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THE DIFFERENTIAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON THE CLASSROOM MANAGEMENT BEHAVIORS OF SELECTED ELEMENTARY TEACHERS by Robert George Knapp A DISSERTATION Submitted to Michigan State University in partial fuifiilment of the requirements for the degree of DOCTOR OF PHILOSOPHY Division of Student Teaching and Professional Deveiopment I981 Copyright by ROBERT GEORGE KNAPP I981 ABSTRACT THE DIFFERENTIAL EFFECTS OF SELF MONITORING AND LOCUS OF CONTROL ON THE CLASSROOM MANAGEMENT BEHAVIORS OF SELECTED ELEMENTARY TEACHERS By Robert George Knapp The research of Jacob Kounin (T977) has deiineated severaT cate- gories of management behavior that contribute to an effective cTass- room miTieu. This investigation assumed that in order to effectiveTy exhibit these management behaviors, teachers must be sensitive to situationai and interpersonaT cues in the cTassroom sociaT context. Thus, the major purpose of this study was to examine the reTationship between sensitivity to situationaT cues, as measured by the SeTf— Monitoring ScaTe deveioped by Mark Snyder (1972), and the cTassroom management behaviors of teachers. A secondary purpose was to examine certain theoreticaT conjec- tures suggested by the seTf-monitoring construct. As a resuTt, two additionaT presage measures were considered: The CTassroom SeTf— Monitoring ScaTe, designed to measure the seTf-monitoring construct in the specific sociaT context of the cTassroom; and Tocus of controT (Rotter, T966), which was used to test the purported abiTity of seTf- monitoring to function as a moderating variabTe. CTassroom observations of nine eTementary schooT teachers pro- vided four measures of cTassroom management behaviors: withitness, Robert George Knapp overlapping, momentum, and smoothness. Each criterion score was based on four observations. Correlational analyses provided measures of the strength of relations among the three presage variables: self- monitoring, and locus of control, and the four management measures. In general, the results failed to provide clear evidence of the hypothesized relation between self-monitoring and classroom management behaviors. They also failed to support the purported ability of self- monitoring to function as a moderating variable. However, there is at least some indication that future research with a more narrowly de- fined contextual focus and a larger sample may provide more definitive evidence of these relations. Finally, the failure of the Classroom Self-Monitoring Scale to yield more precise predictions of classroom management behaviors than the Self-Monitoring Scale was the most con- vincing finding of the study. It suggests that Snyder's scale is not situation specific and is probably generalizable to a wide range of social contexts. ——————__m2w DEDICATION To my wife Linda. Thank you for the love and support that made this all possible. ACKNOWLEDGEMENTS The completion of this dissertation represents the collective efforts of many people. Without the support and encouragement of the following individuals, this project would never have been completed. 1 would like to express my appreciation to Don Freeman who pro— vided countless hours of his time in assisting me to design the study, analyze the data, and clearly express myself in the final document. His constant support and gentle criticism kept the final goal always in focus. To my committee: Jan Alleman-Brooks, who was the first to en- courage me to enter a doctoral program; Joe Byers, who suggested read- ings which led to my identification of the self-monitoring construct: Arden Moon, who chaired my committee; and, of course, Don Freeman. To Jan Shroyer, who willingly shared her library of videotapes which made observer training so effective. A special thanks to the teachers who allowed me to intrude upon their classrooms. Their open- ness renews my faith in the basic good that classroom teachers have to offer their charges. To Linda, my wife, whose moral support carried me through those times when everything seemed black. Her willingness to share the burdens of this dissertation will always be appreciated. To my family who never questioned my decision to give up the security of a job and return to school. Thanks for helping me to fulfill a dream. To a very special group of people--Camp Runamuck. We were thrown together and became great friends. To Lynda, Fran, Shirley, Sue, Gene, Pat, Becky, Terry, Arly, and honorary camper Thom. We will always be friends; thank you. TABLE OF CONTENTS Chapter I: II: III: IV: IHE PROBLEM . A Model for Research on Teaching . Teacher Personality: A Presage Variable The Classroom as a Self— Monitoring Environment Need . . . . Purpose . Research Questions Hypotheses Overview REVIEW OF THE LITERATURE . Overview . Part 1: The Classroom as a Social System . Part II. The Classroom Management Research of Jacob. Kounin . . . Part III: Self— Monitoring and Locus of Control . Chapter Sunmary . . . . . . . METHODOLOGY . An Overview . Phase I . . Phase II . . Instrumentation/Reliability . Observer lraining . Data Collection . Summary . ANALYSIS OF RESULTS Correlational Analysis Multiple Regression Analyses Group Analyses . Summary . V: DISCUSSION AND IMPLICATIONS . . . . . . . . . . . . . . . 92 Summary: Design of the Study . . . . . . . . . . . . . . 92 Discussion of the Findings . . . . . . . . . . . . . . . 95 Implications for Research . . . . . . . . . . . . . . . . lOO Concluding Statement . . . . . . . . . . . . . . . . . . lO6 Reference Notes . . . . . . . . . . . . . . . . . . . . . l08 Appendix A . . . . . . . . . . . . . . . . . . . . . . . . . l09 Appendix B . . . . . . . . . . . . . . . . . . . . . . . . . ll2 Appendix C . . . . . . . . . . . . . . . . . . . . . . . . . ll8 U Appendix l20 m Appendix l23 -n Appendix l26 Appendix G . . . . . . . . . . . . . . . . . . . . . . . . . l29 Appendix H . . . . . . . . . . . . . . . . . . . . . . . . . l34 Appendix I . . . . . . . . . . . . . . . . . . . . . . . . . l36 References . . . . . . . . . . . . . . . . . . . . . . . . . l37 vi LIST OF TABLES Table l. 2. Mean Differences in Test Taking Order . Demographic Characteristics of the Research Sample lest Reliabilities and Interscale Correlations Classroom Management Observation System Inter- Rater Reliabilities (N_= 9) Correlations Between Presage Variables and Class- room Management Measures (N_= 9) . . Intercorrelations among Classroom Management Measures (N_= 9) . . . . . . ..... Self-Monitoring Group Means (N_= 9) . Self-Monitoring/Locus of Control Group Means (N_= 9) vii 6b 74 8O 84 86 LIST OF FIGURES Figure 1. IO. ll. Overview of critical variables in Dunkin and Biddle's model for research on teaching . Critical variables in the research design . Relations that serve as the primary focus of this investigation . Interaction of the nomothetic and idiographic di- mentions of the social system Self-monitoring x locus of control subgroupings . Observation Schedule Graphic representation of the relationship between presage and criterion variables Self-monitoring by locus of control subgroupings Graphic representation of self-monitoring/locus of control groups and criterion variables . Criterion variables in the research design Self-monitoring by locus of control subgroupings viii Table 13 23 26 48 68 76-78 85 88 93 99 --‘_ CHAPTER I THE PROBLEM Getzels and Thelen (l960)describe the classroom as a working group containing individuals with certain personalities and need dis- positions. They assert that the classroom can be best understood by studying the interaction between internally defined personalities and needs (the idiographic dimension) and externally defined roles and ex- pectations (the nomothetic dimension). They contend that teacher be- havior is a function of the institutional role defined by the expecta— tions attached to it and the personality of the particular role incum- bent as defined by his need dispositions. The interaction of the idiographic and nomothetic dimensions of the classroom is the focal point of this investigation. The complexity of classroom interaction makes it a difficult area to research. One aid in conducting research in the classroom has been the development of research mnodels. Models are used to conceptua- lize, study, and interpret the classroom. A generally accepted model for the study of classroom teaching is presented by Dunkin and Biddle (l974). Their model seems especially well suited for discussing the theory, need, purpose, and research questions which underlie this in- vestigation. A Model for Research on Teaching Model building is made possible by the nature of the classroom. Classrooms are surprisingly invariant across different geographic lo- cations. Classrooms in Florida, Nebraska, and Alaska are much more alike than different. Physical similarities are obvious. Desks, chalkboards, and the manner in which they are arranged differ only slightly among classrooms. Classrooms are also alike in the general pattern of human interactions they exhibit. In most classrooms stu- dents raise their hands and are called upon by teachers, and student movement is regulated by the ringing of bells. Classrooms have also remained remarkably invariant over time. Despite many calls for basic changes in classroom structure and routine, they have changed little. In all likelihood, the classroom of the l980's will not be radically different from the classroom of the l970's. These stable characteris- tics of classrooms make it possible for researchers such as Dunkin and Biddle to develop models of classroom teaching. Dunkin and Biddle's model for the study of classroom teaching (see Figure l) contains four sets of variables: presage, process, context, and product variables. The arrows in the model represent causal assumptions. Presage Variables The model assumes that teacher behavior is primarily a function of presage variables. Presage variables concern the characteristics of teachers which affect the teaching process. They may be further divided into three general subcategories: teacher formative experi- ences, teacher training experiences, and teacher properties. The Presage Variables\\\\‘\\\\\\t; Process > Product Context ///’//,,,//9? Variables Variables Figure l. Overview of the critical variables in Dunkin and Biddle's model for the study of classroom teaching. (Adapted from Dunkin and Biddle, 1974, p. 38.) teacher property category which includes personality traits is of par- ticular interest in this research. Process Variables Process variables are at the heart of the model. They concern the actual activities of teaching. Process variables are studied by observing teacher behavior, student behavior, the interaction of teachers and students, and the resultant changes in behavior. The importance of the teacher's role in the classroom is emphasized. It is assumed that the reSponsibility for teaching success is in the hands of the teacher and that changes in pupil behavior are evidence of success or failure of the teaching act. A process variable, teacher classroom management behavior, is a central focus of this investigation. Context Variables Context variables concern the conditions to which the teacher must adjust. In this study, context variables serve to limit the scope of the investigation. Only elementary, self-contained, urban classrooms are involved in the research sample. Product Variables Product variables concern the outcomes of teaching-—those changes that come about in pupils as a result of their in- ;olzgment in classroom activities (Dunkin and Biddle, l974, Dunkin and Biddle consider product variables to be the necessary mea- sure of teaching success, but others (e.g., Jackson, Note l) consider observable behaviors of pupils as the most suitable variables to assess when measuring the products of education. Although the present research project does not involve product variables, previous research has linked classroom management beha- viors of teachers with productive student behaviors (Kounin, l977) and attitudinal and learning outcomes (Anderson, Evertson, and Brophy, Note 2; Brophy and Putnam, Note 3). It is therefore reasonable to conclude that if a link can be demonstrated between presage and pro- cess variables, evidence will also be provided for the larger causal chain between presage, process, and product variables as suggested by the Dunkin and Biddle model. Teacher Personality: A Presage Variable A central assumption of the Dunkin and Biddle model is that teacher behaviors are primarily a function of presage variables. Biddle (l964) defines the presage variable-personality traits as fol- lows: Hypothetical constructs in psycholOQy, thus they are as- sumed to characterize the individual teacher in a consis— tent fashion, over time, and serve to explain her behavior in response to a variety of situations. It is also pre- sumed that such properties are laid ”within” the teacher and are not amenable to direct observation in the same way that behavior can be observed. Contemporary American ide- ology (also) stresses the alterability of teacher proper- ties (pp. 9-lO). The Failure of Traditional Personality Assessment Attempts to define personality traits which predict individual behaviors across situations have been disappointing. Following a thorough review of research in this area, Walter Mischel (1968) con- cludes that a +.3O ceiling exists on correlation coefficients between personality measures and cross-situational behaviors of individuals. In his view, this constitutes a fundamental conceptual challenge to the usefulness of the concept of personality itself. Daryl Bem and Andrea Allen (1974) address this challenge by con— tending that the classification of situations must be an integral part of any assessment procedure . . . (and that any) such classi- fication will have to be in terms of the individual's own phenomenology, not the investigator's (p. 518). Self-Monitoring The argument that personality assessment must attend to the indi- vidual's phenomenological view of different situations has prompted the conceptualization of new social-psychological constructs. One of these, self-monitoring (Snyder, 1974), serves as a critical variable in this investigation. This, and other similar constructs stemming from Bem and Allen‘s analysis, may be a promising way to examine pre— sage variables in the Dunkin and Biddle model. Self-monitoring theory assumes that social interaction requires the ability to manage or con- trol our verbal and nonverbal self—presentation to foster gesgggd images in the eyes of our beholders (Snyder, 1979, Two sources of information are available to guide social behavior ap— propriate to particular contexts. First, the cues contained in the social situation which define situational or interpersonal specifica— tions of appropriateness (the idiographic dimension) and, second, per- ceptions of one's own inner states, personal dispositions, and social attitudes (the idiographic