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MULTIMEDIA TECHNOLOGY IN THE LIVES OF URBAN
MIDDLE SCHOOL STUDENTS: CONTEXTUAL AND SOCIAL
INFLUENCES ON MULTIMEDIA CONFIDENCE

presented by
Darryl Theodore Hall

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Multimedia Technology in the Lives of Urban Middle School Students:
Contextual and Social Influences on Multimedia Confidence

By
Darryl Theodore Hall

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree
DOCTORATE OF PHILOSOPHY

Department of Counseling, Educational Psychology, and Special Education

2005

ABSTRACT
MULTIMEDIA TECHNOLOGY IN THE LIVES OF URBAN MIDDLE SCHOOL
STUDENTS: CONTEXTUAL AND SOCIAL INFLUENCES ON MULTIMEDIA
CONFIDENCE
By
Darryl Theodore Hall

The purpose of this research was to study variations among urban
middle school students in their confidence with multimedia technology. Rarely
have researchers examined within-group differences in order to understand
the disparities between urban and suburban students in their ownership of
computers, lntemet access, and other uses of multimedia technology. This
study used both quantitative and qualitative methods to examine within-group
variations among 124 urban middle school students to understand social and
contextual influences on students’ patterns of computer use. Specifically, the
study examined the influence of time spent on multimedia activities; social
support networks for multimedia use; physical access‘to multimedia
technology; and early adoption of multimedia technology on multimedia
confidence among students.

Results revealed that students who spend more time on multimedia
activities, had larger social support networks that encouraged multimedia use,
had more physical access to multimedia technologies and had adopted
multimedia technology at an earlier age had higher confidence levels with
multimedia technology. Environmental factors such as physical access and

the amount of time spent on multimedia activities were the strongest

predictors of students’ confidence with multimedia. Both quantitative and
qualitative data supported the importance of social and contextual factors
such as social support network influences from the home and school
environment. Future research should include social and contextual factors
along with socioeconomic and other environmental considerations when

examining students’ use of multimedia and the digital divide.

COPYRIGHT BY
DARRYL THEODORE HALL
2005

Dedicated to my beautiful mother.
She continues to express her love through her sacrifice for family and friends.

For you, I am so grateful!

ACKNOWLEDGEMENT

I recognize that I am at this point only by His mercy and grace. Far too
many begin the journey of writing a dissertation only to have it go unfinished. I
am truly humbled by the graciousness of family, friends, and colleagues who
have provided untiring, spiritual, emotional, editorial, and even financial support.
Mentors near and far have shaped my work and commitment to an intellectual
life with practical applications.

I now fully understand that scholarship and the Ph.D. process is about
building and maintaining relationships-- through the scholarship that we produce,
the tasks that we carry out, and most importantly the people that we meet. I can
only endeavor to be part of a similar support system for others as I continue my
academic career.

My thanks go first to Dr. Patrick Dickson, my advisor who helped recruit
me during my first visit to campus. Thanks for your patience, understanding and
support, while I moved through my coursework and l labored through the
dissertation process. You have been a wonderful advisor. I want to thank my
other dissertation committee members including, Dr. Sonya Gunnings. I
appreciate your willingness to listen first as a friend and then as mentor. You will
always be special to me. Dr. Ernest Morrell, I appreciate your willingness to hear
my ideas and help me articulate them more clearly. I benefited greatly from our
informal discussions on research. Dr. Rand Spiro, I appreciate your inspiration
through the courses you taught early in the Ph.D. process and our informal

conversations about research and Jazz.

vi

I want to thank two other people who were always willing to share their
time and space. Dr. Gloria Smith, you helped me grow personally in so many
ways. Dr. Harriette McAdoo, you made me think deeply about my ideas.

I want to thank all of my colleagues and friends at the Graduate School
including Dean Karen Klomparens, Cathie Allison, and Tammy Wahpeconiah.
Also, I want to thank everyone at the King Chavez Parks Program (housed in the
Graduate School), Associate Dean Yevonne Smith, Evette Chavez, Rudi
Redmond, Pam Martell and all others

I want to thank friends I met along the way, Dave Kirkland, Austin
Jackson, and James Damico. Your feedback and conversations were invaluable.

I especially appreciate my support from friends back home. Dr. Tim Lake,
who on many evenings listened to me complain about graduate life and life in
general. Ramadan Abdul Azeez CEO of Blue Marble Inc, who encouraged me to
do good work that matters and stay grounded.

I want to especially thank my good friend Dr. Cheryl Boyce. Your
assistance in editing my work was invaluable. You really came through for me!

Finally, I want to thank my family-my sisters Robin Hall and Pamela
Kirkman who were always praying for me. My brother in-Iaw Edward you have
become a spiritual elder in the family. My older brother Derrick, you have always
served as my friend and mentor. I have always tried to emulate you. I learned to
dream because you were always dreaming. My mother, my first teacher, my
best friend, Alice Hall, because of you I understand the meaning of love through

sacnfice.

vii

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................. x
LIST OF FIGURES .............................................................................................. xi
I. INTRODUCTION ............................................................................................... 1
1.1 STATEMENT OF PROBLEM .......................................................................... 2
1.2 PURPOSE OF STUDY ................................................................................... 3
1.3 RATIONALE .................................................................................................... 5
II. LITERATURE REVIEW .................................................................................... 8
2.1 PHYSICAL ACCESS ...................................................................................... 8
2.2 CONFIDENCE AND SELF EFFICACY ......................................................... 11
2.3 ADOPTION PATTERNS ............................................................................... 14
2.4 TIME SPENT ................................................................................................ 17
2.5 SOCIAL SUPPORT ...................................................................................... 19
2.6 THEORETICAL FRAMEWORK .................................................................... 21
Ill. METHODOLOGY ........................................................................................... 28
3.1 BACKGROUND AND SETTING ................................................................... 28
3.2 SCHOOL DISTRICT ..................................................................................... 28
3.3 DATA COLLECTION SITE ............................................................................ 30
3.4 PROCEDURES ............................................................................................. 32
3.5 MEASURES .................................................................................................. 38
3.6 RESEARCH QUESTIONS AND HYPOTHESIS ........................................... 41,
IV. QUANTITATIVE RESULTS ........................................................................... 44
4.1 PARTICIPANTS ............................................................................................ 44
4.2 MAJOR CONSTRUCTS ............................................................................... 45
4.3 MAIN HYPOTHESIS .................................................................................... 62
4.4 FULL MODEL ............................................................................................... 72
V. QUALITATIVE RESULTS ............................................................................... 74
5.1 EXAMPLES OF PARENTAL INFLUENCES ................................................. 75
5.2 EXAMPLES OF SIBLING INFLUENCES ...................................................... 78
5.3 EXAMPLES OF TEACHER INFLUENCES VIA PROJECTS ........................ 78
5.4 CONCLUSIONS FROM INTERVIEWS ......................................................... 80
VI. DISCUSSIONS AND CONCLUSIONS .......................................................... 82
6.2 MAJOR FINDINGS ....................................................................................... 82
6.3 FUTURE RESEARCH .................................................................................. 86
6.4 CONCLUSIONS ............................................................................................ 87

14

viii

APPENDICES ..................................................................................................... 89

BIBLIOGRAPHY ............................................................................................... 102

ix

LIST OF TABLES

TABLE 4.1: MEAN AND STANDARD DEVIATION FOR STUDENTS’

CONFIDENCE IN THEIR ABILITIES TO USE MULTIMEDIA ............................. 47
TABLE 4.2: CORRELATION MATRIX OF STUDENTS’ CONFIDENCE
LEVELWITH MULTIMEDIA ................................................................................ 48
TABLE 4.3: MEAN AND STANDARD DEVIATION FOR TIME SPENT ON
MULTIMEDIA ACTIVITIES ................................................................................. 50
TABLE 4.4: CORRELATION MATRIX OF TIME STUDENTS SPEND ON
MULTIMEDIA ACTIVITIES ................................................................................. 51
TABLE 4.5: MEAN AND STANDARD DEVIATION FOR SOCIAL SUPPORT
NETWORKS ....................................................................................................... 53
TABLE 4.6: CORRELATION MATRIX OF PERSONS AS PART OF STUDENTS’
SOCIAL SUPPORT NETWORKS ....................................................................... 54
TABLE 4.7: MEAN AND STANDARD DEVIATION FOR STUDENTS’ ACCESS [
TO VARIOUS MULTIMEDIA ............................................................................... 57

TABLE 4.8: CORRELATION MATRIX OF STUDENTS’ ACCESS TO VARIOUS
MULTIMEDIA ...................................................................................................... 58

TABLE 4.9: MEAN AND STANDARD DEVIATION OF STUDENTS FIRST
ADOPTION OF MULTIMEDIA ............................................................................ 59

TABLE 4.10: CORRELATION MATRIX OF STUDENTS FIRST ADOPTOIN OF
MULTIMEDIA ...................................................................................................... 61

LIST OF FIGURES
FIGURE 4.1: CONFIDENCE WITH MULTIMEDIA AND HOURS PER WEEK ...64
FIGURE 4.2: MULTIMEDIA SCHOOL CONFIDENCE AND TIME ON SCHOOL

MULTIMEDIA ...................................................................................................... 64
FIGURE 4.3: TIME ON SCHOOL AND TIME ON ENTERTAINMENT
MULTIMEDIA ...................................................................................................... 66
FIGURE 4.4: FRIENDS ONLINE AND TIME SPENT ONLINE ........................... 66
FIGURE 4.5: MULTIMEDIA CONFIDENCE AND SOCIAL SUPPORT
NETWORKS ....................................................................................................... 68
FIGURE 4.6: SCHOOL MULTIMEDIA CONFIDENCE AND SOCIAL SUPPORT
NETWORKS ....................................................................................................... 68
FIGURE 4.7: MULTIMEDIA CONFIDENCE AND MULTIMEDIA ACCESS ........ 69
FIGURE 4.8: SCHOOL MULTIMEDIA ACCESS AND TIME ON SCHOOL
MULTIMEDIA ...................................................................................................... 69
FIGURE 4.9: MULTIMEDIA CONFIDENCE AND AGE OF FIRST USE ............. 71
FIGURE 4.10 SCHOOL MULTIMEDIA AND MULTIMEDIA PROGRAMS .......... 71

xi

CHAPTER I
INTRODUCTION
There seems to be agreement among policymakers, educators, and
researchers on the growing need to prepare students to use information
technology in their future careers. According to an industry survey by the
Information Technology Association of America (Joyner, 2000), United States
companies create on average 1.6 million new information technology jobs per
year. Based on the current application pool, more than half of the job openings
may go unfilled because of a lack of qualified applicants (Joyner, 2000). Also, it
is estimated that in the coming years, almost half of the US workforce will be
employed by industries that are either major producers or intensive users of
information technology products and services (Joyner, 2000). It is now common
knowledge that students need to be prepared to work in a technology-based
economy (Kvasny, 2002).

Multimedia technology has revolutionized how future generations will
communicate and participate throughout the nation and the world. New
technologies have been compared to the locomotive during the Industrial Age
(Castell, 1996). Multimedia technology revolution has important implications for
children and their future. While we know that multimedia technology plays a
crucial role in their social and cognitive development, it is somewhat uncertain
what the mechanisms and processes are that account for differences among
individual users. Historically, social and contextual factors have played a part in

the relationship between individual behavior and new technologies.

Statement of the Problem

Recently the term “digital divide” has been used to describe the disparities
in computer ownership and lntemet access. Early national survey data
illuminated these differences and the terms “haves” and “have-nots” emerged
(Hoffman, Novak, & Venkatesh, 1997; Katz & Aspden, 1997). These studies
presented findings that link the divide to ethnic and minority affiliation, geographic
location, household composition, age, education and income level (Hoffman et
al., 1997; Katz & Aspden, 1997; Kvasny, 2002). To bridge the digital divide,
national policies and initiatives were implemented to make physical access more
abundant to ethnic minorities and low-socioeconomic communities (Kvasny,
2002). The policies were based upon research that provided social and
psychological explanations for the divide.

Sociological explanations similar to those on diffusion patterns of new
innovations such as the telephone and television were used to frame studies on
the digital divide. Sociologists linked the divide to differences in social networks
and economic resources. More specifically, findings indicated that sparse
economic resources and restricted social networks as explanations for lower
rates of physical access in urban communities (Kvasny, 2002). Alternatively,
psychological explanations drawing on Bandura’s (1986) theory of self-efficacy
linked the digital divide to differences in computer efficacy and computer anxiety
(Weil & Rosen, 1995).

This early research is problematic for several reasons. First, by focusing

on the relationship between socioeconomic status and physical access only,

social explanations created binary relationships such as “haves” and “have nots”
that oversimplified the complexity of the digital divide. Multimedia users fall
somewhere along a continuum in their physical access to multimedia. Secondly,
psychological explanations alone ignore important sociocultural and
environmental factors that might impact the divide. Additionally, each of these
explanations tends to use a deficit lens that locates the problem within individuals
or cultural groups.

Purpose Statement

This study attempts to overcome these shortcomings by integrating
theories from psychology and sociology to explain the digital divide. The
relationship between multimedia confidence and contextual and social factors
such as physical access (Hoffman et al., 1997; Katz & Aspden, 1997), early
adoption (Brancheau & Wetherbe, 1990), social support networks (Kvasny,
2002), and time spent on multimedia (Alvarez, 2002; Robinson, Kestnbaum,
Neustadtl, & Alvarez, 2002; Wartella & Jennings, 2000) have been viewed as
affecting patterns of use.

