improvements by the instructional designer and the
client),

(a) the course should be ready for target student use

(b) continue to monitor the course carefully checking
(1) formative evaluation forms
(2) summative evaluation forms
(3) final tests of student learning.

Make any modifications necessary if 17) indicates the
need.

Ask client to evaluate the performance of your group
and the product produced. Use results to improve per-
formance on next project.

Continue modifications 17 and 18 as long as the course
is being used on at least a periodic check schedule.

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