dimension). The self-monitoring construct suggests that individuals differ in the extent to which they characteristically rely on either source of information. High self-monitors rely on situational cues for con— struction of their self-presentation; low self-monitors rely on inter- nal states. Mark Snyder (1974) has developed and validated an instrument to measure the extent to which situational and dispositional factors in- fluence an individual's behavior. The Self-Monitoring Scale measures five facets of the process of behavior construction: (a) concern with the social appropriateness of one's self- presentation; (b) attention to social comparison informa- tion as cues to appropriate self-expression; (c) the ability to control and modify one's self-presentation and expressive behavior; (d) the use of this ability in parti- cular situations; and (e) the extent to which the respon- dent's expressive behavior and self-presentation is cross- situationally consistent or variable (Snyder, 1974, p. 529). These five facets of behavior construction provide a measure of an individual's sensitivity to situational cues. Since sensitivity to situational cues would appear to be central to a teacher's skills in managing a classroom, it should be possible to demonstrate a link be- tween measures of self-monitoring and classroom management behaviors of teachers. Specifically, it is theorized that high self-monitors should be more effective classroom managers than low self-monitors. This hypothesized relation serves as the primary focus of this inves- tigation. As mentioned earlier, self-monitoring measures the extent to which individuals characteristically rely upon cues contained in the social situation or upon their inner states. In other words, self- monitoring may identify individuals who are particularly affected or unaffected by their personality traits. Therefore, when used in con- junction with a measure of personality, it may increase the predictive power of the personality measure. One personality variable that would seem to have some influence on an individual's ability to manage a classroom is locus of control. This presage variable will, therefore, also be considered in this investigation. Locus of Control (Locus of control) is a concept which was developed out of social learning theory (Rotter, 1954) and refers to the ex— tent to which an individual feels that he has control over the reinforcements that occur relative to his behavior. Externals feel that forces beyond their control are the essential factors in determining the occurrence of rein- forcements (such forces might include fate, chance, power- ful others, the complexity of the world, or its unpredic- tability, etc.). Internals, however, tend to feel that they control their own destiny and are the effective agent in determining the occurrence of reinforcements. All of this represents a continuum of individual differences that cuts across specific need areas (Phares, 1965, p. 359). Research using the locus of control construct has identified several specific behaviors exhibited by internally-oriented indivi— duals which may directly affect classroom management behavior. Re- search conducted by E. Jerry Phares (1972) suggests that internals are more able than externals to exert influence upon others in social situations. It has also been demonstrated that internals more than externals avail themselves of information, even if it has negative connotations for themselves (Seeman and Evans, 1962). In addition, internals are more likely than externals to engage in the preliminary steps of data gathering when information seeking seems pertinent to outcome demonstration (Davis and Phares, 1967). These and other re- search findings suggest that it is reasonable to hypothesize that internally-oriented teachers are apt to be better classroom managers than externally-oriented teachers. Self-Monitoring as a Moderating Influence By considering both self-monitoring and locus of control, it may be possible to generate more precise predictions of classroom manage- ment behaviors than predictions that are based on either measure alone. With the aid of the self-monitoring instrument, teachers can be subdivided into two groups: those whose social behavior is parti- cularly sensitive to situational influences and those whose behavior characteristically reflects underlying attitudes and dispositions (Snyder, 1979). In other words, the Self—Monitoring Scale might be used to identify individuals ”for whom" locus of control orientation is particularly relevant to the construction of their self-presenta- tion and individuals who are not particularly affected by their locus of control orientation. It is, therefore, conceptually reasonable to predict that teachers who are both internal and high self-monitors will be the most effective classroom managers. Conversely, those who are external and low self-monitors will be the least effective class- room managers. Hypotheses which consider both presage variables will, therefore, be examined in this investigation. The theoretical con- jectures which underlie these hypotheses will be described in more detail in Chapter II. Classroom management: a process variable. Research on classroom management has a long history beginning with H. H. Anderson's (1939) .--. .. mflrV'l‘M ..'- .. k0 dominative-integrative dichotomy. Recently, the work of Jacob Kounin (1977) has redirected teacher management research. By studying stu- dent behavior and its accompanying teacher behavior, he has described 1 a set of teacher classroom management behaviors which create an ef- fective classroom milieu. Kounin (1977) states: It is possible . . . to delineate concrete aspects of teacher behavior that lead to managerial success in the classroom . . . . These techniques of classroom manage- ment apply to the group and not merely to individual children (p. 144). The possession of group management skills allows the teacher to accomplish her teaching goals--§he absence of managerial skills acts as a barrier p. 145 . Kounin has delineated six categories of teacher classroom manage- ment behavior. Four of his categories are employed in this investi- gation. For a more complete explanation of these categories than is presented in this chapter, see Chapter II and Appendix G, ”The Classroom Management Observation System.” Withitness is defined as a teacher communicating to her students that she is aware of their behavior. It is measured by first observ- ing if the teacher ”desists” the correct deviant student. That is, is the teacher intervention directed toward the student who, in the observer's opinion, is causing a disruption? Secondly, is the desist ”timed" properly? Does the teacher desist the disruptive behavior be- fore it becomes more serious and before it spreads to other students? Withitness is theorized to have a positive effect upon student judgments concerning teacher effectiveness. Students are more likely to refrain from deviant behavior and to be involved in school work if they judge the teacher to be cognizant of their behavior. Differences in the manner (quality) of desists are not recorded. Only the observ- able actions of the teacher's desist is of concern to the observer. Overlapping is defined as a teacher's ability to pay attention to two issues simultaneously. Success in handling the two issues is not important. An overlapping event is present when the teacher is occu- pied with the total group or a subgroup and a deviancy occurs in another group or a student ”brings in” an issue when she is occupied with a group. Two categories of overlapping are coded—-some overlapping and no overlapping. For an overlapping issue to be coded some overlapping, the teacher must show some attention to the “sphere group” while handling (a) a problem or question which a student brings in or (b) the student deviancy. To be coded no overlapping, the teacher must completely drop the sphere group and become immersed in only one of the two overlapping issues. Overlapping is purported to affect student behavior by broadening the teacher's scope of active attending, enabling the teacher to re— ceive more information concerning student behavior. As one might suspect, withitness and overlapping highly correlate with each other. Both management codes concern ”deviancy management” of student beha— vior. Smoothness describes behaviors initiated by the teacher which in- terfere with the flow of academic activities. Any perceptible action of the teacher which produces a stop or break in the programmed acti- vity flow is coded as negative smoothness. Uncontrollable events, such as a principal's message, are not coded. Five categories of smoothness are recognized and coded: stimulus-boundedness, thrusts, dangles, truncations, and flip-flops. ll Smoothness is theorized to affect student behavior by breaking the flow of student cognitive activity, thereby distracting the stu- dent and encouraging misbehavior or lower levels of work involvement. A smooth academic presentation leads the student through a set of ideas without teacher-initiated distractions. Momentum codes measure behaviors initiated by the teacher that slow—down the rate of movement in a recitation activity. Two cate— gories of momentum are coded: overdwelling and fragmentation. Their effect is to hold back the progress of an activity. Momentum is hypothesized to effect student behavior in a manner similar to smoothness. If the rate of an activity is slow, students will be more open to distraction and will have difficulty in following the lesson, thereby encouraging misbehavior and lower levels of work involvement. Smoothness and momentum are highly correlated with each other. They are also conceptually related and may be subsumed under the move general label ”movement management.“ A Conceptual Link Between Presage Variables and Classroom Management Research conducted by Amidon and Flanders (1953) suggests that a teacher's ability to adapt behavior to the specific classroom situa- tion contributes to student leaning. Better teachers used a variety of patterns of behavior while poorer teachers used patterns that were much alike. In order to vary their behavior to meet the demands of the speci— fic classroom situation, teachers must be sensitive to situational cues and they must be predisposed to influence the social situation. 12 These two determinants of teacher flexibility are directly addressed by the psychological constructs of self-monitoring and locus of con- trol. The four classroom management criterion measures employed in this investigation also stress teacher behaviors which demand sensitivity and flexibility to the changing social environment of the classroom. Teachers must read the student behavior cues in the situation and tailor their responses to them in a manner which facilitates positive student behavior. For example, when a teacher desists a student de- viancy, she has a wide range of possible responses available to her ranging from a subtle nonverbal message to the use of an I-message to the use of a discipline technique such as a time-out corner. The frequency of behavior management techniques such as these are re— flected in the withitness scale. Teachers must also be aware of the changing social environment in order to exercise movement management. When students become bored with the rate of presentation of subject matter, a teacher must read the situational cues and change her pace (momentum) accordingly. Responses may range from excluding some ma- terial to dealing with the subject matter in a more superficial mannen In summary, self-monitoring and locus of control measure sensi- tivity to situational cues and predisposition of teachers to influence social situations. The classroom management measures employed in this investigation reflect a teacher's sensitivity to the changing so- cial context within the classroom and flexibility of their response to the situation. It is, therefore, reasonable to expect that the two measures of presage variables will be positively correlated with the four measures of classroom management behaviors. 13 Summary The critical variables in the research design can now be graphi— cally represented using the Dunkin and Biddle model (see Figure 2). Presage Variables Teacher Properties Process Variables Self-Monitoring Teacher Behaviors Product Variables Locus of Control Nithitness Achievement Overlapping - — - - 9 Attitudes Context Variables Smoothness Elementary Momentum Self-Contained \ ‘gg'fl Recitation Activities //’/ \ . j Urban Student Behaviors Freedom from Deviancy work Involvement Note: Relations that will be examined in this study.—————————9 Relations that have been demonstrated in the literature. ----- 9 Figure 2. Critical variables in the research design. The arrows in the model represent causal assumptions. Teacher classroom management behavior is assumed to be a function of teacher properties and student outcomes are assumed to be a function of teach- ing. The present research project concerns itself only with the rela- tionship of presage and process variables. Context variables are viewed as affecting the generalizability of the research methodology and findings. 14 The Classroom as a Self- Monitoring Environment The self-monitoring construct need not be linked uniquely and exclusively with differ- ences between individuals in their self-monitoring pro- pensities. In fact . . . it is possible to identify so- cial environments and interaction contexts that promote the strategic orientation that characteristically is adopted by high (and low) self-monitoring individuals (Snyder, 1979, p. 111). Individuals understand themselves in relation to the social circum- stances in which they find themselves. Since the classroom is a well defined environment in which teachers interact with others, the self- monitoring construct might be measured in relation to this specific environment. In other words, a measure of self-monitoring that fo- cuses on the classroom environment may provide more precise predic- tions of classroom behaviors than a measure that concentrates on the general social context. The development of a specific Classroom Self-Monitoring Scale and tests of its ability to predict classroom behaviors represents the final goal of this investigation. Need Research attempting to link teacher presage variables to teacher classroom behavior and student outcomes has been noticably unproduc- tive (Getzels and Jackson, 1963). Despite the disappointing findings in this area to date, contemporary American ideology and conventional wisdom persists in the assertion that behavior is directed by internal regulatory systems. As a result, researchers continue to search for personality constructs that will provide effective predictions of in- dividual behaviors in a variety of situational contexts. 