In addition, an assets-based approach is used, which focuses on
strengths and differences related to disparities in multimedia use. The
quantitative data examined the relationship between multimedia confidence and
four independent variables. The qualitative data focused on contextual and
social factors that influence individuals in confidence with multimedia.

Respondents were considered to have a high level of confidence if on the

eleven-item multimedia confidence scale, they had a reported mean of four or
more on a five point Likert scale.

The study was designed to examine contextual and social factors that
affect multimedia confidence as suggested by our knowledge of children’s
development and their sociocultural contexts. While an understanding of
contextual and social factors that influence multimedia confidence for all children
is needed, this study focused specifically on urban children. Digital divide
literature suggests urban communities tend to be on the low end of the digital
divide. When children are considered, there are additional social and
developmental considerations that are necessary to understand their patterns of
use. It is unknown how the digital divide may affect children in urban
communities. Understanding how urban students use multimedia must be
studied as distinctive in nature. This study focused on within-group divides that
emerged as students participated in everyday uses of multimedia.

Educational research on urban populations abounds; however,
disentangling what urban means is often misunderstood. Educational
researchers commonly oversimplify our notions of urban communities by
depicting them as downtrodden neighborhoods with dilapidated buildings for the
desperately poor. What is lost in this portrayal is the economic diversity that
exists among urban communities. Indeed, urban students are more likely than
their suburban counterparts to experience greater exposure to poverty. Even
within the family, there may be challenges such as greater family mobility rates

and less stable home environments. However, it is a mistake to assume that all

urban students live in poverty and that those who do experience poverty will
experience poverty in the same way. Many urban students are part of working
class and middle class families. In the coming decades, urban gentrification may
create more economic diversity and more urban students may come from affluent
homes.

The site for the study was a magnet school that was situated in a working
class to lower middle class stable neighborhood. While the school attracted
students from a variety economic backgrounds, the majority of students would be
considered working class or lower socioeconomic status. The majority of
students walk to school from the surrounding neighborhood, while others either
ride the bus or are dropped off by parents. Throughout conversations with
students, a number of students referred to their parents’ employment as factory
workers, teachers, or secretaries. The school is flanked by a residential
neighborhood where most of the tenants have been long-term residential
homeowners.

Rationale

Understanding the plight of urban students is important for several
reasons. First, despite multimedia technology becoming an important and rapidly
growing part of our society and our children’s lives, everyday uses of multimedia
among urban students are understudied. There is limited data on adult urban
populations as well. Rarely, are urban students discussed in ways that

demonstrate the wide variation that exists among urban students. Various

developmental perspectives on children’s social and cultural development with
multimedia and learning informed this study.

Secondly, the prevailing assumption among many researchers conducting
cross-cultural research in information technology is that understanding patterns
of use for urban students is the same for suburban and rural students. Theorists
propose that beyond individual differences, what works in one context will
generalize to other contexts as well. Indeed, there are some practices that
transcend regional boundaries and geographical location. However,
understanding variations in patterns of use among urban communities is
fundamentally contextual. It can be argued that a different set of social,
contextual, political and historical factors impact how we make sense of the ways
in which urban communities engage with multimedia. Therefore, any attempt to
understand urban students patterns of use should be first studied as distinctive in
nature. While political and historical factors are important aspects that may help
explain patterns of use among urban communities (Castell, 1996; Kvasny, 2002),
for the scope and size of this study only social and contextual factors were
exanfined.

Additionally, many conversations regarding the multimedia needs and
performances of urban students discuss them as if they were a homogeneous
group. Rarely is research generated that focuses on within-group comparisons.
Comparisons of this kind require understanding individual differences that may
exist among cultural groups with similar social, contextual and historical

expenences.

Finally, this study builds on prior research on the digital divide by providing
another perspective that informs the current discourse on urban communities and
multimedia by using an approach that highlights the assets of high multimedia
confidence and users who are engaging in multimedia tools in sophisticated
ways. Narratives from their voices will challenge the current discourse, which
often characterize urban students as lacking technology skills. These narratives
reflect the long tradition of urban community-based technology organizations
such as the Black Data Processing Association, which hold annual computer
competitions involving urban youth, during which these urban students
demonstrate their mastery of complex multimedia skills such programming
languages including XTML and ColdFusion MX 7 (Bell, 2005; Meritz, 2004).

It is hoped that findings from this study can lead to the development and
support of education policies and programs that will allow more opportunities for
children from urban communities to more fully access and participate with
multimedia technology. A study such as this one can perhaps challenge the way
we think and talk about urban youth in general and particularly around

multimedia confidence.

CHAPTER II
LITERATURE REVIEW

Each year billions of dollars are spent on multimedia to provide children
access in school, at home, and in the community (Becker, 2000). At some level
the majority of American schools are equipped with multimedia technology, and
over two-thirds of American children have some type access at home. They are
socialized and mature in a world permeated with multimedia. The relationship
between children and multimedia technology has spawned new areas of
research in educational technology, communications, sociology, policy and
education.

This chapter begins with a literature review on multimedia technology
access. Secondly, this review explores factors such as confidence, efficacy, and
anxiety related to computer use. Third, adoption patterns for multimedia
technology among adults and children are discussed. Fourth, the amount of time
children spend on multimedia activities is discussed. Fifth, a brief summary of
the role of social support networks on computer use is explored. Finally, tenets
from social cultural theories are offered as a conceptual framework to inform this
study.

Physical Access

Computer ownership and access to the lntemet continues to be at the
forefront of debates on patterns of multimedia use. A series of national reports
have illuminated the disparities in computer ownership and Internet access

(National Telecommunications and Information Administration (NTIA), 1999,

2000, & 2002). The reports revealed that while more Americans than ever before
own computers and access the lntemet, the gap between information “haves”
and "have nots” persists and has widened. Despite declining costs of multimedia
technology and rising incomes, the digital divide appears to have increased
(Kvasny, 2002; NTIA, 1999, 2000, & 2002).

These annual studies report a gap between what is described as the
“information rich”, who are characterized as Whites, Asian Americans, and those
with higher incomes and education levels; and the “information poor" who are
characterized as those with lower incomes and lower educational levels, African
Americans, Hispanics and those living in central cities and rural areas (NTIA,
1999, 2000, & 2002). For example, a summary of the NTlA findings indicated
that households with incomes of $75,000 or above are more than 20 times more
likely to have lntemet access than those at lower income levels (NTIA, 1999,
2000, & 2002). Black and Hispanic households are roughly two-fifths less likely
to have home lntemet access as White households. A child in a low-income
White family is three times as likely to have lntemet access as a child in a
comparable Black family, and four times as likely to have access as children in a
comparable Hispanic household. Adults with a college degree are more than
eight times as likely to have a computer at home, and nearly sixteen times as
likely to have home lntemet access, than those without a college degree (NTIA,
1999, 2000, & 2002).

The inequities in multimedia access portrayed by these statistics are often

disputed and recent reports present an alternative view of multimedia access

(Kvasny, 2002). A government report, “A Nation Online: How Americans Are
Expanding Their Use of the lntemet” (2002), presented findings that show a US.
population rapidly growing with multimedia technologies across all demographic
groups and geographical regions with more than half of the nation online. In
September 2001, 143 million Americans (about 54 percent of the population)
were using the lntemet, which was an increase of 26 million in 13 months (NTIA,
2002). In September 2001, 174 million people (or 66 percent of the population)
in the US. used computers.

Additionally, computers at schools have substantially narrowed the gap in
multimedia use. Research findings suggest that individuals across racial and
economic lines are increasing their use of the lntemet by finding alternative
places for accessing information technology (Warschauer, 2003). Researchers
conclude that not only are many more Americans accessing the lntemet and
computers at home, but they are also using them at work, school, and other
locations (Warschauer, 2003). Recent data in the annual “Technology Counts”
issue published by Education Week (Education Week, 2005) support a narrowing
technology gap.

In short, over the past several years, multimedia access has increased
steadily for all demographic categories (NTIA, 2002). While some notable
differences remain in lntemet use related to income categories, computer
ownership has grown considerably among people who live in lower income
households (less than $15,000 annually) from 9.2 percent in October 1997 to 25

percent in September 2001. If the current trend continues aspects of the digital

10

divide related to multimedia access will diminish to the point of no longer being
an issue.
Confidence and Self-Efficacy
Bandura’s concept of self-efficacy is widely used within educational

research (Lent, Brown, & Hackett, 1994, 1996; Mitchell & Krumboltz, 1984).
Briefly, as originally proposed by Bandura from social cognitive theory (1977),
self-efficacy expectations refer to an individual’s beliefs concerning his or her
ability to successfully perform a given task or behavior. Bandura (1977)
postulated that beliefs are the major mediators of modifying behavior. Self-
efficacy is a form of self-evaluation that influences decisions about what
behaviors to undertake, the amount of effort and persistence put forth when
faced with obstacles, and finally, the mastery of the behavior. Therefore, low
self-efficacy expectations regarding a behavior or behavioral domain lead to
avoidance of those behaviors, and increases in self-efficacy expectations should
increase the frequency of approach versus avoidance behavior. Thus, self-
efficacy beliefs can be useful in understanding and predicting behavior.

Bandura’s concept of self-efficacy focused primarily on clinical treatments
by psychologists (Betz & Hackett, 2002). However, Hackett and Betz (2002)
were the first to apply the concept to other areas of research like career
counseling. They developed the occupational self-efficacy scale, which is widely
used today in career counseling and educational research (Betz & Hackett,
2002). Two formats of the self-efficacy have been developed. One format

requires single responses such as “yes” or “no”, while an alternative format

11

provides respondents with Likert-type ratings (Betz & Hackett, 2002). In each of
these formats, “confidence ratings” represent measures of self-efficacy.

More recently self-efficacy scales have been applied to research on
individual behavior and multimedia technology. Research has supported the link
between self-efficacy and individual responses to multimedia technology, both in
regards to adoption and integration of computers (Higgins, 1995B; Hill et al.,
1987; Talylor & Todd, 1995), and in terms of learning to use multimedia
technology (Compeau & Higgins, 1995a; Gist et al. 1989; Webster & Martocchio,
1992)

Computer self-efficacy does not refer to a person’s skill at performing
specific computer related tasks, such as writing HTML, using a web browser, or
transferring data files. Instead, it assesses a person's judgment of his or her
ability to apply computer skills to basic and complex tasks that require critical
thinking rather than rote learning of specific computer tasks. Extending
component skills such as formatting disks and booting up the computer to
behaviors that can be accomplished with component skills requires higher
computer self-efficacy (Compeau & Higgins, 1995). Using software to analyze
data, finding new information, or troubleshooting errors, are examples of
activities that require high computer self-efficacy. Novice computer users need
self-efficacy to overcome any fear and to master more complex computer skills
necessary for the advanced multimedia tasks now a part of effective computer
use. Higher self-efficacy in remote computing situations has also been

associated with more productive and satisfied users when working remotely

12

(Staples, Holland, & Higgins, 1998).

Researchers have used cognitive models base on self-efficacy and anxiety
to examine disparities in multimedia technology use. In their work titled “The
Psychology of The Digital Divide”, Eastin and LaRose (2000) conducted a study
that examined the lntemet and self-efficacy among college students. Their
findings indicated that lntemet usage could be linked to initial barriers such as
self-efficacy deficits, or low self-efficacy. Their research was a response to
prominent psychological explanations of the digital divide, which focused
exclusively on the relationship between multimedia technology disparities and
anxiety, namely computer anxiety. Other studies have explored human factors
such as inexperience, needs, and anxiety involved when using computers
(Paxton & Turner, 1984). Some have suggested that gender differences might
affect anxiety, efficacy and computer use (Gilroy & Desai, 1986).

In summary, differences in computer use between non-users and users,
and basic skill users versus advanced users are related to differences in
computer efficacy. Those with lower computer efficacy are less likely to perform
computer related behaviors in the present and future than those with higher
computer efficacy.

Research on computer self-efficacy has primarily focused on adult users.
However, these theoretical models can be applied to adolescents as well. While
all adolescents may learn basic computer skills by participating in various
multimedia activities, those with higher computer efficacy are able to apply these

skills for complex tasks such as publishing to the lntemet and creating digital

13

videos.

In this study, an eleven-item Likert type scale was used to assess
respondents’ beliefs in performing multimedia related task that ranged from basic
to complex. For example, a basic multimedia task was surfing the lntemet, while
a more complex task was using publishing software. The survey instrument was
derived from two surveys used in earlier research studies that examined access
to multimedia (Dickson & Phillips, 2004) and computer efficacy (Murphy, Coover,
& Owens, 1989). The Murphy, Coover, & Owens (1989) study referred to
confidence with computers as an application of self-efficacy theories of students
computer use. Similar to the methods in this research study, they developed a
32-item Likert scale that measured domains of computer self-efficacy.

Applying the theories and research on self-efficacy and computer use in this
research study, a student’s belief regarding his or her ability to perform
multimedia tasks or multimedia self-efficacy was operationalized as multimedia
confidence. Confidence ratings were proposed to bea valid indicator of self-
efficacy. Therefore, perceived confidence level with multimedia technology is the
construct that was measured and explored as the dependent variable and major
outcome for this study.

Adoption Patterns

Research studies have largely examined the adoption of technology in
workplace settings, but not for personal use at home and for students in schools
(Brancheau & Wetherbe, 1990). There appears to be a range of behaviors for

adoption of multimedia. Some individuals may adopt very early compared to

14

their peers. Others may adopt when technology has become the expected
behavior and standard. A longitudinal study found that those who adopted
technology later stated that they were afraid that rapidly changing technologies
would be obsolete (Brancheau & Wetherbe, 1990).