15 Recent theoretical developments which suggest that personality assessment must attend to the individual's phenomenological view of different situations seems to provide a promising new direction for presage variable research. Articles by Bem and Allen (1974) and Snyder (1972, 1974, 1979) seem particularly noteworthy in this re- gard. This investigation attempts to expand upon Snyder's work by examining the potential role of self-monitoring in guiding the class— room management behaviors of teachers. The study should, therefore, have implications for both social-psychological theory and educa- tional practice. Purpose The primary purposes of this study are to investigate (a) the re- lationship between self-monitoring and four classroom management variables (withitness, overlapping, momentum, and smoothness), and (b) to test the purported ability of self-monitoring to function as a moderating variable, identifying "for whom" locus of control orien- tation is salient information for the prediction of classroom manage- ment behaviors. In addition, several secondary purposes, suggested by theoretical conjectures, will be investigated. In order to satisfy these purposes, two objectives must be met. The first objective is to develop a Classroom Management Observation System which will provide satisfactory measures of the four classroom management variables. This system should be useful to practicing teacher educators as well as those engaged in research on teaching. The second objective is to develop and refine a measure of self- monitoring which focuses on the classroom environment. Tests of the predictive properties of this instrument should be of interest to 16 educators as well as social psychologists. The purposes and objec- tives are perhaps best described by the set of research questions out- lined below. Research Questions Specific research questions suggested by the purposes and objec— tives of this investigation may be briefly summarized as follows: 1. Will the relationship between self-monitoring and each of the classroom management measures be signifi- cantly greater than zero? Hill mean scores on the management measures vary as a function of the level of self-monitoring gpg_10cus of control orientation? Will relationships between each of the predictor vari- ables and each of the classroom management variables conform to patterns suggested by theoretical conjec- ture? Will relationships between each of the predictor vari- ables and the entire set of classroom management vari- ables conform to patterns suggested by theoretical conjectures? Is there a predictable pattern of relationships among the four classroom management measures? Hill the magnitude of the correlation between scores on the Self-Monitoring and Classroom Self-Monitoring Scales conform to the theoretical conjectures on which the latter measure is based? 17 7. Will relationships between the entire set of predic— tor variables and each of the classroom management variables conform to patterns suggested by theoreti- cal conjectures? 8. Will mean scores on the management measures be larger for those teachers who have high scores on the Self- Monitoring Scales than for those with low scores? Hypotheses The study focuses on relations between the three predictor vari- ables (self-monitoring, classroom self-monitoring, and locus of con- trol) and measures of classroom management (withitness, overlapping, momentum, and smoothness) that serve as criterion variables. Primary Hypotheses ”I The magnitude of the simple correlations between self- monitoring and each criterion measure will be signifi- cantly greater than zero. lbw) zero ICo> zero ICm> zero Note: Subscripts: S = self-monitoring, w = withitness, o = over- lapping, m = momentum, s = smoothness Hypothesis II examines the moderating function of self-monitoring on the locus of control orientation of individuals. ”11 The magnitude of mean scores on the management measures will differ significantly when teachers are grouped according to their level of self-monitoring and internal- 18 external locus of control orientation. The distribu- tion of mean scores will conform to the following patterns: high self-monitoring, internal locus of control)> M ( M (high self—monitoring, external locus of control) and M (low self-monitoring, internal locus of control)> M_(low self-monitoring, external locus of control). Secondary Hypotheses The hypotheses which follow are based on the theoretical conjunc- ture described in Chapter II. ”III Note: The magnitude of the simple correlations between each predictor variable and each criterion variable will vary in a consistent order. Corrolary 3a: Simple correlations between self-monitoring and each criterion measure will vary in the following order: [SW (withitness)> £8 (overlapping)> [Sm (momentum) > :55 (smoothness) Corrolary 3b: Simple correlations between classroom self- monitoring and each criterion measure will vary in the following order: raw (withitne55)> :50 (overlapping)> Itm (momentum) > 3C5 (smoothness) Corrolary 3c: Simple correlations between locus of control and each criterion measure will vary in the following order: er (withitness) >tL0(overlapping)> fiLm (momentum) > [Ls(smoothness) Subscripts: C = classroom self-monitoring, L = locus of con- trol 10 HIV The magnitude of the simple correlation between each predictor variable and the entire set of criterion variables will vary in a consistent order. Ibwoms (classroom self-monitoring/withitness, and overlapping, and momentum, and smoothness)’ ISwoms (self-monitoring/withitness, and overlapping, and momentum, and smoothness)> FLwoms (locus of control/withitness, and overlap- ping, and momentum, and smoothness) HV The magnitude of intercorrelations among the four class- room management measures will conform to a predicted pattern. Corollary 5a: The simple correlation between the two deviancy management measures (withitness and overlap— ping) will be greater than correlations between either of those measures and the two movement management mea- sures (momentum and smoothness): two) (Ewm 0T Ews or Eom or E.os) Corrolary 5b: The simple correlation between the two movement management measures (momentum and smoothness) will be greater than the correlations between either of these measures and the two deviancy management mea- sures: rsm>’(-r—'mw or Emo 0V Esw or £50) HVI HVII HVIII 29 The correlation between self-monitoring and classroom self-monitoring will be less than .60 and greater than .40. .40< :SC <.6O The magnitude of the multiple correlations between the three predictor variables and each criterion variable will vary in the following order: BCSLw (classroom self-monitoring + self-monitoring + locus of control/withitness)> ECSLo (three predictor variables/overlapping)> BCSLm (three precictor variables/momentum)> BCSLs (three predictor variables/smoothness) The magnitude of mean scores on the management measures will differ significantly when teachers are grouped ac- cording to their level of self-monitoring. Corollary 8a: The group mean score for withitness will be significantly larger for high self-monitors than for low self—monitors. Corollary 8b: The group mean score for overlapping will be significantly larger for high self-monitors than for low self-monitors. Corollary 8c: The group mean score for momentum will be significantly larger for high self-monitors than for low self-monitors. Corollary 8d: The group mean score for smoothness will be significantly larger for high self—monitors than for low self-monitors. Overview This dissertation consists of four additional chapters. In Chapter II a conceptual framework is provided with an emphasis on the classroom as a social system, classroom management research of Jacob Kounin, self-monitoring and locus of control research, and the rela- tionship between classroom management and personality. It includes a review of the literature relevant to the problem under study. The procedures employed in the implementation of the research de- sign are described in Chapter III. It includes a description of Phase I (testing), the design of Phase II, instrumentation and instrument reliability, observer training, data collection, and data analysis. The statistical results that test each hypothesis are presented in Chapter IV. Post hoc analyses that are considered significant are also considered. Results of the study are discussed in Chapter V,and general con- clusions are drawn from the research. The chapter ends with a dis- cussion of implications for presage-process researchers. CHAPTER II REVIEW OF THE LITERATURE Thus, when our young student enters school in the morn- ing he is entering an environment with which he has be— come exceptionally familiar through prolonged exposure. Moreover, it is a fairly stable environment——one in which the physical objects, social relations, and major activi- ties remain much the same from day to day, week to week, and even, in certain respects, from year to year. Life there resembles life in other contexts in some ways, but not all. There is, in other words, a uniqueness to the student's world. School, like church and home, is some- place special. Look where you may, you will not find another place quite like it (Jackson, 1968, p. 9). Overview The research design used in this investigation can be character- ized as presage-process. The presage variables are two personality constructs which are examined within the context of the leadership role of the teacher in the traditional classroom. The process vari— ables are the overt classroom management behaviors of teachers. The basic purpose of the study is to investigate relationships between the personality variables and the classroom management behaviors of ele- mentary teachers. Figure 3 provides a pictorial representation of these relations. As indicated in Figure 3, the teacher's institutional role as leader of a working group, whose goal is academic learning, is as- sumed to interact with the individual's personality to produce the teacher's classroom management behavior. Therefore, the review begins 22 23 Presage Institutional Roles Leadirship Process Personality Classroom Self-Monitoring > Management X Behaviors Locus of Control Figure 3. Relations that serve as the primary focus of this investigation. with a theoretical framework that serves as the basis of these assump- tions (Getzels and Thelen, 1960). The role of the teacher to lead or to manage the classroom learn- ing environment is central to the investigation. Thus, research con- cerning this role is traced from the early investigations of H. H. Anderson (1939) through the mroe recent studies of Jacob Kounin (1977) With the work of Kounin, the review shifts from presage to process variables. He delineated specific categories of classroom management behaviors which significantly correlate with positive student beha- viors and highler levels of learning. These categories of teacher be— havior form the criterion variables in the investigation. The review then returns to two specific presage variables, self- monitoring (Snyder, 1979) and locus of control (e.g., Rotter, 1966), which are the two personality variables of interest in this investiga- tion. The major assumption is that these variables, singly and in combination, predict teacher classroom behaviors. The final section of Chapter II provides an explanation of the behavioral consequences of the interaction of the two presage variables. 24 Part I: The Classroom as a Social System In 1932 Willard Waller analyzed the school in sociological terms. He characterized the school as a “social organism” and investigated the school's relationship to the community, its existence as a cul— ture unto itself, and the internal relationships within the school. Twenty years later Talcott Parsons (1959) focused the lens of socio- logical investigation on the classroom. He analyzed the structure of the classroom and related it to the primary functions of society. He concluded that the classroom functions to (a) internalize in its students the commitments and skills necessary for successful perfor- mance of adult roles, and (b) allocate human resources into the role structure of the adult society. Parsons viewed the school as the principal channel of selection as well as the agency of socialization which increasingly differentiates and progressively upgrades society. Getzels and Thelen's Analysis of the Sociology of the Classroom Perhaps the most widely read and cited work on the classroom as a social system is Getzels and Thelen's chapter ”The Classroom Group as a Unique Social System” in The Dynamics of Instructional Groups, edited by Henry (1969). In this work, the authors describe the nature of the classroom group and present a conceptual framework which may be used to study the classroom. Because this investigation relies heav- ily upon the assumptions made in this paper, Getzels and Thelen's position will be reviewed in detail. According to Getzels and Thelen, the classroom is a working group and all working groups have certain characteristics in common: (a) goals they endeavor to achieve; (b) participants who interact with 25 each other to achieve these goals; (c) leaders to control and direct activities; and (d) relationships, both implicit and explicit, to other groups or institutions. Their discussion of goals and leader- ship is of particular importance to this investigation. Classroom goals are consciously planned and the primary goal is learning. Subject—matter and teaching methods are, to a certain ex— tent, specified in advance by authorities external to the learning group. Within these stipulated limits, teachers and students have room for flexibility which enables them to meet immediate needs and interests of the particular group. The leadership of the classroom is vested in the teacher. This authority is sanctioned by law and custom. The teacher can delegate authority for certain functions to students, but delegation of author- ity cannot occur without a teacher's permission. The classroom is not a democracy. Students have only indirect influence on the teacher's style of leadership. A Conceptual Framework Getzels and Thelen (1960) conceive of social systems as involving two classes of phenomena which are at once conceptually independent and phenomenally interactive. First, there are the institutions with certain roles and expectations that will fulfill the goals of the system (the nomothetic dimension). Secondly, there are the in- dividuals with certain personalities and need dispositions inhabiting the system (the idiographic dimension), whose observed interactions comprise what we call social or group behavior (p. 65). According to this framework, behavior can be understood as a function of the nomothetic and idiographic dimensions of the social system. The nomothetic dimension consists of roles which define the 26 behavior of the role incumbent and are defined in terms of role- expectations. Applied to the classroom, the teacher performs the role-behaviors expected of the him-teaching, and the student performs the role expectations expected of him-learning. Roles are occupied by real individuals who stamp their particu- lar role with the unique style of their own characteristic pattern of expressive behavior. The idiographic dimension involves the indivi- dual's personality and need-dispositions. Need-dispositions are indi- vidual tendencies to act, and their dynamic organization defines the individual's personality. Need—dispositions and role expectations may be thought of as the motives for behavior. A pictorial model of the interaction of the nomothetic and idiographic dimensions is summarized in Figure 4. Nomothetic Dimension I”,s1nstitutions —————9 Role —~——~——)Expectation Social 1 L 1 L l L ‘TT‘SAObserved Systems Need ///},Behavior Individual~——+ Personality ————>Disposition Idiographic Dimension Figure 4. Interaction of the nomothetic and idiographic dimensions of the social system (Getzels and Thelen, 1960, p. 69). In Figure 4, each term is the analytic unit for the term preced- ing it,and observed behavior is derived simultaneously from both the nomothetic and idiographic dimensions. Getzels and Thelen presume that each classroom calls for a balance between the institutionally defined roles and personalities of teachers and students. In working out this balance between the institution and the individual, the group develops a "culture” or, 27 perhaps better here, a climate . . . (Getzels and Thelen, 1960, p. 79). Early Studies of Teacher Role The primary role-expectation for teachers in our society is to direct the learning activities of students. Teachers and students ex— pect the teacher to take charge, to initiate activities, and to con- tribute information as needed in the learning process. Considerable research has been directed toward showing that how the teacher per- forms this role makes a great deal of difference in student behavior. According to Amidon and Flanders (1963), H. H. Anderson set the general pattern for research on the consequences of teacher behavior. Anderson (1939) identified two general styles of teacher behavior (dominative and integrative) and examined the impact of both styles on student behavior. In the course of his research, he developed reli— able measures for recording "dominative" and “integrative” teacher behaviors. Domination is the behavior of a person who is inflexible, rigid, deterministic, who disregards the desires or judg- ments of others, who himself has the answers . . . . Domi— nation is the technique of autocracy or dictatorship. The term integrative behavior was chosen to designate beha- vior leading to an awareness or commonness of purpose among differences . . . . It is non-coercive; it is the expres- sion of one who attempts to understand others, who is open to new data (Anderson, 1939, p. 89). The research of Anderson produced four significant findings. First, the dominative-integrative style of the teacher sets the pat- tern of behavior which spreads throughout the classroom. In other words, it is the teacher who establishes the climate of the classroom. Second, students show more spontaneity and initiative in the classroom 28 when a teacher is integrative. Third, students exhibit more compli- ance to teacher directions when a teacher is dominative. Fourth, Anderson noted that teachers classified as dominative or integrative differ from each other only in degree and are apt to vary their be- havior in order to achieve desired student behaviors. This observa- tion is the first indication that flexibility of teacher behavior is an important personal characteristic. More definitive evidence that flexibility in teaching style, or the ability to adapt behavior to the immediate situation, is important to teaching success is supplied by Mitzel and Rabinowitz (1953) and Amidon and Flanders (1963). Mitzel and Rabinowitz found wide variability in the integrative—dominative style of teachers across different observations. Amidon and Flanders took this observation one step farther and found flexibility of teaching style to be more predictive of teaching success in terms of student achievement than the more static concept of direct-indirect influence. In other words, above-average teachers had the capability to make their behaviors appropriate to the requirements of the class- room situation at the moment. More recently, Hunt and Joyce (1967) found that teachers who were able to exhibit a wide range of teaching styles were judged to be more effective as teachers. Crocker (1974) found significant correlations between flexibility test scores and performance in student teaching. In brief, there is considerable evidence that flexibility of teacher style is an important predictor of teacher effectiveness in terms of student behavior and achievement. Several other studies concerning teacher style deserve to be noted. The classic laboratory experiments of Lewin, Lippitt, and 29 White (1939) were carried out a year or so after Anderson started his work. Adults working with ten year old boys were trained to consis- tently act authoritarian, democratic, or laissez-faire. Authoritarian leadership was similar to Anderson's dominative style in which leaders gave orders without much explanation. Democratic leadership was simi— lar to integrative contacts where leaders took time to solicit Opin- ions and achieve some group consensus. Laissez-faire leadership con- sisted of giving vague directions and was not present in the Anderson study. The effectiveness of these leadership styles was assessed for group productivity and attitudinal development. Most of the results of the Lewin, Lippitt, and White study con- firmed the general conclusions of Anderson. The authoritarian-led groups were most efficient in meeting production goals, but boys in these groups developed negative feelings toward each other and the leader. Although the democratically-led groups developed positive feelings toward the leader and for each other, they were not quite as efficient in meeting production goals. The laissez-faire groups did not succeed by either criterion. The research of Baumrind (1971) provides further clarification of the findings on group leadership. Baumrind classified parents as au- throitarian, authoritative, or laissez-faire. The term authoritative replaced Lewin, Lippitt, and White's term democratic and seems to be much more consistent with the descriptions of an ideal leadership style that may be inferred from Anderson (1939) and Amidon and Flan- ders (1963). The authoritative leader retains a position of ultimate authority, but seeks input from the group and takes care to see that everyone is clear about the rationale for decision making. Baumrind 30 reports that the children of authoritative parents are more indepen- dent, more confident, and generally have more healthy self—concepts. Summary: The Classroom as a Social System Getzels and Thelen (1960) describe the classroom as a social sys- tem in which behavior is a function of roles and personalities. The interaction of institutionally defined roles and individual personali— ties results in a unique group climate. Research concerning the role of the teacher has a long history. Collectively, these investiga- tions suggest that flexibility in a teacher's classroom mangement style is an important predictor of teaching success. Perhaps the best descriptor of the optimum style of the teacher's role is offered by Baumrind (1971), namely, authoritative. An authoritative teacher is one who speaks as an experienced and mature adult, who retains ul- timate responsibility for decision-making, but is flexible enough to solicit input and seek consensus from the group. Part II: The Classroom Management Research of Jacob Kounin Despite the generally recognized importance of classroom management skills, the work of Kounin and his colleagues remains the only completed large scale program on the topic (Brophy and Putnam, Note 3). As the introductory quote clearly implies, the role of the teacher as manager of the classroom learning environment has been most thor- oughly researched by Jacob Kounin. It is summarized in Discipline and Group Management (1977). In his early research, Kounin concluded: There is no relationship between the qualities of a teacher's desist technique (observable teacher reaction to student misbehavior) and the degree of success in handling a deviancy. Thus, for any teacher, neither the degree of clarity, firmness, and intensity of her 31 desist effort; nor whether she focuses on the misbehavior, or on the legal activity, or on both; nor whether she treats the child positively, negatively, or neutrally; makes any difference for how readily a child stops his deviancy or gets on with the prescribed task (pp. 65-66). Kounin's (l977) conclusion leads him to ask the question, ”Is it possible to delineate what it is that teachers gp_that makes a differ- erence in how children behave?” (p. 74). Using videotapes of actual classroom events, he constructed specific categories of teachers' behavior that correlated with their managerial success as measured by work involve- ment, deviancy rate, contagion of misbehavior, and effec- tiveness of desists (p. 74). These categories of teacher behaviors related to the classroom as a whole and not merely to specific pupils and held for all types of students including those who were emotionally disturbed. Scoring of Pupjl Behavior Kounin's indicators of successful classroom management were rate of work involvement and freedom from deviancy of pupils. Each child preselected for scoring was coded for these two behaviors every twelve seconds for the duration of the lesson. Work involvement was cate- gorized by coding the students behavior as ”probably in“ and ”defi— nitely out.” Deviancy was coded by characterizing the behavior of a child as “definitely in“ or “definitely out” of deviancy. Deviant behavior was defined as having: direction and purpose (intentional and with knowledge that it is de- viant) and as being against the teacher, another child or some reasonably important convention of classroom be- havior (Kounin, 1977, p. 78). Scoring Teacher Behavior Six different teacher management behaviors were identified from videotapes of classrooms, and they were grouped in three categories. The first category, deviancy management, consists of withitness and overlapping, both of which address management of student behavior. The second category, movement management, consists of momentum and smoothness, both of which concern the presentation of subject-matter. Due to the demands of recording live classroom observations, the third category, group focus, was not considered in this investigation. It consists of group alerting and accountability, both of which concern maintaining student attention. Deviancy Management Measures Withitness is defined as a teacher's communicating to students by her actual behavior that she knows what the students are doing. In Kounin's view, the communication of teacher awareness of the social situation induces work—like behavior and restrains deviancy since stu— dents believe their behavior is being accurately monitored. Kounin identified two teacher behaviors which communicate to stu- dents that the teacher is withit. They are ”targeting” and ”timing” and are coded when a teacher "desists” a student. A desist event oc— curs when a teacher engages in an overt action to manage student beha- vior. The target constitutes a student or subgroup that the teacher desists. Target mistakes consist of desisting the wrong student, subgroup, or a less serious deviancy. Timing mistakes consist of desisting a deviancy after it became more serious or spreads to other students. Overlapping concerns the behavior of a teacher who has two or more matters to deal with at a given point in time. It is coded for evidence of a teacher's paying attention to both issues (some 33 overlapping), or only to one (no overlapping). The event is not coded for whether it is successful or not. The Relationship Between Deviancy Management and Managerial Success Kounin's research (1977) suggests that both withitness and over- lapping are significantly related to managerial success in recitation sessions. The product moment correlation of withitness with work in- volvement is .62 and .53 with freedom from deviancy. The correlation of overlapping with work involvement reported by Kounin is .46 and .36 with freedom from deviancy. Withitness and overlapping, then, may be said to induce work-like behavior and to restrain deviancy. Withitness and overlapping are significantly correlated with each other (p_= .60), which means that teachers who manifest more withit- ness also tend to manifest more overlapping. Using partial correla- tional analyses, Kounin determined that withitness by itself has a stronger relationship with managerial success than does overlapping by itself. Movement Management Measures Momentum involves behaviors initiated by teachers which clearly impede the forward movement (rate) of an activity; i.e., behaviors which produce friction. Two categories of momentum which cause slow- downs are coded overdwelling (dwelling on an issue beyond what is necessary for understanding), and fragmentation (breaking up an ac- tivity into needlessly small parts). Smoothness delineates teacher initiated behaviors that interfere with the smoothness of movement in academic activities. Such beha- viors produce stops or jarring breaks in the activity flow. Events 34 which are not initiated by the teacher are not coded for smoothness. Five categories of smoothness are coded: stimulus—boundedness (the teacher becomes distracted by an irrelevant and unrelated stimulus), thrust (teacher insensitivity to student readiness), dangles (the teacher drops an activity before it is finished, starts a new acti- vity, and then returns to the original activity), truncations (a dangle without returning to the original activity), and flip-flops (the teacher finishes an activity, begins another, and returns to the original one). Scoring procedures for withitness, overlapping, momentum, and smoothness are presented in Chapter III. The Relationship Between Movement Management and Managerial Success Kounin (1977) has shown that both momentum and smoothness are significantly related to work involvement and freedom from deviancy. The product moment correlation of momentum with work involvement is .66 and .64 with freedom from deviancy. The correlation of smooth— ness with work involvement is .60 and .49 with freedom from deviancy. Momentum and smoothness, then, may be said to induce work involvement and to restrain deviancy. Momentum and smoothness also correlate significantly with each other (p_= .75). In other words, teachers who score high on momentum also tend to score high on smoothness. Using partial correlational analyses, Kounin determined that momentum is more highly associated with student behavior in recitation settings than is smoothness by itself. These results seem to indicate that it is more important to maintain momentum than it is to maintain smoothness in these settings. 