To describe this range of behaviors, Rogers (1995) defined five categories
of adopters: “innovators, early adopters, early majority, late majority, and
laggards” to describe the patterns of adoption of technologies in the home.
Results showed that innovators and early adopters represented a small percent
of adopters (16%) who integrated to technology quickly. Interestingly, the early
majority (34%) and late majority (34%) represented most adopters. The laggards
represented a similar small percentage (16%) who had not yet adopted
technology. However, this categorization assumes that eventually everyone will
adopt technology at some point, when in fact some individuals may never adopt
technology. Those who are resistant to adopt technology may use surrogates
such as friends and family to assist them with technology and never become
adopters themselves, or remain "laggards.”

Applying these characterizations of adoption and use for multimedia
technology among children suggests that the age at which a child adopts
technology may differentiate them from their peers. Early adoption could also
affect success in future educational and occupational outcomes mediated by
their confidence and skill level with multimedia technology.

Many of the home personal computer users (Kraut, Miller & Siegel, 1996)

will include innovators, early adopters, and part of the early majority type groups

15

will include innovators, early adopters, and part of the early majority type groups
described by Rogers (1995). Children in these homes may fit these
characterizations, but their use of multimedia in school could provide additional
opportunities for early adoption that do not rely on the purchase and use of a
home personal computer.

A recent report by the National Center for Educational Statistics (2004)
revealed interesting results regarding where and what age children are adopting
new technologies. For example, home and school are the primary locations
where children and adolescents began to use computers. About 90% of children
and adolescents ages 5—17 used computers for general applications while
approximately 59% used computers for accessing the lntemet. Surprisingly,
among younger children who were five years old, 75% used computers for
general use, while 59% used computers for the lntemet (NCES, 2004). Trends
suggest that the majority of children are adopting computers at earlier ages and
for a variety of reasons. }

Similar trends among families suggest dramatic increases in computer use
rates. During a five-year period from 1996—2000, among families with children
from ages 2 to 17, home computer use increased from 48% to 70%, while
lntemet connections penetrated homes at a 150% rate over the same period
(Woodward & Gridina, 2000). Current estimates project that computer ownership
and lntemet access will reach 90% market penetration by the end of the decade

(Woodward & Gridina, 2000). The rapid diffusion of physical access of

16

computers is described as nine times faster than that of radio and three times
faster than television (Woodward & Gridina, 2000).

Technology adoption patterns have important implications for predicting
later use. Findings by Brancheau and Wetherbe (1990) suggested that early
adopters of new multimedia technology developed more positive attitudes and
sustained their use over time. Early technology adopters were less likely to
experience “end-user frustration” (Brancheau & Wetherbe, 1990). Early adopters
were better educated, had higher income levels, had more access to various
multimedia, and were more computer-literate than later adopters. Conversely,
late adopters experienced an array of barriers to overall use such as lower self-
efficacy levels and increased anxiety. Late adopters also spent less time
engaged in multimedia activities. Higher rates of self-efficacy demonstrated by
early adopters are important indicators of later use.

Time Spent

The emergence of multimedia has drastically changed the way children
spend their time. Studies such as the Kaiser Family Foundation’s 1997 Report on
Kids Multimedia & The New Millennium (Kaiser, 1999) and the Hemmingway
Foundation ’3 2000 Report on Children and Interactive Media (Wartella 8.
Jennings, 2000) indicated that young people spent as much time engaged in
multimedia activities as they did in school or with family or friends. According to
one national survey, children between the ages of 2 and 17 spent approximately
ninety minutes a day using the computer and/or playing video games

(Subrahmanyam, Kraut & Greenfield, 2000). Multimedia activities can include

17

everything from video games, and the lntemet to handheld computers.
Multimedia activities appear to be the most common way that children ages 2-18
spend their time (Becker, 2000).

Time has been conceptualized in two ways: discretionary time and non-
discretionary time (Robinson, Kestnbaum, Neustadtl, & Alvarez, 2002). On
average most adults and students engage in activities regarding during non-
discretionary time, which includes a number of activities that occur on a regular
basis. For students, attending school would be an example of an activity during
the academic school year that would be classified as non-discretionary time
(Robinson, et al., 2002). Self-maintenance activities such as eating, dentist
appointments, and exercise are all activities that are considered discretionary
time. In this study, students reported on their engagement of multimedia
activities during discretionary time.

Research findings suggest some positive outcomes for children who have
access to computers and spend more time engaged in multimedia. The
Annenberg Public Policy Center found that children in households without
computers watched approximately one hour more television each day than
homes with computers (Subrahmanyam et al., 2000). Children in homes with
computers spent less time playing video games and more time doing homework
and reading magazines (Subrahmanyam et al., 2000).

Additionally, children who spend more time engaged in multimedia
activities gain more expert knowledge and are typically able to use multimedia in

more productive ways. Time was an important construct in the current study,

18

which explored the relationship between multimedia confidence and time spent
on multimedia.
Social Support

Computers have allowed individuals to create social networks by linking
them to people, organizations and knowledge (Wellman, 2001 ). Technologies
such as the lntemet have the potential to increase a person’s social capital by
linking him or her to friends and families. The diffusion of innovations literature
expresses the importance of social support networks in the spread of new
technologies (Hargittai, 2003). Newer technologies are more likely to be adopted
by individuals in communities who have greater exposure (Hargittai, 2003).

The digital divide has been linked to restricted social networks (Kvasny,
2002). Researchers have suggested that restricted social support networks are
linked to variations in patterns of use in urban communities (Rice, Grant,
Schmidt, & Torobin 1990). Anecdotal evidence has proposed that social support
networks where experienced users can draw upon the expertise of more
experienced users are important to new users in underserved communities
(Kvasny, 2002). Fulk and Boyd (1991) have argued that social networks
influence behavior through messages and signs that are assigned to specific
activities. Whereas physical capital refers to physical access, human capital
refers to the properties of individuals, and social capital refers to connections
among individuals such as social networks and the norms of reciprocity and trust

that arise from them (Putnam, 2000).

19

Within urban communities, poverty must be considered in terms of its
impact on social support networks. William Julius Wilson (1987) provided
theoretical and empirical work in social network analysis and social capital theory
and contended that social isolation perpetuates poverty. Wilson originally
proposed that social isolation was an alternative explanation to the then
prominent cultural deficit explanations. Since then, social capital theory has
argued that those in poverty find it difficult to access resources related to social
and human capital, such as, information, health care, housing and education.

Wilson’s analysis has been important for researchers who have attempted
to understand multimedia use in urban communities (Becker, 2000; Kvasny,
2002; Warschauer, 2003). It has been argued that disparities in multimedia
access and integration may be linked to social spheres with an abundance of
resources compared with those in which resources and opportunity are scarce
(Kvasny, 2002). The implications of scarce resources or restricted social support
networks have implications for students in urban schools. In a recent qualitative
study on the digital divide, Warschauer, Knobel and Stone (2004) compared the
availability of, access to, and use of new technologies in a group of low-SES and
high-SES California high schools. They found that social contexts for computer
use was negatively influenced by differences in human support networks among
low-SES school students. These differences included parental attitudes toward

computer use for school purposes (Warschauer, et al., 2004).

20

Theoretical Framework

There are few studies on children and multimedia, particularly in urban
communities. Yet, there are theories on children’s social and cognitive
development that can be applied to frame this problem.

Cognitive theories have served as dominant approaches to examining
human development. The more recent dramatic shift from behaviorism to
cognitivism focuses our attention on rich descriptions of mental processes
(Kirshner & Whiton, 1997). In cognitive theories, knowledge is viewed as
symbolic mental representations in the individual mind, and learning is the means
by which these symbolic representations are memorized (Greeno, Collins &
Resnick, 1997). Notions of progress and development reflect changes in the
organization of mental operations. Therefore, teaching for transfer of knowledge
from one context to another is an important concept. Cognitive theorists make
the separation between knowing and doing and the context in which it may occur
(Collins, Brown, 8. Newman, 1989). Recent investigations on learning and
development offer an alternative view of learning and development that examines
the “situatedness” of knowledge.

Sociocultural theory emerging from the work of Vygotsky (1978) raised
issues that challenge the notion of a separation of how knowledge is constructed
from the way it is constructed, submitting instead that learning and cognition are
situated in the activity, context, and culture in which it occurs (Brown, Collins, &
Duguid, 1989). Vygotsky’s developmental theory emphasized the inherent social

nature of all human endeavors (Smagorinsky & Lee, 2000). A fundamental

21

premise of Vygotsky's (1978) theoretical framework is that social interaction plays
a fundamental role in the development of cognition. Vygotsky offered two
propositions concerning his work the “genetic law of cultural development” and
“the zone of proximal development”.

First, the “genetic law of cultural development” theorizes the connection
between the social and the psychological. Vygotsky proposed that learning and
development occurred in the social realm and then the psychological realm.
Vygotsky viewed these fundamental sign-means as confirmation of the historical
transition from natural to culturally mediated forms of behavior. He asserts:

“Any function in the child’s cultural development appears twice, or on two

planes. First it appears on the social plane, and then on the psychological

category, and then within the child as an intrapsychological category. This is
equally true with regard to voluntary attention, logical memory, and
formation of concepts, and the development of volition. We may consider
this position as a law in the sense of the word, but it goes without saying
that internalization transforms the process itself and changes its structure
and functions, social relations or relations among people genetically

underlie all higher functions and their relationships” (Vygotsky, 1978, p.

163)

Second, the zone of proximal development has been interpreted as the
“distance” between the problem solving abilities by an individual working alone
versus the leamer’s problem solving in collaboration with a more capable other

(Vygotsky, 1978). The distance is viewed as the space between everyday actions

22

and historically new forms of social activity. Aspects of the zone of proximal
development have been studied in a variety of ways. For example, African
American discourse patterns have served as a scaffold for literacy development
(Lee, 1995). Latino families’ indigenous knowledge has been linked to classroom
learning (Moll, 1990). Young adults have learned to use multimedia through
collaborative learning systems (Cole, 1996). Despite some variations, scholars
focus on the how individuals participate with others within a seamless
involvement of social cultural activity (Rogoff, 1990).

The sociocultural perspective maps onto understanding learning as it
occurs in everyday routine activities. Anthropologists and cross-cultural
psychologists have examined the differences between learning as it occurs
through participation in everyday activities within informal environments and
formal settings such as school (Cole, 1989). Early on researchers discovered a
mismatch between how cognitive strategies were used in informal settings
versus formal settings. For example, research by Lave, Murtaugh, and de la
Roche (1984) on mathematics and everyday practices found that grocery
shoppers who scored poorly on a formal arithmetic test were able to use
legitimate arithmetic operations to make informed choices at a supermarket. As
Gordon asserted, “This substantiates the fact that students appeared to use
memory strategies suboptimally when performing a task in one setting often used
them strategically on a different task in a different setting” (Gordon, 2003, p.
200). These important findings speak to the situatedness of knowledge and serve

as the foundation for further research models that can be used to explore notions

23

of individual progress and development as it occurs in real world contexts for
learning and technology.

Apprenticeship learning models have served as a useful paradigm for
understanding the mutual embedeness of learning and activities in authentic
settings. Apprenticeship applies to a specific group of individuals who are
working toward the establishment of mutually shared goals (Rogoff, 1990). The
group may involve colleagues or peers who are novices or experts who serve as
resources in examining shared activity. In the apprenticeship paradigm,
newcomers to a community of practice advance their understanding through
participation with others in shared activity. Apprenticeship is often associated
with the apprentice-master relationship of traditional crafts (Lave &Wenger,

1 998).

Lave and Wenger’s (1998) seminal research on apprenticeship learning
explored how individuals move from novice to experts in communities of practice.
Their concept of legitimate peripheral participation is a framework of social
learning theory that focuses on “old-timers” and “newcomers” and how their
individual identities are transformed and shaped as they participate in
communities of practice and engage in everyday activities (Lave & Wenger,
1989). Learners acquire some skills, become knowledgeable and have new
understanding of the application of those skills. Through participation in shared
activities and culturally defined norms, individuals move from peripheral

participants to more established members. Legitimate peripheral participation

24

conceives of learning as a process of increasing participation within sociocultural
contexts known as communities of practice.

The concept of communities of practice are linked to learning in social
contexts. Members of a community of practice are bound by their focus on and
participation in culturally developed practices. Communities of practice have
been studied in a variety of settings such as apprenticeship settings (Jordan,
1993), the workplace (Wenger, 1990) and school classrooms (Carlock, 1995).
The shared practice component differentiates a community of practice from an
interest group. Wenger (1998) asserted that a community of practice defines
itself along three dimensions:

1) What it is about (i.e. its joint enterprise as understood and

continually renegotiated by its members)?
2) How it functions as a “mutual engagement” that binds members
together into a social entity? f
3) What capability it has produced (the shared repertoire
of communal resources, including routines, sensibilities, artifacts,
vocabulary, styles, etc.) that members have developed over
time?
Many people participate and learn in a variety of communities of practiceuat
home, at school, and at work. These settings evolve over time as new
technologies emerge.
Recently, scholars have used a sociocultural lens to look specifically at

learning and young people’s appropriation of various multimedia in informal

25

Ieaming settings. In his seminal work on children and video games, Gee (2003)
identifies thirty-six learning strategies such as probing, hypothesizing, reprobing
and rethinking that young people employ as they learn to master video games.
Findings also support our understanding of students’ enculturation into video
game culture through manipulation of various kinds of multimedia activities. For
example, he asserted that “within the chatrooms and the online exchanges, web
sites, documentation manuals, underground cheats and language associated
with computer games—young people learn semiotic and the cognitive skills they
will need in the changing contemporary high-tech world as well as the values and
skills that make such skills important” (Gee, 2003, p. 142). Gee’s findings
support Ieaming in informal spaces while participating as a member of a
community of practice. Leander (2003) made a similar observation in his
examination of everyday uses of the lntemet.