35 Group Focus Group alerting refers to teacher behaviors which maintain or establish student attention during lessons. These behaviors include looking around the group before calling on a student to recite, keep- ing students in suspense as to who will be called upon next, calling on a wide variety of students, mixing choral and individual responses, and challenging students. Accountability refers to the degree to which teachers hold stu- dents responsible for their task performances. Teachers can hold stu- dents responsible by requesting them to hold up their work, having them recite in unison, circulating and checking work, and asking who is prepared to answer. The determination of group alerting and accountability scores re- quire the investigator to observe and record teacher behaviors at 30-second intervals. Although this requirement might be satis— fied when videotapes are being used, it clearly strained the bounds of live observation. These two measures were, therefore, not considered in this investigation. Subsequent Research in Classroom Management Most, but not all of Kounin's findings have been supported by subsequent research. In a correlational study (Brophy and Evertson, 1976) and in an experimental study (Anderson, Evertson, and Brophy, Note 2), withitness, overlapping, momentum, and smoothness were found to be associated with better classroom management and, most important— ly, facilitated higher levels of student learning. However, these studies did not provide support for some of the group alerting and accountability techniques. 36 Good and Grouws (Note 4) found that group alerting was positively related to student learning, but found accountability to be related curvilinearly. In other words, a moderate amount of accountability was more successful than too much or too little. A recent study by Anderson, Evertson, and Emmer (Note 5) carries Kounin's work one step farther by investigating the development and maintenance (or decline) of management systems. They concluded that better managers provide information to students about how to behave, provide reasons to perform on-task behaviors, maintain the learning environment by providing success-oriented tasks and activities, and hold students accountable for these activities. Summary of Classroom Management Research This investigation is consistent with the framework described by Getzels and Thelen (1960) which holds that the classroom is a social system in which behavior is a function of roles and personalities. Research concerning the role of the teacher as a flexible monitor and manager of the classroom social system was reviewed in Part I. A sys- tem for evaluating the managerial success of teachers was the focal point of Part II. This system (Kounin, 1977) gave rise to the four criterion variables of this investigation: Withitness and Overlapping. These dimensions deal with a teacher's communicating that she knows what is going on regarding children's behavior and with her attending to two issues simultaneously when two different issues are present. Smoothness and Momentum. These parameters measure how the teacher manages movement during recitations and at transition periods (Kounin, 1977, pp. 143-144). Kounin (1977) has shown that each of these four variables is closely related to student work involvement and freedom from deviancy. 37 Anderson, Evertson, and Brophy (Note 2) have subsequently shown that they are also associated with higher levels of student learning. Part III: Self-Monitoring and Locus of Control Personality psychologists have long argued the relative impor- tance of personality traits or situations in the determination of in- dividual behavior. Classical personality theories postulate underly- ing properties, qualities, or processes which exist within the person and account for behavioral consistency. On the other hand, social learning theorists argue that the situation determines human behavior. This debate seems to be a pseudo issue. Bowers (1973) reported that the average behavior variance due to personal traits was 12.71%, that due to situations was 10.17%, and that due to Person X Situation in- teraction was 20.77%. Bowers research suggests that the traits or situations debate is misdirected and that the interaction between per- sonal and situational determinants of behavior needs to be stressed (Bem, 1972). Moreoever, research by Bem and Allen (1974) suggests that individuals differ in the extent to which their social behavior is “trait-like“ or ”trait-free“ across social situations. Snyder (1972, 1974, 1975, 1979) has interpreted these findings as indicating that individuals differ in the extent to which situational and dispos— itional factors influence behavior. He has conceptualized these indi- vidual differences in terms of the social-psychological construct of self-monitoring. Self-Monitoring The roots of Snyder's construct of self-monitoring may be traced to the classic pragmatic theories of the self. According to 38 phenomenological theory, individuals exercise control over their self- presentations in social situations. Research has demonstrated that individuals can express emotions with their vocal and/or facial beha- vior and that their expressive behavior can be accurately interpreted by observers (e.g., Davitz, 1964). In fact, as Mischel (1973) has emphasized, the ability to manage and control expressive behavior may be the hallmark of an individual who copes effectively in a variety of situations. Snyder (1972) constructed a scale which captures differences in the extent to which individuals can and do monitor or regulate their expressive behavior and self-presentation. The Self-Monitoring Scale (Snyder, 1972, 1974) is a set of 25 true—false self-descriptive statements that de- scribe (a) concern with social appropriateness of one's self presentation . . . ;(b) attention to social com- parison information as a cue to situationally appropri— ate expressive self—presentation . . . ; (c) the ability to control and modify one's self-presentation and ex- pressive behavior . . . ; (d) the use of this ability in particular situations . . . ; (e) the extent to which one's expressive behavior and self-presentation are tailored and molded to fit particular social situations (Snyder, 1979, pp. 89-90). Construction of the Self-Monitoring Scale The first step in the development of the 25-item Self- Monitoring Scale was to administer 41 descriptive statements to 192 Stanford University undergraduates (Snyder, 1974). Using low dis— crimination scores as a guide, items were then discarded. According to Snyder (1974), the final 25— item Self-Monitoring Scale has a Kuder-Richardson formula 20 reliability coefficient of .70 and a test-retest reliability of .83 for a one month interval. Cross— validation on an independent sample of 149 University of Minnesota 39 undergraduates yielded a Kuder-Richardson 20 reliability of .63 (Snyder, 1974). Tests of the Validity of the Self-Monitoring Scale To demonstrate that differences identified by the Self-Monitoring Scale cannot be equally well identified by existing measures of re- lated psychological constructs, direct comparisons have been made be- tween self-monitoring and: need for approval (Snyder, 1972, 1974), extraversion (Lippa, 1976; Snyder and Monson, 1975), and Machiavel— lianism (Jones and Baumeister, 1976) in the prediction of external criterion variables. In each case, a strong and reliable relationship between self-monitoring and the criterion emerged. By contrast, the effects of need for approval, Machiavellianism and extraversion were trivial and statistically insigificant (Snyder, 1979, p. 92). In addition, Snyder (1979) has shown that self-monitoring is not correlated with locus of control, inner-directed versus other-directed social character, social chameleon, field dependence, intelligence, academic achievement, or vocational interests. It appears that self- monitoring is relatively independent of many psychological constructs. Snyder and others have also conducted studies to establish the extent to which the Self—Monitoring Scale can be shown to measure the psychological construct of self-monitoring. The first study (Snyder, 1974) involved peer ratings. It is assumed that people who have good control of their expressive self- presentationeukiwho are sensitive to social appropriate- ness cues should be seen as such by others who have known them in a wide variety of social situations (Snyder, 1979, p. 90). This assumption was confirmed. 40 In a seond study, Snyder (1974) predicted how predetermined groups of individuals (actors and psychiatric patients) would score on the Self—Monitoring Scale in comparison with an unselected sample of undergraduate students. The results were consistent with his pre- dictions. "Theater actors scored higher and hospitalized psychiatric ward patients scored lower than university students” (Snyder, 1974, p. 536). In a third study, Snyder (1974) investigated differences in the ability to accurately and naturally communicate affective states by means of expressive behaviors. He found that high self-monitors were more able to express arbitrary affective states than low self— monitors. Other investigations have shown that high self-monitors can change their self-presentation from introverted to extroverted with chameleon—like ability (Lippa, 1976) and can exploit their self- presentational skills to successfully practice the arts of deception (Krauss, Geller, and Olson, 1976). Snyder (1974) has also demonstrated that high self-monitors con- sult information about the self-presentation of others more often and for longer periods of time than low self-monitors. In addition, high self-monitors accurately remember information about otherslonger (Ber- scheid, Graziano, Monson, and Dermer, 1976) and pay keen attention to the subtle interplay between an individual's behavior and the context in which it is observed (Jones and Baumeister, 1976). Subsequent Self-Monitoring Research Armed with a measure of self-monitoring that has been shown to have a respectable level of validity, researchers have been able to link level of self-monitoring to (a) one's sensitivity to situational and interpersonal influences on self-presentation, (b) cross- 41 situational variability/consistency of behavior, (c) differences in foreground and background self-presentations, (d) consistency between attitudes and behavior, and (e) the dynamics of social relationships. Sensitivitypto situations. Snyder and Monson (1975) sensitized individuals to different reference groups which provided cues to social appropriateness of self-presentation. High self-monitors were keenly attentive and sensitive to the differences between reference groups and varied their self-presentations accordingly. Low self— monitors on the other hand were virtually unaffected by the differ- ences in the social setting. It was as if their self-presentations were reflections of internal states and dispoisitions and not the re- quirements of the social setting. Cross-situational variability. Snyder and Monson (1975) investi- gated the cross-situational variability in social behavior of low and high self-monitors. According to their self-reports, high self- monitors demonstrated considerably more variability across situations than did their low self-monitoring counterparts. In other words, high self-monitoring individuals were more flexible in their self-presenta— tions. “In different situations and with different people, they often act like very different people" (Snyder, 1979, p. 96). Foreground and background selfspresentations. The findings con- cerning cross-situational variability should not be interpreted as evidence that high self-monitors tailor their self-presentations in a chameleon-like fashion from situation to situation. Rather, the self- presentation skills of high self-monitors should allow them to be cross-situationally consistent if the situations call for such consis- tency. 42 Empirical research by Lippa (1976) suggests that high self- monitors appear to outside observers to be more friendly and non- anxious than low sel-monitors. It is this consistent background upon which high self-monitoring individuals construct their (situationally) specific foreground self-presentation. Snyder (1979) offers an ex- ample of foreground-background self—presentation. A campaigning politician might strive for different images when courting the city vote and the farm vote, but in each situation he or she would also try to appear friendly and non-anxious (p. 96). In contrast, the low self-monitor's self—presentation typically de- monstrates greater cross—situational consistency in foreground self- presentation and greater fluctuations in background self—presentation. Attitudes and behavior. Snydern and Swann (1976) investigated the relationship between measured attitudes toward affirmative action and verdicts (behavior) in a mock court case. As the researchers ex- pected, the relationship between attitudes and later behavior was mo- dest. However, when the participants were grouped according to their level of self-monitoring, a pattern emerged. The behavior of low self-monitors was consistent with their measured attitudes. In other words, self-monitoring worked as a moderating variable, identifying ”for whom" the measured attitude would have the most impact. Snyder and Tank (1976) have also shown that it is possible to forecast the attitudes that low self-monitors will express in the future from knowledge of their current behavior. Further evidence of the link be- tween level of self-monitoring and the effects of inner states on behavior can be found in the work of Ickes, Layden, and Barnes (1978). They concluded that the self-presentations of low self-monitors seem quite sensitive to transitory mood states and that high self-monitor- ing individuals seem better able to ignore such mood states. Social relationships. Empirical research has also linked self- monitoring with the initiation and development of social relation- ships. For example, Garland and Barnes (Note 6) found that high self- monitorswere inclined to talk first and to initiate subsequent con- versational sequences. They were seen by their partners to have a greater need to talk and as being the more directive member of the dyad. High self—monitors frequently emerged as group leaders. Self-Monitoring Strategies Validation and subsequent research on the self-monitoring con- struct can be combined to provide descriptions of the characteristic strategies practiced by high and low self—monitoring individuals. High self-monitoring individuals strive to create an image appro- priate to the social and interpersonal forces of the situation. The high self-monitoring strategy gives the individual the flexibility to cope quickly and effectively with shifting role and situational de- mands. Situational information can be thought of as figural against the ground of dispositional information which the individual uses to construct his/her unique self-presentation. Low self-monitoring individuals, on the other hand, strive to choose words and deeds which most accurately reflect and communicate relevant attitudes, feelings, and personal dispositions. They would manifest substantial congruence between their dispositions and beha- viors. Characteristic self-attributes serve as figure against the ground of information about the current situational context which the individual uses to construct his/her unique self-presentation. 44 Situations and Strategies Self-monitoring need not be exclusively linked to the self- monitoring strategy of the individual. Self-monitoring research not only demonstrates ”for whom” situational and dispositional information is particularly relevant, but also suggests that it may be possible to specify when social environments are particularly relevant to the in- dividual. Research by Snyder and Tank (1976) indicates that it is possible to construct social environments that promote characteristic behavior- al orientations of low and high self-monitoring. Snyder (1979) sug- gests that low self-monitoring environments encourage a reflective, contemplative orientation to action and provide normative support for consistency between behavior and belief. High self-monitoring en— vironments sensitize one to the perspective of others, motivate con— cern with social evaluation and conformity with reference group norms, and motivate individuals to adopt a strategic impression management orientation. Early sections of Chapter II stressed the social nature of the classroom and the interaction of roles and personalities (Getzels and Thelen, 1960). This description suggests that the classroom is a high self-monitoring environment. Because the Self-Monitoring Scale de- veloped by Snyder employs general social situations to measure the self-monitoring construct, it may also be useful to rewrite the scale in terms of the high self-monitoring environment of the classroom. Need for an Additional Personality Variable The Self—Monitoring Scale serves two related functions. First, it delineates individual differences in sensitivity to situational 45 influences on self-presentation. Second, self—monitoring appears to function as a moderating variable which identifies "for whom" disposi- tions are reliable and salient information for the prediction of be- havior. In order to consider the second function of self-monitoring in this investigation, a complementary personality measure, locus of con- trol, was selected. As explained in the next section, locus of con- trol may have an influence on an individual's ability to manage a classroom. Furthermore, this influence may be moderated by self- monitoring. Locus of Control Social learning theory draws heavily from behaviorism. It recog- nizes the critical role of reinforcement, reward, and gratification in the learning process. It differs from behaviorism in that it stresses the individual's perception of reward. That is, does the individual perceive a reward as contingent upon his/her behavior, or controlled by outside forces? Social learning theory assumes that individuals differ in the degree to which they attribute reinforcement to their own action. Phares (1957) was the first to attempt to measure individual dif- ferences in a generalized expectancy or belief in external control. Phares' investigation indicated that knowledge of an individual's per- ception of control was useful for predicting the type of judgments made in response to success and failure in a given task. James (Note 7) subsequently developed a larger and more reliable scale. Rotter, Seeman, and Liverant (1962), in turn, revised the scale used by James. The final revision was a 23-item forced choice scale 46 subsequently known as the Rotter Internal-External Control Scale (often referred to as the I-E Scale) (Rotter, 1966). The locus of control construct which serves as the focus of this scale refers to the extent to which an individual feels that he has control over the reinforcemtns that occur relative to his behavior. Externals feel that forces beyond their control are the essential factors in determining the oc- currence of reinforcements (such forces might include fate, chance, powerful others, the complexity of the world or its unpredictability, etc.). Internals, however, tend to feel that they control their own destiny and are the effective agents in determining the occurrence of reinforcement (Phares, 1965). Scale Characteristics The I—E Scale is considered to be an additive scale. That is, the scale represents an attempt to sample beliefs across a large range of situations. Rotter (1966) has summarized research on the statis- tical properties of the scale. According to his summary, internal consistency estimates range from .65 to .76 and test-retest reli— ability ranges from .49 to .83. Mean level scale scores range from 5.48 to 10.00. According to Phares (1976), college population means tend to be about 7.5 to 8.5. Characteristics of Internal-External Individuals There is a clear parallel between descriptions of effective classroom managers and those of internally-oriented individuals. As described earlier, effective classroom managers are more likely than less effective managers to be active, alert, and directive in attempt- ing to control and manipulate their classrooms (e.g., Kounin, 1977; Anderson, Evertson, and Emmer, Note 5). In addition, effective mana- gers are assumed to participate more actively in efforts to change the 47 social environment. Locus of control research has shown that the per- sonal qualities identified in the foregoing assumptions are character- istics of internally-oriented individuals. Seeman and Evans (1962) focused on the relationship between locus of control and the knowledge and information-seeking behavior of hos- pital patients. They found that internals knew more about their condi- tions, were more inquisitive, and indicated less satisfaction with the amount of information they were receiving than externals. Two related studies by Seeman (1963, 1967) and Davis and Phares (1976) supported the notion that internals gather more information and are more knowl- edgeable, in terms of personally relevant information, than externals. Research conducted by Phares (1965) concluded that internal sub- jects are able to exert more influence upon others than are external subjects. In other words, internal subjects are more effective than externals in influencing the attitudes of others. If, as research suggests, internals gather more information and tend to exert more social influence upon others than externally-oriented individuals, then it seems logical to expect a relationship between locus of con- trol orientation and helping behavior. Evidence for this assertion is provided by Midlarsky (1971). He concluded that an internal orien— tation was associated with helping even when the helper could expect little materials gain. The studies reviewed here are only a smattering of locus of con- trol research. For a more complete review of research see Rotter, Chance, and Phares (1972); Lefcourt (1976); or Phares (1976). The purpose of this review has been to establish the potential link between an internal locus of control and the successful management of classrooms. Interaction of Self-Monitoring and Locus of Control Self-monitoring purports to (a) identify individuals who are par- ticularly sensitive to the social context, and (b) operate as a moder- ating variable which identifies "for whom" dispositional information will be most salient and relevant. An internal locus of control orientation is hypothesized to be a beneficial dispositional factor influencing the classroom management behavior of teachers. In order to explain the interaction of these two presage variables and the be- havioral consequences of the four combinations of variables, a proto- typic description will be presented. Figure 5 provides an overview of the four presage variable combinations. Locus of Control External Internal Self-Monitoring High Group Group I II Group Group Low IV III Figure 5. Self-monitoring x locus of control subgroups. Group I consists of individuals with a high self-monitoring score and an external locus of control orientation. Prototypic Group I individualswould be sensitive to social situations and able to tailor their self-presentations to the demands of a changing social 49 situation. If self-monitoring operates as a moderating variable, the members of this group should be relatively unaffected by their inter- nal states. Thus, the effects of an external locus of control orien- tation would be mitigated. The classroom management behavior of this group should, therefore, be best predicted from their levels of self- monitoring. That is, they should be relatively effective managers who use the social interaction cues to construct their self-presentations. Group II consists of individuals with high self—monitoring scores and internal locus of control orientations. Prototypic Group II mem- bers would be sensitive to situational influences and able to vary their self-presentations to meet the demands of a changing social context. To the extent to which internal dispositions may influence behavior, an internal locus of control orientation should have a positive effect on the individuals' classroom management behaviors. In brief, members of this group have well developed repertoires of self-presentational skills and would likely be the most effective classroom managers. Group III consists of individuals with low self-monitoring scores and internal locus of control orientations. The prototypic Group III individual would be more affected by personal traits and less sensi- tive to situational influences. They would view themselves as ef- fective agents in determining the outcomes of their behavior and are likely to exert social influence upon others. In brief, their inter- nal characteristics would enable them to be relative effective class- room managers. Group IV consists of individuals with low self-monitoring scores and external locus of control orientations. Prototypic Group IV 50 individuals would be more affected by personal traits and less sensi- tive to situational influences. These individuals would view them- selves as controlled by outside forces and would be less likely to exert social influence upon others. They are, therefore, theorized to be the least effective classroom managers. Summary: Self-Monitoring and Locus of Control The traits versus situation controversy in psychology prompted the development of the Self-Monitoring Scale (Snyder, 1979). Self- monitoring measures individual differences in sensitivity to social contexts and functions as a moderating variable which defines "for whom" dispositional traits are most apt to be relevant. Research in- dicates that high self-monitoring individuals are more likely to be flexible in their abilities to adapt their self-presentations to the needs of the social context than is true for low self-monitoring indi- viduals. Locus of control is a personality measure that may interact with self-monitoring. An internal locus of control orientation has been shown to be associated with greater information gathering, exertion of social influence upon others, and positive helping behaviors. It was, therefore, hypothesized that teachers who are high self-monitors and have an internal locus of control orientation are likely to be the most successful classroom managers. Conversely, those who are low self-monitors and have an external orientation are likely to exhibit the lowest levels of success as classroom managers. 51 Chapter Summary Getzels and Thelen (1960) view the classroom as a social system in which behavior is a function of institutionally defined roles and individual personalities. This interaction defines the group climate or milieu. There is clear evidence that a classroom climate charac- terized by the application of a flexible managerial role will facili- tate positive student behaviors (e.g., Anderson, 1939; Amidon and Flanders, 1963; and Crocker, 1974). The classroom management observation system developed by Kounin (1977) provides a measure of a teacher's success in establishing this climate and gives rise to the four criterion variables in this inves- tigation. Kounin has demonstrated that these behaviors promote stu- dent work involvement and freedom from deviancy. The work of Brophy and Evertson (1976) and Anderson, Evertson, and Brophy (Note 2) fur- ter extend Kounin's work by linking these variables to student academic and attitudinal outcomes. The psychological controversy concerning the relative importance of persons and situations led to the development of the Self-Monitoring Scale (Snyder, 1979). Snyder suggests that individuals differ in the extent to which situational and dispositional factors influence beha- vior. High self-monitoring behavior is characterized by the ability to quickly cope with shifting role and situational demands. On the other hand, low self-monitoring behavior is characterized by cross- situational consistency. In addition, the self-monitoring construct serves as a moderating variable which identifies individuals who are most likely to be affected by their internal dispositions. 