Given the characteristics of the sociocultural lens and the scholars
associated with this perspective, tenets of the sociocultural perspective serve as
the framework for the current study. Students’ multimedia activities reflect their
participation in various multimedia literate communities. Within these
communities, they operate with varying levels of confidence as experts or
novices with multimedia tools. Cognitive apprenticeship assumes that students
are active agents that are purposefully seeking and constructing knowledge
within a meaningful context with computers. As students use various multimedia
tools such as computers and video games players, they are acting in purposeful

ways. They are attempting to achieve some underlying goal.

26

Students gain expertise with multimedia through participating in activities.
They create and produce knowledge within communities of practice. As they
move from novice to expert users, their identities change. They participate in
multiple communities of practice in formal and informal Ieaming spaces.
Operating in the zone of proximal development, teachers, parents, peers and
multimedia serve as scaffolds to support their mastery of multimedia activities.

Variations in students' multimedia activities can be linked to the ways in
which they have been apprenticed into communities of practice, and the situated
knowledge that stems from their experiences. Some students are operating
within multimedia communities of practice on the periphery, while others have

moved toward the center.

27

CHAPTER III

METHODOLOGY

Background of the Setting

The study was conducted in a small midwestern city in the US. According
to city reports, the median income for a household was $34,833, and the median
income for a family was $41,283 (Lansing Report, 2001). The city is located in
the south central part of the lower peninsula of the state where two rivers meet.
There were 119,128 people, 49,505 households, and 28,366 families residing in
this city according to 2000 US. Census reports (Lansing Report, 2001). The
research questions for this study included information on social and contextual
patterns among urban communities. Therefore, a culturally diverse, urban
community was necessary for the subject population of this study. The racial
makeup of the city was diverse with White (65%), African American (22%),
Hispanic or Latino (10%), Native American/American Indian (1%), and Asian
(3%) populations. Given the city’s status as a state capital, many residents were
employed by the local state government (Lansing Report, 2001). The city was
home to an automotive plant that employed another large sector of the
population at the time of the study.
School District

The school district where the study was conducted included 43 schools

that served approximately 17,000 students from K through grade twelve
(Lansing, 2001). The school superintendent was the city’s first female and

African American individual in this position. One of the early challenges for the

28

superintendent was student retention that posed a serious threat to the viability of
urban school systems in the state. Through a statewide “school of choice”
program, students were allowed to attend any school in their area. Therefore,
urban school districts began to compete with suburban school districts for the
same students.

To address this issue, the new superintendent implemented the magnet
school concept. Historically, magnet schools in urban areas were designed to
assist schools with racial desegregation (Kahlenberg, 2003). These schools offer
similar features like those of a traditional public school but specialize in a specific
subject area, such as math, science, or performing arts (Kahlenberg, 2003).
Unlike charter schools, magnet schools remain part of a school district. Magnet
schools are often not limited by neighborhood boundaries and can draw students
from across the district. For this reason, magnet schools are often referred to as
“schools of choice”. Critics have suggested that magnet schools drain important
resources such as outstanding teachers and school supplies from neighborhood
schools (Kahlenberg, 2003).

The site for this study was a magnet school for middle school students.
The school integrated an academic curriculum with an enriched exposure to the
visual and performing arts. Additionally, the school was a recipient of a state
grant program designed to bridge the digital divide by expanding multimedia
technology opportunities to students, especially those students living in rural
areas and experiencing poverty. The aim of this grant program was to improve

student achievement in core academic subjects by providing an enriched

29

educational environment with access to multimedia technology (Lansing Report,
2001). The program provided assistance with technology-enhanced art, digital
music composition and lntemet research (Lansing Report, 2001). With this grant,
the school provided laptops for all of its students. However it is important to note
that during the time of the study, none of the students had received laptops
because of administrative and logistical delays. Therefore, the grant program
was not able to change student’s level of multimedia access by providing
increased physical access to multimedia.
Data Collection Site

The school where data was collected for the study was situated in a
working-class, ethnically diverse, urban neighborhood. The building was
converted from an elementary school. The interior reflected the open classroom
design concept that was popular in the early seventies era. There were no
permanent doors on classrooms, but only pre-fabricated sliding doors to separate
classrooms. Both teachers and students complained about the organizational
layout of the school. Teachers cited high noise levels and lack of privacy as
problems within the classroom environment. Students expressed concerns that
the design of the building did not allow them to have space for amenities such as
personal lockers.

Like many schools in middle size or small school districts throughout the
US, the majority of teachers at the school were White and female (Darling-
Hammonds, 1999). Teachers were selected based on their interests in the visual

arts and outstanding prior experience (Lansing Report, 2002). The teacher ratio

30

was 22:1, which is considered good for an urban school setting. Compared to
other middle schools in the district, the school had the smallest student
population. The school population reflected the ethnic and socioeconomic
diversity of the larger school district and bordering neighborhoods. The school
consisted of mostly low to working class families with 53% of students
participating in free or reduced-lunch assistance programs (Lansing Report,
2002). The predominantly minority student population was in stark contrast to
the largely White teaching staff. Table 3.1 provides a summary of the
demographic data for the district and the larger community.

Table 3.1: Ethnic Composition of the School District and Middle School

Research Site

 

 

 

 

 

 

 

 

 

School District Middle School Research Site
White 46% African American 60%
African American 33% White 30%
Hispanic/Latino 12% Hispanic/Latino 8%
Asian American 5% Asian American 1%
Respondents

Originally, 150 students from a local area middle school participated in the
study. After accounting for missing data and lost surveys, there were 124 valid
surveys for analyses from both female (n=83, 67%) and male students (n=41,
33%) who were enrolled in sixth (n=43), seventh (n=37), and eighth (n=44)

grades (See Table 3.2). The response rate for this study was very good at 83%.

31

Respondents participated according to the policies and guidelines of the
University Committee on Research Involving Human Subjects (UCRIHS) at
Michigan State University.

Table 3.2: Gender and Grade Level of Respondents

 

 

 

 

 

 

 

 

Males Females
Grade Six 17 26
Grade Seven 10 27
Grade Eight 14 30
Procedures
Mixed Methods Research

Within the social sciences, mixed methods research has garnered
widespread support as a stand alone research design (Creswell, 2002, 2003;
Tashakkori &Teddie, 2003). It may be defined as “the collection or analysis of
both quantitative and qualitative data in a single study in which the data are
collected concurrently or sequentially, are given a priority, and involve the
integration of the data at one or more stages in the process of research”
(Creswell, 2002, 2003; Tashakkori & Teddie, 2003). When both quantitative and
qualitative data are included in a study, researchers may enrich their results in
ways that one type of data does not allow (Creswell, 2002, 2003; Tashakkori 8
Teddie, 2003). Using both forms of data, for example, allows researchers to
simultaneously generalize results from a sample to a population and to gain a
deeper understanding of the phenomenon of interest. It also allows researchers

to test theoretical models and to modify them based on participant feedback.

32

 

Results of precise, instrument-based measurements may, likewise, be
augmented by contextual, field-based information.

The use of both quantitative and qualitative data improved the construct
validity of the current study. In order to understand the social and contextual
reasons for variations in the patterns of students’ multimedia use, a mixed
method approach was very effective. The quantitative survey data were
particularly useful in exploring the variety of access of multimedia in the lives of
students. It further revealed variations in patterns of use. The qualitative
interviews provided a deeper exploration of the findings from the quantitative
data.

Validity and Reliability of Self-Report Data

Kuh (2001) has discussed several issues regarding reliability and validity.
The arguments concerning reliability and validity were heavily influenced by
Kuh’s work on surveys of college freshman at Indiana University and informed
this dissertation study, which relied on self-report data. Using self-reported data
from students to assess their use of various multimedia tools is common practice.
By and large, achievement tests have failed to adequately measure outcomes
such as beliefs or attitudes or gains in social and practical competence (Kuh,
2001). Student self-reports are an informative source of data to provide insight
into student perceptions and the indicators of good educational practices with
multimedia. For example, how students use their time with multimedia

technology can be most accurately assessed using student self-reports. Teacher

33

and parents may not be aware of how students spend their time in multiple
environment contexts.

Other researchers have examined the validity and credibility of self-reports
extensively (Pike, 1995). In using self-reports, accuracy can be affected by two
problems. One problem is that self-reports involve the respondents’ inability to
provide accurate information in response to a question (Wentland & Smith,
1993). Students might lack knowledge regarding various technological terms to
provide precise judgment on their multimedia use or they might simply not
understand the questions. The second problem involves how willing respondents
are to provide truthful information (Kuh, 2001). Students could intentional
misrepresent information about their multimedia use. Bradbum and Sudman
(1988) argued that respondents typically provide accurate information related to
their past experiences, except in cases in which information can place them in
uncomfortable situations. To optimize self-report data for students’ self-reports of
multimedia the questions should be easy to understand and administered in a
manner that is appropriate and comfortable for their developmental age.

Self-report data can raise questions about validity. For example, in the
present study, respondents were asked to report the amount of time they spent
engaging in various lntemet activities. According to Kuh (2001), estimates of
time usage tend to be less accurate than diary entries. To reduce this threat to
validity, Kuh suggested that respondents should be asked about recent activities
that they are more likely to remember with accuracy. It is also important to

reference specific time frames to obtain accurate information on behaviors.

Referencing a specific, recent period of time to be considered can improve
memory recall and reduce distortion since respondents tend to remember more
current events (Converse & Presser, 1989; Singleton, Straits, & Straits, 1993).

A halo effect can also impact the accuracy of student self-reports. That is,
there is a possibility that students might inflate certain aspects of their behavior,
such as time spent on educational activities with computers or their confidence
level interacting certain technologies. Fortunately, Pike (1995) has argued that in
the event that the halo effect occurs, it appears to be consistent across different
types of students. As Kuh (2001) distinguished, “while the absolute value of what
students report may differ somewhat from what they actually do, the effect is
consistent across schools and students, so that the halo effect does not appear
to advantage or disadvantage one student group compared with another.”

Given these considerations, self-reports are considered valid under five
general conditions according to Pike (1995). The first condition is that the
information requested has strong psychometric validity and reliability. The
second condition requires that questions be phrased clearly and unambiguously.
The third condition is that questions should refer to recent activities. Fourthly,
respondents should believe that the questions merit serious and thoughtful
responses. Finally, answering the questions should not threaten, embarrass, or
violate the privacy of the respondent or encourage the respondent to respond in
socially desirable ways.

The survey design of this dissertation attempted to satisfy all conditions

related to validity for self-report data among the students who participated in the

35

study. Prior to administering the survey, the researcher met with teachers and
students to familiarize them with each section of the instrument. Memory recall
was enhanced by asking students about the frequency of their participation in
multimedia activities during the past month. To eliminate the variability in day-to-
day fluctuations, students reported the number of hours spent in multimedia
activities during a normal week. This also allowed for an accuracy check on the
total number of hours students reported. The format for most of the responses
was a simple Likert-type rating scale. This repetitive simple scale formatting
helped students to understand the Likert scaling system and accurately recall
and record their multimedia activities to minimize this as a possible source of
error.

In summary, evidence clearly supports the use of self-report surveys in
collecting data. Under the right circumstances, including clearly written questions
and pertinent informatiOn, students can accurately report on their daily activities
with multimedia. Middle school students often spend a majority of their time
alone and with peers across multiple contexts. Conceivably, they are the most
appropriate reporters of their own weekly activities with multimedia.

Survey Questionnaire

The complete battery of instruments was administered during a two-week
period in the spring of 2004. The general purpose of the study was described to
the students first and then any remaining questions were answered. Both parent
and student consent forms were required for the study (See Appendices A and

B). As part of this consent form, participants were informed of their right to

36

refuse to answer any questions and to withdraw from the study at any time
without any consequences.

At the end of the testing session, students were thanked and debriefed
about the research project. Students were provided the opportunity to receive
results of the study when the study was completed, to be contacted for further
interviews, withdraw from the study without consequence, and to ask further
questions. In addition, the names and phone numbers of the experimenter and
dissertation advisor were listed on the consent forms that were provided to the
respondents to serve as contact persons for any questions or concerns regarding
the study. Each respondent was assured anonymity and confidentiality in later
reports. Data were for research purposes only and were analyzed as group data
only. All data were kept secure in a locked room.

Psychometrics and Scaled Validity

Subscales from the questionnaire assembled for use in this study were
originally developed and validated on college populations (Dickson & Phillips,
2004; Robinson, 2001). Given the importance of validity, a considerable amount
of time was dedicated to ensure that the survey instrument was clearly worded,
well defined, and had good content validity for middle school students. The
responses to the questionnaire items were normally distributed. The patterns of
responses to clusters of items (i.e. multimedia confidence, early adoption of
multimedia technology, social support networks for multimedia use, access to
multimedia technology, and time spent on multimedia activities) discriminated

among students both within and across gender and grade levels.

37

The degree to which an instrument is reliable is another important
indicator of an instrument’s psychometric quality. Reliability is the degree to
which a set of items consistently measures the same thing across respondents
and institutional settings (Kuh, 2001). Reliability analyses were conducted on
each of the constructs and are reported in the results section in Chapter IV.