52 The personality variable, locus of control, refers to individual differences in reinforcement expectations and may interact with self- monitoring. Individuals with an external orientation attribute rein- forcement to forces beyond their control. Individuals with an inter- nal orientation feel that they control the occurrence of reinforce— ment. Inferences based on the classroom management research of Brophy and others suggest that the personal characteristics associated with high self-monitoring and an internal locus of control orientation should promote successful classroom management behavior. These in- ferences give rise to a set of predicted relationships between the two presage variables, self-monitoring and locus of control, and the four measures of classroom management. Chapter III describes the design and implementation of research which tests hypotheses based upon these predicted relationships. CHAPTER III METHODOLOGY An ability to demonstrate significant relations between presage variables and classroom management behaviors of teachers would make an important contribution to educational research. Kounin (1977) has linked teacher classroom behavior to student work involvement and freedom from deviancy. In addition, Anderson, Evertson, and Brophy (Note 2) have linked classroom management behavior to student learning and attitudes. Since teacher behavior is assumed to be a function of presage variables, the study of the relationship between presage vari- ables and teacher classroom management behavior is an important area of study. This investigation, which attempts to demonstrate the link be— tween a potentially important presage variable, self-monitoring, and classroom management behaviors focuses on this causal link in the Dun- kin and Biddle (1974) model. The procedures employed in the implementation of the research de- sign of this investigation are described in this chapter. The chapter consists of seven sections and is concluded with a summary. The sec- tions are (a) an overview, (b) a description of Phase I (testing), (c) a description of Phase II (observation), (d) instrumentation and instrument reliability, (e) observer training, (f) data collection, and (g) hypothesis/data analysis. An Overview This investigation was conducted in two phases. Phase I involved two steps: (a) the development of the Classroom Self-Monitoring Scale 53 54 and (b) a study to determine the reliabilities of the Self-Monitoring and Classroom Self-Monitoring Scales when administered to classroom teachers. Phase II, the main research project, was designed to test hypotheses concerning the relationship between selected presage vari- ables and classroom management beahviors. Instrument development in this phase focused on measures of classroom management behaviors. Prior to conducting Phase II, Kounin's (1977) system for observing classroom behaviors was modified and field tested. In view of this emphasis on the development of new or relatively untested measures, reliability data were compiled on the four research instruments: the Self-Monitoring Scale, the Classroom Self-Monitoring Scale, the Internal-External Locus of Control Scale, and the Classroom Management Observation System. Phase I In order to develop the Classroom Self-Monitoring Scale and to establish its reliability, a comparatively large sample of classroom teachers was needed. Early in February, 1980, arrangements were made to administer the original and the Classroom Self-Monitoring Scales to a graduate class of 34 practicing teachers. The scales were administered during two class periods scheduled at one week in— tervals. One-half of the participants were randomly administered the Self- Monitoring Scale during the first class period while the other half were administered the Classroom Self-Monitoring Scale. The following week the alternative form was administered to the two groups. Because of fluctuating attendance, the final sample contained 32 members. 55 Two respondents left one question unanswered on the Classroom Self-Monitoring Scale, and one respondent left a question unanswered on the Self-Monitoring Scale. The mean score for all respondents on those questions was substituted for the unanswered questions in deter- mining scores for these three individuals. Effects of Text Taking Order An analysis of variance was done to determine if test taking order affected scores on the Self-Monitoring Scales. The results of these analyses are summarized in Table 1. As these results suggest, the or- der of test taking had little or no influence on the scores on either test. In order words, responses to items on either scale do not ap- pear to be influenced by the experience of completing the other in- strument. Following an extensive item analysis (to be described in the in- strumentation section), five items were deleted from the Classroom Self-Monitoring Scale. Therefore, an analysis of variance test was also computed to examine the potential influence of test taking order on the 20—item form of the Classroom Self-Monitoring Scale (see Table 1). Once again, the order of test taking did not appear to influence the scores. The apparent lack of influence of test taking order was important to the design of the main research study. In the main study the order of test taking was predetermined. As a result of this analysis, it was reasonable to assume that the Phase II sample's test scores were not affected by that order. 56 Table 1 Mean Difference in Test Taking Order Instrument p_ Test Order M_ Efratio Self-Monitoring Scale 15 l 14.64 .62 17 2 13.53 Classroom S-M Scale 15 1 13.53 (25-item) .10 17 2 13.15 Classroom S-M Scale 15 l 11.13 (20-item) .09 17 2 10.76 Phase I Sample A demographic data form (see Appendix Al) was completed by 33 of the 34 teachers in the pilot study. All respondents were public school teachers with 61% elementary teachers, 18% high school teachers, and one special education teacher. Sixty-one percent of the teachers had taught five or fewer years, and 49% were 30 years old or less. For a more complete description of the demongraphic characteristics of the pilot sample, see Appendix A2. Phase II In most applied research studies, a compromise must be struck be- tween the desire for a large sample that will maximize generalizabil- ity of results and practical conditions such as the number of poten- tial volunteers, time demands in collecting data, and other factors that tend to restrict sample size. This study is no exception. Dif- ficulties in identifying volunteers coupled with the heavy time 57 requirements posed by repeated classroom observations suggested the desirability of a relatively small sample. On the other hand, the focus of statistical analyses on correlation coefficients suggested the need for a relatively large sample. Power curves for the Pearson- product moment correlation coefficient suggest that samples of 12 or more individuals should yield ”reasonably stable" estimates of correlations between two variables. This figure was, therefore, used as the minimum sample size that would be acceptable. Selection of Schools The investigator contacted the Office of Evaluation Services in a medium size (31,630 students and 1,545 teachers), urban school dis- trict in an attempt to identify 12 or more teachers who might be will- ing to participate in the study. The district that was selected is located in a Midwestern community and is generally made up of blue collar workers. The director of the Office of Evaluation Services agreed to pre- sent the research proposal and an application to conduct research (see Appendix B1) to the research committee for approval. The original application requested a random sample of 10 of the 40 elementary schools. This proposal was unacceptable to the committee. An alter- nate application (see Appendix B2) was, therefore, developed and pre- sented to the committee. This compromise called for contacting two principals who would allow the researcher to make a presentation to their staffs and ask for volunteers. This proposal was approved. The two schools that were identified were each comprised of 16 K-6, self- contained elementary classrooms. 58 Selection of Subjects The research depended upon the voluntary cooperation of teachers. Therefore, an outline of the proposed research design(see Appendix B3) was presented to each staff, and a group presentation was made. Seven teachers in one school and five teachers in the other school volun-- teered to be involved in the research. The investigation initially planned to select 12 teachers on the basis of their scores on the Self-Monitoring Scale (six highest and six lowest scores). Since only 12 teachers volunteered, this feature of the research design was abandoned. Four weeks after the research was begun, three teachers in one school changed their minds and decided not be involved in the research. Two teachers cited possible disruption of their classrooms as a reason for withdrawing from the research, and the third teacher was suspi- cious of the Self-Monitoring Scale. Therefore, the final sample con- tained only nine classroom teachers, seven from one school and two from the other. Description of the Sample The nine teachers were of mixed racial backgrounds (2 minorities), and all were female. The distribution of teachers according to years of experience, grade level taught, and educational level is presented in Table 2. Instrumentation/Reliability The research instruments employed in this study included the Self-Monitoring Scale, the Classroom Self-Monitoring Scale, the Inter- nal—External Locus of Control Scale, and the Classroom Management 59 Table 2 Demographic Characteristics of the Phase II Sample Years of Experience .2;4 8-10 21-28 p_ 3 2 4 Grade Level Taught l_ __ §_ 4_ §_ p_ l 1 3 Educational Level BA_ Working on MA .MA n 2 4 3 Observation System. The following subsections describe the develop- ment of the Classroom Self-Monitoring Scale and the Classroom Manage— ment Observation System and evidence of the reliability of all four instruments. Self-Monitoring Scale The Self-Monitoring Scale was developed by Mark Snyder (1974) and consists of a set of 25 true-false, self—descriptive statements (see Appendix C). It purports to measure an individual's (a) gppgpg tiveness to the actions of others in social situations, (b) motivation to seek out relevant social comparison information, and (c) ability to translate beliefs about what constitutes a situationally appropri- ate self—presentation into action. Chapter II provides a detailed description of this scale. In order to establish the reliability of this instrument for classroom teachers, Chronbach's (1951) coefficient alpha was computed for the 32 teachersirlthe Phase [sample and for the nine subjects in the Phase II sample. Coefficient alpha is algebraically equiva— lent to the Kuder-Richardson formula 20 (K-R 20). The coefficient 6O alpha of the Self-Monitoring Scale was .65-finnthe Phase [sample of 32 teachers and .82 for the nine teachers in the Phase II sample. Work- ing with a sample of 192 undergraduates, Snyder (1974) established a K-R 20 reliability of .70 and a test-retest reliability of .83 (one month time interval) on his 25-item Self-Monitoring Scale. A cross- validation study on an independent sample of 146 subjects yielded a K—R 20 reliability coefficient of .63. Thus, the reliability findings for both Phase I and Phase II were generally consistent with those reported by Snyder. Evidence of the construct validity of the Self-Monitoring Scale has been provided by an analysis of the convergence of diverse methods of measuring self-monitoring. Four studies were conducted by Snyder (1974) to establish construct validity. His analysis focused on (a) peer group ratings, (b) prediction of self-monitoring scores of pre- determined groups of individuals, (c) differential ability of high and low self-monitors to control expressive behavior, and (d) differ- ential ability of high and low self-monitors to infer the affective and emotional status of others. For a complete review of the four sets of studies, see Chapter II. In addition, evidence of the discriminant validity (see Campbell and Fiske, 1959) of the Self-Monitoring Scale was provided by direct comparisons between self-monitoring and need for approval, extraver- sion, locus of control, and other measures in the prediction of a variety of external criterion variables. A strong and reliable rela- tionship between self-monitoring and the criterion measures emerged, but effects of the other predictor variables were trivial and 61 statistically insignificant. For a complete review of the converging discriminant validity investigations, see Chapter II. Classroom Self-Monitoring Scale In order to test some of the theoretical conjectures outlined in Chapter II, a Classroom Self-Monitoring Scale was developed by the author (see Appendix D1). All but one (number 18) of the 25 true- false, self-descriptive statements on Snyder's scale were rewritten in terms of specific classroom applications. For example, the statement ”I find it hard to imitate the behavior of other people" was rewritten to read ”I find it hard to imitate the behavior of other teachers.“ The construction and use of a Classroom Self-Monitoring Scale was an attempt to place the use of self-monitoring strategies in the context of the classroom environment. The coefficient alpha of this 25-item scale was .53 for the 32 teachers in the Phase [sample. This value was judged to be unaccept- ably low. The point-biserial correlations (relations between re- sponses to each item) were, therefore, examined in an attempt to iden- tify items that may have detracted from the internal consistency of the scale (see Appendix DZ). Five items (statement numbers 7, 13, 14, 15, and 20) with atypically low point-biserial correlations were identified. When these five items were omitted, the alpha level for the modified 20-item scale increased to .66. Fortunately, the dele- tion of these five items should not alter the content validity of the Classroom Self-Monitoring Scale since each question came from a dif- ferent subsection of Snyder's Self-Monitoring Scale. 62 The 20-item Classroom Self-Monitoring Scale (see Appendix E1) was, therefore, used in Phase II. Unfortunately, however, the coef- ficient alpha for the Phase II sample of nine teachers was only .28. Further analyses suggested that point—biseral correlations for two of the items (statement numbers 5 and 20) were unusually low (see Appen- dix E2). When these two items were omitted, the coefficient alpha for the lB-item scale increased to .66. Therefore, the relationship be- tween scores on the 18-item Classroom Self-Monitoring Scale and each of the classroom management measures was examined. The four correla- tion coefficients ranged from a low of 5.: -.01 for smoothness to a high of 3.: .20 for momentum. None of the correlations was signifi- cantly different from zero when alpha was fixed at .05. A complete presentation of this analysis can be found in Chapter IV. Although these analyses suggest that the properties of the scale maylxaimproved through further revisions, the author elected to use the 20-item scale in analyses reported in Chapter IV. This decision was based in large measure on the instability of correlationsal measures for small group samples. Internal-External Locus of Control Scale The Internal—External Locus of Control Scale (I-E Scale) was de- veloped by J. B. Rotter in 1966 (see Appendix F). It is a 29-item forced choice questionnaire with six filler items intended to make the purpose of the test ambiguous. The Rotter I-E Scale was adapted from a 60-item scale developed by James (Note 7). Locus of control is a mediating expectancy variable which de- scribes the extent to which an individual feels that he has control over the reinforcements that occur relative to his behavior. One 63 characteristic of the internal-external orientation of individuals is of particular interest to this research. Phares (1965) validated the assumption that internals are more able to exert influence upon others in a social situation than are externals. The locus of control con- struct was chosen for use in this research because the process of classroom management involves the exertion of influence by teachers upon students in the social environment of the classroom. Reliability of the I—E Scale was determined for the Phase II sam- ple only. The coefficient alpha for the nine teachers in this sample was .64. The correlation between scores on the I-E Scale and the Self-Monitoring Scale was .06; the corresponding correlation with scores on the Classroom Self-Monitoring Scale was .25. These correla- tions were