Measures

The questionnaire ascertained demographic data; early adoption of
multimedia technology; social support networks for multimedia technology use
(Kvasny, 2002), physical access to multimedia (Katz & Aspden, 1997; Hoffman et
al., 1997), time spent on multimedia activities and perceived confidence with
multimedia. Each of these subscale constructs are described below.

Demographic information. Demographic information including academic
grade level and gender was collected (See Table 3.2 for summary data) to
determine any differences between male and female students and their current
grade level expectations.

Early adoption (Brancheau & Wetherbe, 1990) (See Appendix C , Section
A). The early adoption of multimedia technology subscale consisted of seven
items that assessed students’ first use of various multimedia activities and first
access of physical multimedia hardware. Respondents indicated their age at first
use. Early adoption was coded as “0” if there was no participation indicated for a
particular activity.

Social support networks (Kvasny, 2002) (See Appendix C, Section A).

Three questions assessed students’ available social support networks for

38

multimedia use. One question asked respondents to identify from a list of ten
persons such as parents and teachers, who influenced their use of multimedia.
Respondents could identify multiple supports. Another question sought
information on the place where students’ first used computer technology.
Students were also asked where they most often engaged in computer
multimedia activities.

Physical access (Hoffman et al., 1997; Katz & Aspden, 1997) (See
Appendix C, Section A). This measure was designed to assess students’ overall
physical access to entertainment multimedia such as televisions and compact
disc players, as well as school related multimedia such as desktop computers
and educational software outside the school environment where standard
equipment was provided for all students. Respondents had a list of sixteen
multimedia items to choose their level of access outside of school. “Easy”
access was defined as physical availability to multimedia technology as
frequently as possible.

Time spent (Wartella & Jennings, 2000; Robinson) (See Appendix C,
Section B). The time subscale included seventeen items to assess the time
spent on multimedia activities. Time was measured in hours per week.
Respondents indicated their time spent on various multimedia activities related to
school and entertainment purposes including television, video games, lntemet,
and educational software.

Multimedia confidence (Brancheau & Wetherbe, 1990) (See Appendix C

Section C). Confidence level with multimedia technology was the major

39

dependent construct in the study. The measure was designed to appraise
students’ confidence level in completing eleven multimedia activities related to
school and entertainment. Some activities involved more basic skills such as
surfing the Internet, while other activities involved more complex skills such as
designing a webpage. Respondents indicated their confidence level on a five-
point Likert scale (i.e., 0=strongly disagree; 1=somewhat disagree; 2=neither;
3=somewhat agree; and 4=strongly agree) to designate their degree of
confidence for each multimedia activity.
Interviews

Ten students in groups of two and three were interviewed using small-
scale focus group interviews by one researcher. The use of the focus group
interviews is now a well-established part of research in educational settings
(Flores & Alonso, 1995). Because interviewing middle school students can be
challenging, the use of small focus groups was intended to encourage students
to feel comfortable while talking and to decrease possible interviewer effects,
exaggeration or deceit (Bogdan & Biklen, 1992). Each group of students was
selected from the same classroom so that they might feel more comfortable
when sharing information among each other. Interviews lasted between 30 to 35
minutes.

The interview protocol included open-ended questions on multimedia use
(See Appendix D). Students were asked when they first used a computer. They
were also queried about what type of multimedia activities they typically engaged

in. Interviews questioned who within students’ social support networks fostered

40

their engagement with multimedia. Various opinions on multimedia use were
also collected as part of the interview.

The data analysis proceeded according to Leininger’s (1995) four phases
of analysis for qualitative data. During phase one, the interview data were
described and documented. The second phase consisted of the identification of
descriptions in relation to students’ activities with multimedia at school and home.
The third phase included formulation of themes and an analysis of the context in
which they occurred. In the final phase, the reduction of raw data was clustered
around the major quantitative constructs, which included: early adoption of
multimedia technology, social support networks for multimedia use, access to
multimedia technology, time spent on multimedia activities and multimedia
confidence.

Research Questions and Hypotheses

The development of these constructs and measures were key to explore
social and contextual influences on multimedia use and multimedia confidence.
The quantitative and qualitative methodologies were used to examine five
research questions as part of this study.

Questions One: Does the time spent by students on multimedia tasks

influence their confidence with multimedia?

Question Two: How do social support networks influence variations in

patterns of computer multimedia use among students?

Question Three: What is the relationship between access to multimedia

technology and confidence with multimedia for students?

41

Question Four: What environmental factors impact students’ confidence

with multimedia?

Question Five: Does early adoption of multimedia increase students’ level of

confidence with multimedia technology?

Questions Six: Does early adoption of multimedia technology, social

support networks for multimedia use, access to multimedia technology, time

spent on multimedia activities predict multimedia confidence among
students?

In order to answer these research questions, six corresponding hypotheses
were explored through the data analyses. It was expected that the multimedia
confidence of students was influenced by all of the key constructs that included:
early adoption of multimedia technology, social support networks for multimedia
use, access to multimedia technology, and time spent on multimedia activities.

Hypothesis One: Students who spend more time on multimedia tasks
will have higher confidence levels on multimedia.

Hypothesis Two: Students with larger social support networks will have
increased confidence levels with multimedia.

Hypothesis Three: Those students who adopt multimedia technology at
an earlier age will have higher confidence levels.

Hypothesis Four: Students who have more physical access to

multimedia technology will have higher confidence levels with multimedia.

42

Hypothesis Five: Students who spend more time using multimedia tools
for educational purposes will spend less time using it for entertainment
purposes.

Hypothesis Six: Those students who adopt to multimedia use at an
earlier age, have larger social support networks that encourage
multimedia use, have more physical access to multimedia technologies,
and spend more time on multimedia activities, also have higher

confidence levels with multimedia technology.

43

CHAPTER IV
QUANTITATIVE RESULTS

The methodology developed for this study combined both quantitative
procedures for identifying trends. Preliminary analyses included the validity of
responses to the items; examination of missing data; characteristics of the
sample; descriptive analyses; reliability measures; analyses of gender
differences that might account for differences on the key study variables; and
relationships between variables to address hypotheses outlined in the previous
chapter. Finally, additional exploratory analyses investigated the relationship
between the main dependent construct variable of multimedia confidence and the
independent variables: early adoption of multimedia technology, social support
networks for multimedia use, access to multimedia technology, and time spent on
multimedia activities.

Participants. The final sample included 124 respondents consisting of a
distribution of females (n = 83, 67%) and males (n = 41, 33%) across grades
sixth to eighth. Respondents participated according to the policies and
guidelines of the University Committee on Research Involving Human Subjects at
Michigan State University.

Descriptive Analyses. Background differences on key study variables
were inspected by examining means, medians, standard deviations, and ranges.

Reliability of Measures. lntemal consistency coefficients for existing
measures and newly formed constructs were computed. It was critical that the

measures used in this study were internally consistent.

Major Constructs

The surveys used in this study were designed to measure five main
constructs. The construct of confidence with multimedia was seen as the
dependent measure of interest. The other four constructs were examined as
possible predictors of students’ confidence level: confidence with multimedia,
time spent on multimedia activities, social support networks, and early adoption
of multimedia technology. In this section, each major construct is described,
descriptive statistics on the items within each construct are reported , and the
reliability of each construct is considered.

A. Multimedia Confidence Construct. This construct is a combined
measure of students’ reported confidence level on various multimedia tasks,
such as surfing the lntemet or designing a webpage. Students indicated their
confidence level on 5-point Likert scales, ranging from strongly disagree to
strongly agree for 11 items. The mean and standard deviation for each of the
items is shown in Table 4.1.

The mean confidence levels varied considerably by type of multimedia
use. This suggested that students were thoughtfully responding to the questions.
For example, the students rated their confidence highest with “surfing” the
lntemet and using Microsoft PowerPoint (mean = 4.5). Both of these activities
are relatively simple for computer users and widely used. By comparison, the
students rated their confidence level on more complex tasks such as using
Microsoft Excel or publishing to the lntemet much lower (mean = 2.8). This

pattern of variation provided evidence of the validity of the measures.

45

Reliability of Multimedia Confidence Construct. The reliability and
internal consistency of the multimedia confidence construct was developed in two
steps. First, a correlation matrix was computed for all items on the original scale.
An inspection of the matrix revealed that the items showed generally positive
correlations, supporting the view that these items were measuring an underlying
construct that applies to the domain of multimedia tools (See Table 4.2
Correlation Matrix of Students’ Confidence Level with Multimedia).

An interesting exception was that confidence with Microsoft Excel was
negatively correlated with other items. Perhaps middle school urban students
had less experience with Microsoft Excel or lower performance in mathematic
activities for which Microsoft Excel is often used. For the purposes of this study,
these negative correlations suggested that the item about Microsoft Excel should
be left out of the major constructs and final analyses.

The remaining 10 items were summed together to form the “confidence
with multimedia” construct. SPSS reliability procedures were conducted on these
10 items, yielding a Cronbach alpha coefficient for reliability of .74, which is
considered fairly strong.

8. Time Spent on Multimedia Activities. This construct was a combined
measure of students’ reported time spent on various multimedia activities such
as watching television or surfing the lntemet. Students indicated the number of
hours they spent per week for each activity, ranging from 0-12 or more hours.

The mean and standard deviation for each of these items is shown in Table 4.3.

46

Table 4.1 Mean and SD. for Students' Confidence in Their Abilities by

Multimedia Activities

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Overall Confidence Mean S. D.

General computer use 4.1 .91
Computer knowledge 4.0 1.21
Confidence Using the Internet Mean SD.
Surfing the lntemet 4.5 .92

Instant messaging 4.1 1.44

Internet use for homework 3.7 1.32
Publishing to the lntemet (HTML Editor) 2.8 1.51
Confidence with Computer Software Mean SD.
Microsoft PowerPoint 4.5 1.32

Video editing software 3.2 1.66
Concept map 3.0 1.54

Microsoft Excel 2.8 1.52

Copying compact discs (005) 2.8 1.55

 

 

 

 

 

47

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When examining the actual number of hours students spent on multimedia,
there was wide variation (See Table 4.3 Mean and SD. for Time Spent on
Multimedia Activities). Students reported spending several hours per week
engaging in multimedia activities. Most of their time was spent on Internet
related activities such as games (mean = 3.0), email (responding to email, mean
= 2.4 hours; sending email, mean = 2.0 hours) and instant messaging (mean =
2.5 hours). Data also indicated that most students reported a minimum of 8-12
hours per week watching television (mean = 8.0 hours). After watching
television, students spent the next most significant amount of time using a phone
either by talking on their home telephone (mean = 4.00 hours), talking on their
mobile phone (mean = 1.3 hours), or instant messaging on their mobile phone
(mean = .70 hour).

Reliability of Time Spent on Multimedia Activities Construct. The
reliability and internal consistency of the time spent on multimedia construct was
examined in two steps. First, a correlation matrix was compiled for all 16 items
on the original scale. An inspection of the matrix revealed that the items showed
generally positive correlations, supporting the view that these items measured an
underlying construct that applied to the domain of multimedia tools (See Table

4.4 - Correlation Matrix for Time Students Spend on Multimedia Activities).

49

Table 4.3 Mean and SD. for Time Spent on Multimedia Activities

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Actlvlty Mean Number of Hours S.D.
lntemet
Sending email
2.00 3.26
Responding to email
2.40 3.53
Instant messaging
2.50 3.72
lntemet messaging for
homework .70 2.1 1
Text messaging
.62 1.82
Blogging
.73 2.00
lntemet periodicals
1.89 2.66
lntemet games
3.00 3.6
Computer software
Word Processing
2.60 3.30
Educational software
.90 1.90
Entertainment/Games
Wdeo games
3.0 3.54
Computer video games
1.92 3.20
Television
8.00 4.00
Phone
Home Phone
4.00 4.00
Mobile phone- general use
1.30 1.87
Mobile phone- intemet
messaging .70 1 .82

 

 

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The 16 items were summed together to form the “time spent on
multimedia” construct. SPSS reliability procedures were run on these 16 items
and the construct had good reliability (Cronbach’s alpha =. 83). As anticipated,
on average most students spent more time on entertainment related multimedia
activities than school related activities. Interestingly, 45 % respondents reported
that they did not spend any time on school related multimedia activities.

C. Social Support Networks for Multimedia Activities Construct. This
construct is a combined measure of the number of people students cited as
influencing their use of multimedia. Students indicated their choices from a list of
ten people including academic and parental figures. The mean and standard
deviation for each of these items is shown in Table 4.5. Social support networks
are viewed as playing an important part in multimedia use (Rice, Grant, Schmidt
& Torbin 1990).

Findings indicated a median of three individualswho served as a part of
the social support network for students’ multimedia use. About 25% of the
students reported 1 person or less in their social support network. A small
percentage (4%) of students indicated a large social support network with 6 of
more persons. Students are typically part of two types of social support
networks: school and home. Teachers represented the highest percentage of
those who supported a student’s multimedia use in school. Additionally, students
identified mothers (mean =. 52), peers (mean = .50) and fathers (mean =. 42) as
social supports at home. Other influences such as grandparents, mentors or

school counselors had low rates of influence on multimedia use.

52

Table 4.5 Mean and SD. for Social Support Network for Multimedia Use

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Mean SD.
School/Peers
Teacher .78 .41
Mentor .52 .50
School counselor .10 .30
Youth peer counselor .02 .13
Friend .48 .50
Family

Mother .52 .50
Father .42 .50
Sibflg .22 .43
Grandmother .14 .34
Grandfather .09 .30

 

Reliability of Social Support Networks for Multimedia Activities
Construct. The reliability and lntemal consistency of the social support networks
was developed in two steps. First, a correlation matrix was compiled for all 10
items on the original scale. An inspection of the matrix revealed that the items
showed generally positive correlations, supporting the view that these items are
measuring an underlying construct that applies to the domain of multimedia tools
(See Table 4.6. Correlation Matrix of Persons as Part of Students’ Social
Support Networks).

The social support network construct included two sub-constructs of
school and home relationships that influence students’ use of multimedia. Home
influences consisted of the seven people in the students’ home environment.
School influences consisted of three variables related to school personnel who

provided social support.

53

 

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The 10 items on the social support network were summed together to form
the “social support" construct. SPSS reliability procedures were conducted on
these 10 items, yielding a Cronbach alpha coefficient for reliability of .83, which is
fairly strong.

In addition to their social support to engage in multimedia use, students
reported their social interactions with other users on the lntemet via chat rooms.
Most students (67%) did not report any interactions with other users using chat
rooms. However, it is potentially a cause for concern that a few students (3%)
reported meeting 20 or more people in chat rooms. The related data on these
items was considered exploratory and had good reliability (Cronbach’s alpha =
.68), but were not included as a major construct.

D. Multimedia Access Construct. Multimedia access has been linked to
disparities in multimedia use (Kvasny, 2002). This construct is a combined
measure of students’ reported physical access to multimedia tools. Students
reported their physical access to multimedia from a list of sixteen items such as
mobile phones and computers. The mean and standard deviation for each of the
items is shown in Table 4.7.

Students had remarkably high levels of access to multiple forms of
multimedia. This is worth noting because urban students are often characterized
as lacking availability to new entertainment/receptive and school/productive
technologies. However, a majority of the students reported access not only to
television and home phones, but recent technologies such as video game

players (mean = .86) and digital video disc (DVD) player (mean = .78). A

55

majority of students had a mobile phone (mean = .73). School related/productive
multimedia was highest for desktop computers (mean = .88) and computer
printers (mean =. 75). Students also had access to digital cameras (mean = .49)
and laptop computers (mean = .36).

Reliability of Multimedia Access Construct. The reliability and internal
consistency of multimedia access was examined in two steps. First, a correlation
matrix was compiled for all items on the original scale (See Table 4.8 Correlation
of Students’ Access to various Multimedia Access). An inspection of the matrix
revealed that the items showed generally positive correlations, supporting the
view that these items were measuring an underlying construct that applies to the
domain of multimedia tools. The 16 items were summed together for the
multimedia access construct. SPSS reliability procedures were conducted on
these 16 items, yielding a Cronbach alpha coefficient with good reliability of .83.

E. Early Adoption of Multimedia Construct. Early adoption of
multimedia activities determined by age of first use is shown in Table 4.9. Age
four was the average age that students reported using a computer for the first
time, confirming the view that they are part of a generation that has grown up
with computers. Students were older, at an average age of eight, when they
reported their first time for Internet use. As age increased, the types and levels
of sophistication of lntemet use also increased. For example, most of the
respondents began to surf the lntemet at age 8, advanced to email use at age 9,
and began to use instant messaging at age 10. Further analyses using

descriptive statistics showed a rather wide distribution. A few respondents (8%)

56

Table 4.7 Mean and SD. for Students’ Access to Various Multimedia

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Multimedia 'Lype Mean SD.
Entertainment/Receptive
Television .90 .30
Sound system .83 .38
Compact Disc (CED player .78 .41
Digital Video Disc (DVD)player .78 .41
Digital Video Disc (DVD) .25 .43
Recorder
MP3 mayer .26 .44
Video game player .86 .35
Home phone .86 .35
Mobile phone .73 .45
School/Productive
Desktop computer .88 .33
Laptop computer .36 .48
Digital camera .49 .50
Printer .75 .45
Personal Digital Assistant .15 .36

 

57

 

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Table 4.9 Mean and 3.0. For Adoption of Students’ Multimedia

 

 

 

 

 

 

 

 

 

 

 

Age of First Use Mean 8. D.
Computer
School Computer 7.1 2.30
Home Computer 6.2 3.37
Internet Mean SD.
Surfing the Internet 8.1 2.2
Email 9.5 2.23
Instant Messaging 10.3 2.34
Computer Software Mean SD.
Software of Any Type 7.5 2.70
Word Processing 8.2 2.21

 

 

 

 

 

reported instant messaging as early as age 6. Respondents were considered
“early adopters” because they engaged in multimedia activities earlier than would
be expected in comparison to their peers. The seven items for the early adoption
scale had good reliability (Cronbach’s alpha = .80). The mean age for adoption of
all multimedia activities was seven years old.

Reliability of Early Adoption Construct. The reliability and internal
consistency of the multimedia confidence construct was examined in two steps.
First, a correlation matrix was compiled for all items on the original scale (See
Table 4.10 Correlation Matrix of Age of Adoption of Multimedia). An inspection of

the matrix revealed that the items showed generally positive correlations,

59

supporting the view that these items were measuring an underlying construct that
applies to the domain of multimedia tools.

The 7 items were added together for the age of adoption a construct “early
adoption”. SPSS reliability procedures were run on these 7 items, yielding a

Cronbach alpha coefficient of .80, which is considered good reliability.

60

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Relationship of Major Constructs

Overall the major constructs that were examined showed strong reliability
and indicated a range in students’ experience of multimedia. The multiple forms
of multimedia and the early age that students’ engaged in multimedia was a
surprising finding. These constructs also indicated the role of both family and
school contexts for successful multimedia access and use. Students spent a
significant amount of time engaged in multimedia for both entertainment and
school purposes. These constructs proved to be significant factors for
multimedia use and will be used in the next section to predict confidence level
with multimedia.

Main Hypotheses

Hypothesis Testing (1 -5): Correlations among Measures

To test the key hypothesis about the relationship between confidence level
and social and environmental factors, several correlations were computed.
Individual constructs and the final model were investigated to provide an
understanding of the relationships and interactions that were present among the
key variables.

A level of significance of a = .05 was used as the minimum rejection
level of all statistical analyses. The Statistical Package for the Social Sciences
(SPSS) software version 11.0 was used in all of the statistical data analysis.
Missing data on the subscales were treated as missing with no imputed values.
Gender differences were examined for all main hypotheses. However, no

significant gender differences were noted for any of the correlations.

62

A. Hypothesis one predicted that students who spent more time on
multimedia activities had higher multimedia confidence levels. A correlation of
.31 suggested a moderate relationship that was significant (p < .01 ). The
scatterplot shows that many students spent between 0 and 6 hours and rated
between 3 and 4.5 in their confidence level (See Figure 4.1).

An examination of the hours per week spent on school related multimedia
activities and confidence with school multimedia indicated that there was no
significant correlation between hours per week participants spent on school-
related activities per week and multimedia confidence. Visual inspection of
Figure 4.2 suggested a post-hoc hypothesis that a positive correlation exists

among

63

 

 

 

 

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Figure 4.1 - Multimedia Confidence and Hours Per Week

 

 

 

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Figure 4.2 - Multimedia School Confidence and Time on School Multimedia

64

high level users. An analysis only of those who reported 10 or more hours per
week showed a positive correlation of .22 between confidence levels and time
spent on school related multimedia that was statistically significant (p < .05).

Also explored was the relationship between time spent on school
multimedia and entertainment multimedia. A correlation of .52 indicated a
positive relationship between time using these two types of multimedia that was
significant (p < .01). This result is interesting because one might expect that time
spent on one would take time away from the other. This correlation suggests
that there are high frequency users and low frequency users of multimedia in
general.

An additional correlation examined time spent socializing on the lntemet
and numbers of friends online. There was a moderate correlation at .32 that was
statistically significant (p. < 05). In general students reported having 2 or more
friends online and spending 0-2 hours socializing online (See Figure 4.4). This
finding supports theories on social networks that propose that persons with more
acquaintances online typically spend more time online.

B. Hypothesis two predicted that students with more social support from
home and school would have higher confidence levels with multimedia. A
correlation of .31 was positive in direction, but not statistically significant. Figure

4.5 displays the findings.

65

Time on School Multimedia

Figure 4.3 - Time on School and Time on Entertainment Multimedia

 

 

 

 

60

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Figure 4.4 - Friends Online and Time Spent Online

66

Also explored was the relationship between school social support
networks and confidence with school-related multimedia. A correlation of .15
suggested a small correlation that was not significant. Figure 4.6. displays a
scatterplot of these findings.

C. Hypothesis three predicted that students who have more access to
multimedia have higher confidence levels with multimedia. A correlation of .19
suggested a small correlation that was statistically significant (p <. 05). A
scatterplot displays the findings in Figure 4.7.

The relationship between multimedia access to school related multimedia
and time spent on school related multimedia was explored (See Figure 4.8).
Several students spend no hours on school multimedia, yet they have higher
levels of multimedia access. Therefore, similar to access to all multimedia and
confidence with school multimedia, there does not appear to be a positive
correlation between access to school multimedia and time spent on school
multimedia. A correlation of .05 indicates a small relationship that was not
statistically significant.

D. Hypothesis four predicted that early adoption of multimedia results in
higher confidence levels. A correlation of -.22 indicated a small negative
correlation that was statistically significant at (p <. 03). A scatterplot displays the
findings in Figure 4.9.

An additional relationship explored was the relationship between school

related technology programs and confidence. A correlation of .33 indicated a

67

 

 

 

 

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Figure 4.5 - Multimedia Confidence and Social Support Networks

 

 

 

 

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Figure 4.6 - School Multimedia Confidence and School Social Supports

68

 

 

 

 

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Figure 4.7 — Multimedia Confidence and Multimedia Access

 

 

 

 

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Figure 4.8 - School Multimedia Access and Time on School Multimedia

69

moderate correlation that was statistically significant at (p < .01). Figure

4.10 displays the findings.

70

 

 

 

 

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Figure 4.9 - Multimedia Confidence and Age of First Use

 

 

 

 

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Figure 4.10 - School Multimedia Confidence and Multimedia Programs

71

Full Model: Confidence levels. A multiple regression model was tested
which examined students’ perceived confidence level with multimedia activities
as predicted by multimedia access, early adoption of multimedia, time spent on
multimedia activities, and social support networks. The full model was developed
in two steps. First, a correlation matrix was computed for all constructs. An
inspection of the matrix revealed that the constructs showed generally positive
correlations (See Table 4.11 Correlation Matrix of Constructs). Next, a univariate
multiple regression was computed using the four predictor variables from the
major constructs and multimedia confidence as the dependent variable.
Students that reported higher multimedia access, adopted multimedia at a later
age relative to their peers, spent more time on multimedia activities and had a
larger social support network, reported higher confidence with multimedia
activities (R2 =. 19, Beta = 3.2, F = 5.9, t=7.65, p< .01).

This multiple regression coefficient shows that the four constructs taken
together provide a stronger prediction of confidence with multimedia than any
single construct, supporting the importance of considering the many sources of
influence on children’s confidence. These findings will be discussed in the final

chapter.

72

Table 4.11 Full Regression Model to Predict Multimedia Confidence
8 SE B t

Predictor Variable

Age of Multimedia Adoption -.04 .04 -.11 -1.10
Physical Access to Multimedia“ .84 .34 .25 2.44
Time Spent on Multimedia Activities* .01 .00 .24 2.63

Social Support Networks for Multimedia .01 .04 .03 .34

df=4, R2: .19,F=5.88**

*Significance at p< .05, “Significance at p<. 001

73

CHAPTER V
QUALITATIVE RESULTS

“It is not a matter of starting from certain theoretical or

methodological problems: it is a matter of starting from what we

want to do, and then seeing which methods and theories will best

help us achieve these ends “ (Eagleton, 1996, p. 183).

Throughout the year, students participated in several major activities that
required them to use hardware such as computers, video camcorders and, digital
cameras, and software such as Apple imovie and Adobe Photoshop. Based
upon their observations, students and teachers were asked to identify students
who showed exceptional performance in using the multimedia tools. Given their
recommendations, ten students were asked to participate in semi-structured
group interviews. These ten students were referred to as the “local experts”.
Their interviews were the source for the qualitative data in this study.

The purpose of this qualitative data was to present a more complete
picture of students’ experience with multimedia by providing further insights into
students’ multimedia technology experiences than could be portrayed by only
quantitative analyses. Their voices and ideas help elucidate the social and
contextual factors that may have contributed to the “local expert’s” development
with multimedia technology.

The interview sessions were viewed not as traditional interviews, rather as
a form of collaborative, interpretive practice, involving respondents and
interviewer as “meaning-makers” rather than “ask, asker and tellers" (Segall,

1983). Because children were interviewed, it was important that the interviewer

did not impose any views or bias on the students. The interviewer’s goal was to

74

become “a listener and tolerator inside of children’s society” (Bogdan 8. Biklen,
1 992, p. 88).

From a preliminary analysis of the qualitative results, it was unclear how
social and contextual factors such as early adoption of multimedia, time spent on
multimedia activities or physical access contributed to students’ confidence with
multimedia technology. However, student responses demonstrated the link
between social support networks from home and school with confidence with
multimedia. For example, six students reported a family member as responsible
for assisting them with multimedia technology activities and seven students cited
teachers as introducing them to new software and hardware. These findings
supported the quantitative data, which showed a positive relationship between
multimedia confidence and social support networks. Students’ use of school
projects to master new concepts emerged as a finding in the qualitative data that
was not apparent from the quantitative data. For example, five out of ten
students reported using software to school projects.

Examples of Parental Influences

The following are excerpts from the interviews selected as examples of
how students cite the influences of family in their use of multimedia.
Pseudonyms are used for all examples.

Brandon, an eighth grader with a red Mohawk style haircut, domineering
presence, and engaging manner, does not reflect the cultural profile of what
many would consider the typical technology nerd. Nonetheless, teachers at the

school relied on his expertise with multimedia technology to assist others and his

75

classmates with school and classroom-related multimedia projects. One of his
classmates noted that, “Brandon can do most anything with software and
hardware problems... he is like an expert”.

When Carrington, an energetic, extroverted seventh grader was asked
about people responsible for his knowledge about computers, he responded with
the following comment: “My mom works as a secretary and uses computers all
the time at work. She is always bringing stuff home for me to work on. She is
always showing me stuff in Word.” He also asserted: “My dad is computer
illiterate. He doesn’t know anything about computers. But my mom use to take
classes at a local community college and that’s why she got DSL, so she could
take her test and stuff without it cutting out with dial up. She surfs the Internet.
She works all day on the computer. She takes some of her work home. She
uses the computer a lot more than I do.”

Quincy, adorned in baggy jeans and an oversized sweatshirt, was
somewhat withdrawn and unapproachable during the early part of our
conversation. He was known throughout the school as someone with strong
multimedia ability and confidence. His friends referred to him as the “kid with mad
skills” in web design. Similar to Carrington, he described a parent as influential
for his multimedia technology ability. When asked about how he came to
understand the principles of good web design, he not only cited a few of the
principles of good web design, but added the following: “My step dad, he teaches
at a community. He teaches web design. So it is kind of a necessity that I use

computers. He {dad} uses a lot of Flash. And he collaborates with a lot of

76

different programs. He designed movies sometimes, new very complicated
expensive programs. Really hard to learn, I’ve tried. He helps me and my sister
all the time.”

Robin an eighth grader with dark brown hair and bright eyes was soft
spoken and had a gentle smile. Her responses were so quiet that it was often
necessary to repeat the questions and to ask her to repeat her answers. The
other students noted her artistic creativity with software such as Adobe
Photoshop and Macromedia Dreamweaver. She credited her mother as a source
of inspiration for creatively using computers. Robin stated: “She {mother} knows
how to use it okay. She urn, works for ---, which is an advertising agency, and
they do certain stuff there. Make stuff for commercials and billboards.” She
continued: “Me and my mom were going to make a website that was just like
selling T-shirts. We were just going to go to my dad’s shop and make them. It
was going to be like I --.com. Just like make a bunch of I Heart T-shirts and
saddle bags. We think that would be kinda cool.” ’

Derrick was tall, with broad shoulders and wore his hair in braids. He was
a seventh grader who was similar to Carrington in stature and size. He pointed
to his mother with influencing his use of multimedia technology: “She {mother}
doesn’t use it that much, but I watch her do a few things on it. She emails people
and things cause she has a lot of long distant friends cause she travels a lot to
Europe and things. And she pays bills over the lntemet. And she uses Quicken
just to keep track of her checkbook and things. That is about all she uses it for.”

Derrick’s discussion of his mother's use of email to communicate with friends

77

supported social network theories, which posit expanded social networks as an
explanation for lntemet use.
Examples of Sibling Influences

While the previous discussions linked students to parents in the home, the
following respondents credited a brother or a sister for aiding in their multimedia
use. For example, Lorne, grade seven, asserted: “Me and my brother were
talking about how cool it was and then I got bored one day and after my friend
came went home and my brother said okay let’s figure out how to do this. So first
we sat there for a couple of hours trying to figure out how to do it. Then we
started figuring out a few things and thought, ok this is awesome. So, we were
up all night just making animations.”

Omandre, a seventh grader, indirectly credited his brother as influencing
his multimedia use. He asserted: “He {his brother} always liked that. When he
went into college, he had more of a business mindset and computer science. He
always talked about computers to me.“ He followed up with: “I plan most likely to
do computers, cause I’d like to start a couple, of if not at least one, business of .
my own. But even if I don’t know that skill, it will always come in handy no matter
what you do ...it is always business in trying to market whatever you do to the
public. So, whether I do or don’t go into that, computers, it will benefit me
anyway because I can work with my brother.”

Examples of Teacher Influences Via Projects
In addition to home influences, school influences were another major

construct linked to students’ multimedia use. Five out of the ten students

78

reported an experience with a project or with a teacher as instrumental in their
multimedia use. The following were respondents” reflection of school influences.

Marcel, sixth grade, was somewhat soft spoken when he first began to
talk about the nature of his use with multimedia. However, over time he began to
open up more and to discuss his multimedia experiences. Marcel was the one
student who clearly pointed to a school project as the impetus for sparking his
interest. He asserted: “Last year I was working on a project...l learned how to do
some Photoshop. Our final project was to make like a picture but you were
suppose to add your own things to it. So since I like graffiti, I made like my own
graffiti thing. I got images of bricks and layered it and made it one big page. I
took graffiti from the Internet and posted it on and made it look to the point like it
was actually graffiti on the wall. I used different type of filters from the program to
make it look like that.”

Similar to Marcel, both Dustin and Lorne mentioned their experiences with
a school project. Marcel described: “Um, we just made a film because Ms. ---
had us do it for a project. Okay, sounds cool. We get to do something funny. So
we just decided that we wanted to make a Kung F u movie. We just said, “What
should we make? Then all of our cast dropped out so we just decided to take us
two and make our own. And um, we end up entering it into the contest and we
won second place. It was really cool.” Lorne continued: “ I learned it in
Language Arts cause we had to use it for like presentations. We had to make a
movie in 7'" grade. And inside of Social Studies we had to do a report on a

country with that. So we used it a lot. When I was in Art we had to use that to do

79

our cartoons. Cause we went into Photoshop, cause she took a picture of it and
then we drew over the lines and colored it in and we made a cartoon and
recorded our voices. It was fun.”

While some focused their remarks on the projects, others like Helen
(grade 7) and Pamela (grade 7) emphasized the influences of individual
teachers. Helen mentioned her teachers: “Ms. --, Ms. --, and Ms. -- taught me
how to use multimedia. “Cause I had to take computers otherwise I wouldn’t get
my credit.” She further commented: “Yeah, she let us do a lot on our laptops.
Ms. —- taught me how to do a lot and so did Ms. ---. And Ms. -- had us do a lot
of projects on the computer. So did Ms. --- she had us do us work on our math
album was on our laptop.”

Similar to Helen, Pamela also credited a teacher with introducing her to
new multimedia. She shared: “Last year, I did stuff with Ms. ---. We made
movies with Mac’s. Um, well also, we had to do math albums; we had to do a lot
of stuff. Like, I was in Ms. ---’ class, and we had to do digital poetry where we
had to take pictures off of the lntemet. Inside Photoshop, we redrew them, so
that we wouldn’t be copying them.”

Conclusion from Interviews

The interviews provided a deep, rich window on the contexts in which
these middle school students acquired their multimedia skills. Their voices
conveyed how it was not just any father, but a father who teaches web design. It
was not just any mother, but a mother who uses Quicken. Research on home

and school influences of multimedia needs to explore the depth of contextual

80

influences. Findings in this section support research on the importance of project-
based learning in using multimedia. Based upon observations and informal
discussions with teachers and students, many of the “local experts” were
students who were marginal students academically. Comments from teachers
were that these were students who excelled only in their multimedia use.
Teachers would comment that a student was brilliant with multimedia, but is “a
handful in class.” This suggests the potential of multimedia in engaging some
students who are othenrvise disengaged in traditional school academic activities.
Understanding how social support networks at home and at school work together
to support students’ use of multimedia is a complex interactive contextual
process that is necessary to improve multimedia technology use among diverse
student populations.

What was it for Helen when looking over her mother’s shoulder when
surfing the Internet that inspired her to use the Internet for more advanced uses?
Was it Carrington’s observation of his dad hooking up the DSL line? These
qualitative findings have helped present some insight into the social and
contextual factors that influence students’ patterns of multimedia use. It is clear
that understanding these complex sociocultural processes is worthy of further

detailed qualitative and quantitative research.

81

CHAPTER VI
DISCUSSION AND CONCLUSIONS
Major Findings
In this chapter, the findings are discussed in relation to the proposed
hypotheses. Next the implications are discussed. Finally, the future directions for
research are proposed.
Multimedia Confidence and Social and Environmental Factors

Hypothesis One. The first hypothesis examined the relationship between
how students spend their time on various multimedia activities and confidence
levels. Results revealed a small correlation. Similarly, the time spent on
entertainment construct and school-related multimedia construct showed a
moderately correlation with confidence. The school-related multimedia and
entertainment multimedia were not correlated.

The findings are important because they suggest that both entertainment and
school related multimedia use were important in increasing students’ multimedia
confidence levels. Students who spent more time on entertainment related
multimedia activities also spent more time on school related multimedia activities.
These findings can perhaps support the recent work of scholars who are
interested in entertainment video multimedia and its potential adaptation for
learning in classrooms (Gee, 2002).

There have been concerns raised about the amount of time students
spend on non-school activities. With the emergence of video games and online

games, the study was designed to measure their impact on school-related

82

activities with multimedia. The results showed that time spent on entertainment
activities and time spent on school activities were positively correlated. Students
who spent considerable amounts of time on school related activities also spent
similarly higher amounts on entertainment related multimedia. These findings
support the work of researchers such as Mackey (2003) who examined the
amount of time students spend on non-entertainment literacies and
entertainment literacies, only to discover that the two were not positively
correlated or related.

Hypothesis Two. Hypothesis two examined the relationship between
social support networks and confidence levels. There was a small correlation
between social support networks and multimedia confidence. Parents and
teachers were cited the most often as influential for students’ use of multimedia.
The findings are interesting for several reasons. First the small relationship
between the two constructs contradicts the literature, which discusses the
positive relationship between computer and Internet use with social networks
among. Secondly, the small correlations could represent differences in social
networks for children versus adults. Adults are often part of large social networks
that extend beyond their home to places such as their place of employment or
place of worship. Young adults are part of social support networks that are often
limited to home and school. Given the high percentage of respondents who
reported parents and teachers as influential, it speaks to the fact that it is
perhaps more important that they have a single individual at home or in school

who encourages their interest with multimedia.

83

The qualitative findings offer further insight into this discussion. In the
interviews students identified parents or teachers as important in shaping their
experiences with multimedia. Additionally, students appeared to form these
informal groups around multimedia inside and outside of school. They all knew
each other and referred to each other as sort of “local experts”. This finding did
not come out in the quantitative findings. More importantly it supports research
on the importance of peers for adolescents’ social development. Also, it also
provides evidence of how children are able to create their own communities of
practice around multimedia and share ideas about the activities. Additionally,
their interest in multimedia was the impetus for coming together around
multimedia. Many of the students stated that their friendships did not exist
beyond their activities with multimedia.

Hypothesis Three. Hypothesis three explored the relationship between
early adoption of multimedia and confidence levels. Students’ average age of
early adoption was negatively correlated with confidence levels, which suggests
that early adopters have higher confidence levels than late adopters. These
findings support similar findings from Internet studies, which reports higher
efficacy for more experienced users (Brancheau & Wetherbe, 1990). These
findings clearly support the importance of early adoption of new technologies in
order to increase confidence. Therefore, we must continue to find ways to
provide for students to engage in multimedia as early as possible. These
findings also are similar to a national study that examined the adoption patterns

of children and adolescents (Brancheau 8r Wetherbe, 1990). Early adopters

increased confidence levels could be linked to their opportunities to gain
important experience over a longer period of time.

Hypothesis Four. Hypothesis four examined the relationship between
physical access to hardware and confidence levels. Overall physical access was
abundant. This finding reflects the declining costs of physical hardware and the
wide availability. Increased physical access showed no correlation with
multimedia confidence. Additionally, the two sub-constructs related to school
and entertainment showed no correlation. These findings are encouraging
because they suggest that even if there are socioeconomic barriers that affect
physical access, students can still have high confidence levels with multimedia,
which may be essential for their future success.

Hypothesis Five. Hypothesis five examined the confined relationship
between the four constructs time spent, early adoption, access and social
support networks and confidence levels using a multiple regression model. The
combined prediction (R=. 44) was moderately strong and shows the importance
of studying multiple sources of influences.

The model has several implications for considering multimedia use in
schools. F irst, the quantitative data and qualitative data make it clear that
teachers are important for fostering positive uses of multimedia beyond
entertainment. Therefore, more research is needed to explore the specific ways
in which teachers impact various uses of multimedia. Secondly, project-based
learning appears to be one way that teachers’ can engage students with

multimedia in the classroom. Further research is needed to design methods to

85

make problem based Ieaming more effective in introducing students to
productive uses of multimedia.

Thirdly, there have been ongoing discussions over the digital divide as it
relates to physical access to hardware and the Internet. However, this study
supports the need to look beyond physical access and focus efforts on focusing
on patterns of use such as early adoption. Early adoption of new multimedia
provides users more time to learn complex uses. Therefore, we need to develop
programs and to promote policies that provide opportunities for early adoption of
multimedia tools.

Future Research

This study narrowly defined high end users as students who were using
the multimedia tools most closely related to school technologies—computers and
activities such as spreadsheets, publishing, and other software. Scholars such
as Gee (2003) have examined the uses of video games and literacy and critical
thinking. In the future, scholars should build upon a growing body of research
that looks at literacy practices, informal Ieaming spaces and multimedia activities.
Also, rather than looking at four broad constructs, perhaps a more defined
examination of a single construct will provide greater depth of understanding how
one contextual factor impacts patterns of multimedia confidence. For example,
exploring the only the relationship between early adoption and multimedia
confidence could yield interesting information on variations in patterns of use.

Additionally, the qualitative interviews provided some evidence to support

the quantitative findings. However, a longer ethnographic study could provide

86

 

even more insight into the lives of students’ multimedia patters. An interesting
study would be to follow the local experts for a long period of time and collect
field notes on their experiences with multimedia across multiple contexts in home
school and other places.

Conclusions

Recently, after attending a sporting event within the community of the
study, I began to reflect on the social dynamics of the sporting event and its
relationship to the context in which it was played. In attendance at the event
were large numbers of parents, both mothers and fathers. The children
enthusiastically engaged in the sporting event as both participants and
observers. The motivation to succeed was apparent in the enthusiasm that was
expressed physically by the children and verbally by the parents. I asked one of
the children how often they practiced. He responded “four times a week, two
hours a day, and twice a day during first month of the season in the summer”. I
thought, “That is some dedication!”

I began to reflect and imagine a different scenario in which each day,
children within this urban community began attending multimedia workshops for
two hours a day, and four days a week where they practiced individual skills and
worked collaboratively toward a single goal of understanding complex uses of
multimedia. They were involved in a sort of apprenticeship that introduced
multimedia to using multimedia in school and home. At the end of each week,
parents, siblings and friends of parents attended a showcasing of students

products.

87

 

This scenario is linked closely to what I sought to discover within the
dissertation. How do environmental factors influence children uses of
multimedia? Which activities do children choose to embrace while ignoring
others? Who within this community might share the same enthusiasm for
developing expertise with sophisticated multimedia? How can we use that
understanding to help others with move in that direction? These are questions I
wish to pursue in future research to enhance our knowledge of multimedia
technology among diverse students and inform future educational policy and

practice.

88

APPENDICES

89

Appendix A
Parent Consent Form

The purpose of this study is to explore the multimedia activities of middle school
students and understand how those related to educational competencies. I am
interested in understanding how student’s use of various multimedia activities
can influence their education.

Your signature on this form indicates that you have agreed to allow your child to
participate in a 20 minute survey and if selected a 20 minute interview. This
process will be done during school hours. This form outlines your child rights as
a participant.

Participation includes the following:

0 Your child will be voluntarily participating in a doctoral dissertation
research project that will explore their multimedia activities.

0 You or your child can withdraw participation from this survey or interview
at any time. Your child can refuse to answer a question. If your child
withdraws during the survey or interview, their survey or audiotape will be
destroyed.

0 You or your child can ask questions of the surveyor or interviewer at any
time during the process.

. Your child’s identity will be confidential. Pseudonyms (made up names)
will be used in all written papers in order to protect individual identification.

0 You know that the interviews will be audiotaped. All tapes will be
destroyed or erased after the transcription is complete. The researcher
will retain the transcript of the audiotape and will delete any reference,
which may identify your child as an individual. If you would prefer for your
child not to be audiotaped, the interviewer will take written notes during
the interview.

0 You consent to the publication parts of the transcript and accept that any
information will be anonymous in order to prevent any identification.

If you have questions or concerns regarding the study you may contact the
investigator Dr. Patrick Dickson, phone: (517)355-4737, 509E Erickson Hall E.
Lansing, MI 48823, email: pdicksorfimsuedu. You may also contact the
researcher, Ted Hall, phone: (517)355-6041, 1211 H University Village, E.
Lansing, MI 48823, email: halldarr@msu.edu.

90

If you have any questions or concerns regarding your rights as a parent, or are
dissatisfied at any time with any aspect of the study, you may contact,
anonymously, if you wish, Dr.Ashir Kumar, Ph.D., Chair, University Committee on
Research Involving Human Subjects, by phone (517) 355-2180, email:
ucrihs@msu.edu, or regular mail: 202 Olds Hall, East Lansing, MI 48824

Please check the following:

_You voluntarily agree to participate in this study.
_You agree to be audiotaped

Signature of
Parent or Guardian Date

Signature of Interviewer Date

91

Appendix B
Student Consent Form

The purpose of this study is to examine the multimedia activities of middle school
students. I want to understand whether students' multimedia activities have any
relevance to education.

Your signature on this form indicates that you have agreed to participate in a 20
minute survey and if selected a 20 minute interview. This process will be done
during school hours in coordination. This form outlines your rights as an
interview participant.

Participation includes the following:

a You will be voluntarily participating in a doctoral dissertation research
project that will explore your multimedia activities.

0 You can withdraw participation from the survey or interview at any time.
You can refuse to answer any question. If you withdraw during the survey
or interview, your survey or audiotape will be destroyed.

- You can ask questions of the interviewer at any time during the process.

0 Your identity will be confidential. Pseudonyms (made up names) will be
used in all written papers in order to protect individual identification.

0 You know that the interviews will be audio taped. All tapes will be
destroyed or erased after the transcription is complete. The researcher
will retain the transcript of the audiotape and will delete any reference,
which may identify you as an individual. If you would prefer not to be
audio taped, the interviewer will take written notes during the interview.

0 You consent to the publication of parts of the transcript and accept that
any information will be anonymous in order to prevent any identification.

If you have questions or concerns regarding the study you may contact the lead
investigator, Dr. Patrick Dickson, phone: (517)355-4737, 509E Erickson Hall

E. Lansing, MI 48823, email: mickson@msu.edu. You may also contact the lead
researcher, Ted Hall, phone: (517)355-6041, 1211 H University Village, E.
Lansing, MI 48823, email: halldarr@msu.edu.

If you have any questions or concerns regarding your rights as a study

participant, or are dissatisfied at any time with any aspect of the study, you may
contact, anonymously, if you wish, Dr. Ashir Kumar, Ph.D., Chair, University

92

Committee on Research Involving Human Subjects, by phone (517)355-2180,
email: ucrihs@msu.edu, or regular mail: 202 Olds Hall, East Lansing, MI 48824.

Please check the following:

_You voluntarily agree to participate in this study.
_You agree to be audio taped.

Signature of
Participant Date

Signature of Interviewer Date

93

Appendix C

Survey on Multimedia Technology

Section A: Accessing Technology Case #

 

Basic information about how, when, and where you access technology is the
cornerstone of this survey. The purpose of this survey is to examine various
uses of multimedia by middle school students.

Gender: 0 1. Male 0 2. Female

1. Do you have your own computer or computers at home?
(Mark all that apply)
0 1. Yes, desktop 0 2. Yes, laptop 0 3. No

2. Try to Remember: How old you were the first time you used the following
multimedia? (Just make your best guess as to the age. If you really have
no idea, just put a question mark. If you’ve never used it, put ‘0 ’. )

Your:
( ) 1. Age when you first used word processing on a computer

(Word, PowerPoint.)
)2. Age when you first used electronic mail
) 3. Age when you first used the Web

(
(
( )4. Age when you or your family had a computer at home
( )5. Age when you first used a computer in school.

(

)6. Age when you first used instant messaging
( )7. Age when you first used software
3. Who has supported your use of multimedia? (Mark all that apply)
0 1. Father 0 2. Mother 0 3. Grandfather

O 4. Grandmother O 5. Mentor O 6. Teacher
0 7. Youth Counselor 0 8. School Counselor

09. Friend 0 10. Other, please indicate

94

4. Where was the first place you became involved in working with computers?

0 1. Home O 2. School 0 3. Community Center
0 4. Friend’s house 0 5. Relative’s house
0 6. Religious center 0 7. Other

 

5. Where do you most often use a computer?
0 1. Home O 2. School 0 3. Community center
0 4. Friend’s house 0 5. Relative’s house 0 6. Religious center
6. Other, indicate

6. Have you ever been involved in any of the following programs with
technology?

0 1. After school program 0 2. School program
0 3. Community program 0 4. Technology camp
0 5. Other, please indicate—
7. Which of these describes the kind of access you have to the lntemet
from home:
0 1. Dial-in modem
0 2. Cable modem
0 3. DSL
O 4. Do not know
8. Please mark all the following that you have easy access outside of school:
('Easy access' means you can use it pretty much whenever you choose.)
0 A. Desktop computer
0 B. Laptop computer
0 C.CD recorder ("burner") with computer
0 D. DVD recorder (“burner") with computer
0 E. Printer
0 F. Scanner
0 G. Digital camera

95

O H. Cell phone
0 l. Regular Phone

0 J. PDA (personal digital assistant such as a Palm)

K.TV

L. Sound system (speakers, CD player, etc.)

0

O

O M. Portable CD player
0 N. DVD player
0 0. MP3 player
0

P. Video game player (Playstation, Xbox, or Nintendo)

Section B: How You Spend Your Time

In this section, I am interested in how you spend your time. I will use this
information to build a better understanding of how different activities are

influenced by the use of technology.

9. In the last 7 days, how many hours per week did you spend time doing
the following activities? Please circle the closest answer.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Activity Hours Per Week

a. Watching Television 01/21 2 3 4 5 6 7 8 9 10 11 12

b.Talkingon homephone 01/21 2 3 4 5 6 7 8 9 10 11 12

c.Talkingoncellphone 01/21 2 3 4 5 6 7 8 9 10 11 12

d. Usingcell phonetosend 01/21 2 3 4 5 6 7 8 9 10 11 12
text messages more

d.Playingvideogames 01/21 2 3 4 5 6 7 8 9 10 11 12
(Playstation, Xbox, etc.) more

e. Using instant messaging 01/21 2 3 4 5 6 7 8 9 10 11 12
or chat (Yahoo, Aol) more

f. Usingthe lntemetto 01/21 2 3 4 5 6 7 8 9 10 11 12
play games more

g.Usingyourcomputerto 01/21 2 3 4 5 6 7 8 9 10 11 12
play video games more

h. Sending Emails 01/21 2 3 4 5 6 7 8 9 10 11 12
more

i. Receiving Emails 01/21 2 3 4 5 6 7 8 9 10 11 12
more

j. Usingthe lnternetfor 01/21 2 3 4 5 6 7 8 9 10 11 12
school related work more

R. Using instant messaging 01/21 2 3 4 5 6 7 8 9 10 11 12
for school related work more

 

 

96

 

 

 

 

 

 

 

l.Usingthelntemetfor 01/21 2 6 8 9 10 11 12
school related work more

m. Usingthe lntemetto read 01/21 2 6 8 9 10 11 12
an article more

n. Usingthe Intemetto post 01/21 2 6 8 9 10 11 12
a comment on a website more

0. Using thecomputerto 01/21 2 6 8 9 10 11 12
write a paper more

p. Using educational software 01/2 1 2 6 8 9 10 11 12
(Le. math blaster, Oregon more

Trail)

 

 

97

 

Section C: Confidence on Multimedia Tasks

E f.fifl“n| i“77 "J. I .15 . ‘ '1 l: in“ '. '1 JF§.-" ‘3‘ II“. It g‘l"_A — — .- ,
"7r" ‘5-1.‘

Please place a check under the column that best indicates the extent to which you agree with each ems following
statements.

 

 

 

10. To what extent do you agree or disagree with the following statements? Please circle the number
between 1 and 5 best indicates your level of agreement with each statement

 

Strongly Somewhat Neither Somewhat Strongly
Disagree Disagree Agree Agree

 

a.l am very skilled
at using
computers.

 

b.l do not know
much about
using computers.

 

c. I am confident
using the
lntemet to look
up information.

 

d. I am confident
using the lntemet
to do homework.

 

e. I am confident
publishing to the
Internet.

 

f. I am confident
using
PowerPoint.

 

g. I am confident
creating a
spreadsheet.

 

h. I am confident
creating a
concept map.

 

i.l am confident
creating video
editing software.

 

j. I am confident
instant messaging.

 

k. I am confident
downloading
music

 

 

 

 

 

 

 

 

98

 

 

and burn cd’s.

 

 

 

 

 

 

 

11. How many people have you met online that you did not know before
if no one, please skip to question 13, If yes, go to

 

question 12.

12. Of those people you first met online, how many would you consider friends?

 

13. How many of your friends from school do you instant message?

14. With how many of your friends do you share videos, music, or video
15. games?

99

Appendix D
Qualitative Interview Protocol

Hello, My name is Darryl Hall. I am a graduate student at Michigan State
University. I am interested in Ieaming more about your experiences with
multimedia. The reason I am examining multimedia activities is to
understand how students use it and to see whether they use it for
educational purposes. I am going to ask you some questions to get a

more complete story of your experiences with multimedia activities. Do you
have any questions?

As a researcher, l have a responsibility to keep whatever you tell me

confidential. Confidential means that your name will not appear on any

transcript-I will code this meeting as a number only. I have an obligation

to destroy all tape recordings after transcribing them. At anytime you
may choose not to answer any question.

Again, do you have any questions before we begin?

1. Can you tell me a story about the first time you used a computer?

1a. How old were you then, tell me a little more about that
expenence?

2. What activities do you and your friends like to do most with computers?

2a. Who started those activities, you, a friend, or family member?

2b. What about educational activities with multimedia?

100

3. When you think about computer activities such as, im chat, email, search
engines, and software, do you see any value in their use for educational
purposes?

3a.Why do you see it that way?

4. Why do you think some students use computers more than others?

5. Do you believe in the importance of using computers for school related
work?

6. Have computers helped you become a better student? If so, how?

101

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