generally consistent with the correlation between self- monitoring and locus of control (§_= .19) reported by Snyder (1975). Phares (1976) reports that internal consistency estimates for the I-E Scale range from .65 to .79 and that test-retest reliabilities range from .49 to .83. Thus the reliability findings for the main research study were also generally consistent with those reported by Phares. Table 3 summarizes the reliability data for the pilot sample on the two Self-Monitoring Scales and the I-E Scale. The correlations among scores on the three research instruments are also presented. Classroom Management Observation System For purposes of this investigation, the Classroom Management Ob- servation System developed by Jacob Kounin (1977) was modified by the author. Kounin conducted videotape studies of elementary classrooms 64 Table 3 Test Reliabilities and Interscale Correlations Phase I Study (N = 32) Instrument Reliabilities/Interscale Correlations Self-Monitoring alpha = .65 Classroom S-M alpha = .66 Self—Monitoring/Classroom S-M .n = .69* Phase II (N = 9) Self-Monitoring Classroom S-M I-E Scale Self-Monitoring alpha = .82 :_= .70* p_= .06 Classroom S-M alpha = .28 §_=—.25 I-E Scale alpha = .64 *p‘<.Ol and delineated a set of teacher classroom management behaviors which positively correlated with student work involvement and freedom from deviancy. Through personal contact with Kounin, it was determined that the videotape observation forms were no longer available. A new system, specifically applicable to live observations, was, therefore, developed. Four of Kounin's most significant categories of teacher management behaviors were included in this new system: withitness, overlapping, momentum, and smoothness. To facilitate observer training, a Guide for the Judgment of Teacher Classroom Behaviors (see Appendix Gl) and a Classroom Observation Instrument (see Appendix G2) were developed. Descriptions of the codes used in the guide were taken directed from Kounin's (1977) work. In addition, other forms such as a Daily 65 Observation Schedule were developed in order to facilitate data col- lection procedures (see Appendix G3). Inter-rater reliabilities of the Classroom Management Observation System were determined by correlating subscale scores recorded by two observers during a joint observation of each teacher in the sample. The Observation Schedule (to be discussed in the data collection sec- tion of this chapter) determined when joint observations were to take place. The findings of this analysis are presented in Table 4. Table 4 Classroom Management Observation System Inter-Rater Reliabilities (N_= 9) Management Measure Inter-Rater Reliability Withitness .91* Overlapping .93* Smoothness .92* Momentum .33 *p (.01 The inter-rater reliabilities for three of the classroom manage- ment measures were above .90 and are very similar to intercoder agree- ment reported by Kounin (1977). The reliability of the momentum sub- scale, on the other hand, is considerably lower than that of the other three subscales. The observers found momentum to be the least well defined of the four management measures and experienced difficulty in deriving scores for this variable. 66 Observer Training Use of the Classroom Management Observation System required the training of two classroom observers. The researcher used the follow- ing criteria in selecting observers: (a) ability to spend the amount of time required for training, (b) knowledge of schools, (c) sensitiv- ity to the behavior of others, and (d) demonstrated commitment to the research. Two such observers were available. One was a private school administrator and the other (the researcher) an experienced elementary classroom teacher. The researcher was fortunate to have access to a large library of classroom videotapes. These tapes were reviewed, and instances of positive and negative teacher management behavior were edited into a single videotape. Over a three week period, the observers viewed the videotape, practiced scoring, and discussed the teacher's behavior. As a final exercise, the trainees observed a live classroom which was not part of the research sample and refined their observation techni- gues. Data Collection Data collection in Phase II consisted of five components: (a) administration of the Self-Monitoring Scale, (b) classroom observa- tions using the Classroom Management Observation System, (c) adminis- tration of the Classroom Self-Monitoring Scale, (d) administration of the Internal-External Locus of Control Scale, and (e) interviews. Administration of the Self-Monitoring Scale Although administration of the Self—Monitoring Scale was initial- ly designed to assist the researcher in selecting participants for the 67 research project, the fact that only 12 teachers volunteered negated this purpose. The instrument, nevertheless, served two other impor- tant functions. First, the Self-Monitoring Scale played a major role in determin- ing classroom observation schedules. The Observation Schedule (see Figure 6) was structured according to three blocks of observations where each block represented a level of performance on the Self- Monitoring Scale. Teachers were assigned to blocks using stratified random assignment procedures. By structuring observations in this manner, the likelihood that order of observation or level of self- monitoring would influence scores on the classroom management scales was minimized. This blocking was also important in establishing inter-rater re- liabilities. As noted earlier, each teacher was observed by both re- searchers during one class period. The counterbalanced design of scheduling for two-person observations minimized the possibilities that order of observations and level of self-monitoring would in— fluence estimates of inter-rater reliabilities. The second and most important purpose for administering the Self— Monitoring Scale was to test the set of research hypotheses described in a later section of this chapter. It is important to note that the observers did not have knowledge of the individual teachers' self- monitoring scores at the time they observed classroom management be- haviors. Classroom Observations Classroom observations were conducted during a four month period (February through May). The Observation Schedule served as the guide 68 Number of Observers Level of Observations Self-Monitoripg l§§_ 2pg_ §5g_ Observer an High 2 l l 01 ,§<§ 2 l 1 02 °° Low 2 l l 01 2 l l 02 _x High 1 2 l 01 .§1§ 1 2 1 O2 °° Low 1 2 1 01 1 2 1 02 is a “'9“ 1 1 3 82* O S. I; '15 Low 1 l 2 01* l l 2 02* Note: * indicates a teacher who withdrew from the study. Figure 6: Observation Schedule. for observations in each classroom. All teachers were informed of the schedules for their classrooms. Arrangements for each observation were finalized with teachers the day before the observers were to en- ter the classrooms. Observers positioned themselves in the rear of the classroom and attempted to be as unobtrusive as possible. The length of each ob- servation was determined by the length of the class period. The average time spent observing was approximately one-half hour. Seat- work time was not observed. All observations took place in the morn- ing. The primary purpose of the observations was to generate measures of classroom management behaviors of the nine teachers in the sample. 69 Individual observation scores were computed for each of the four classroom management subscales following the completion of the set of three observations. The following formulas were used: Mistake Free Desists Total Number of Desists Withitness = Events Coded ”Some Overlapping” Overlapping = Total Number of Overlapping Events Number of Six Second ” lowdown“ Units Coded Momentum = 1’ Total Number of Six Second Units 1_ Number of Six Second “Jerkiness” Incidents Tota Number of Six Second Units Smoothness = General classroom management scores were computed for each teacher in the research sample following the final observation. These scores represent a summary of the teacher's performance across the three les- sons that were observed. Because there were two observers during one of the three lessons and only one observer during the other two les- sons, the following formula was used to determine general classroom management scores: General Management 2 (E of the four observation scores) - Scores (5 of the two joint observations) Administration of the Classroom Self— Monitoring Scale and Internal-External Locus of Control Scale The final two scales were administered during the latter part of the observation process. Scoring of these scales did not take place until all observations were complete. This minimized the possibility that observers would be influenced by participant scores. 70 An Interview Following the final observation, a taped interview was conducted with each participant. A copy of the interview is provided in Appen- dix H. Background information was collected, and open-ended questions concerning selected aspects of teaching such as "What are your great- est strengths as a teacher?” were raised. At the conclusion of each interview, the researcher reviewed the teacher's scores on the class- room management, self—monitoring, and locus of control measures. Summary Chapter III provided a description of the design and conduct of this investigation. The research consisted of two phases. Phase I was the development of the Classroom Self-Monitoring Scale and the determination of the reliability of the two Self-Monitoring Scales for a relatively large sample of classroom teachers. A description of the Phase I sample and findings regarding the potential influence of test taking order were presented. Phase II focused on the collection of data needed to test the hypotheses concerning the relationship between selected presage vari- ables (self-monitoring and locus of control) and teacher classroom management behaviors. In addition, the chapter provided a description of observer training, research hypotheses, and the statistical analy- ses that were used. CHAPTER IV ANALYSIS OF RESULTS The results of this investigation are summarized in four major sections of this chapter. The first section presents the results of simple correlational analyses, the second section presents the results of multiple regression analyses, and the third section summarizes analyses of group means. The final section provides a summary of the findings. Correlational Analyses Computation of a Pearson-product moment correlation matrixinvolv- ing both predictor and criterion variables served as the basis for testing Hypotheses I, III, IV, V, and VI. Distinct sections of this matrix summarize measures of the relations between predictor and cri- terion variables (Hypotheses I, III, and IV), among measures of class- room behaviors (Hypothesis V), and among measures of presage variables (Hypothesis VI). Relations Between Predictor and Criterion Variables One of the primary hypotheses of this investigation concerns the effects of self-monitoring on the classroom management behaviors of teachers. Self-monitoring is hypothesized to be significantly related to the management measures. Two of the secondary hypotheses concern the magnitude of the relationships between the predictor and criterion 71 72 variables. The predictor variables are hypothesized to be related to the management measures in the following hierarchical order: withit— ness, overlapping, momentum, and smoothness. The predictor variables are hypothesized to be related to the criterion variables in the fol- lowing hierarchical order: classroom self-monitoring, self-monitor- ing, and locus of control. Hypothesis I. The magnitude of the simple correlations between self-monitoring and each criterion measure will be significantly greater than zero. ESw'> zero 30> zero LSm) zeY‘O £55 > ZEY‘O Note: Subscripts: S = self-monitoring, w = withitness, o = overlap- ping, m = momentum, s = smoothness Hypothesis III. The magnitude of the simple correlations between each predictor variable and each criterion variable will vary in a consistent order. Corollary 3a: Simple correlations between self-monitoring and each criterion measure will vary in the following order: ESw (withitness),> [30 (overlapping)>? ESm (momentwn)> 35$ (smoothness) Corollary 3b: Simple correlations between classroom self- monitoring and each criterion measure will vary in the followingcwder: _pr (withitness)> .350 (overlapping):> ECm (momentum)> [£5 (smoothness) Corollary 3c: Simple correlations between locus of control and each criterion measure will vary in the following order: ELw (withitness)>: F0 (overlapping)>r‘me (momentum)? F5 (smoothness) Note: Subscripts: C = classroom self-monitoring, L = locuscrfcontrol 73 Hypothesis IV. The magnitude of the simple correlations between each predictor variable and the entire set of criterion variables will vary in the following order: (classroom self—monitoring/withitness, and overlapping, r and momentum, and smoothness)> Cwoms r-Swoms (self—monitoring/withitness, and overlapping, and momen- tum, and smoothness)> (locus of control/(withitness, and overlapping, and momentum, and smoothness) l's Lwoms Table 5 summarizes the correlations between predictor and criter- ion variables that served as the focus of tests of Hypotheses I, III, and IV. The predictors were the presage variables classroom self- monitoring, self-monitoring, and locus of control. The criterion variables were the classroom management measures withitness, overlap- ping, momentum, and smoothness. Although the author elected to use the 20-item Classroom Self-Monitoring Scale to analyze the relation between presage variables and classroom management measures, this analysis was also performed using the l8-item scale described in Chap- ter III. This latter scale was suggested by an analysis that demon- strated an increase in the coefficient alpha for the Phase II sample from .28 to .66 when two items were omitted (see Appendix E2). As the data in Table 5 suggest, the correlation coefficients for the 18-item scale were approximately equal to those for the 20-item scale across all four management measures. Other analyses involving the Classroom Self-Monitoring Scale were, therefore, limited to the 20- item version. The data summarized in Table 5 lend limited support for Hypothe- sis I. The correlation coefficients for self—monitoring and the 74 Table 5 Correlations Between Presage Variables and Classroom Management Measures (N_= 9) Classroom Management Measures Presage Variables Withitness Overlapping Momentum Smoothness Self-Monitoring .48 .17 .14 .13 Classroom S-M .09 -.05 .23 -.18 (20 item) Classroom S-M .13 .10 .20 -.Ol (18 item) Locus of Control -.15 .18 .18 -.20 Note: Locus of Control correlations are based on the I-E scale which ranges from low for internals to high for externals. _management measures were positive, but they were not significantly greater than zero when alpha was fixed at .05. Thus, Hypothesis I must be accepted as stated in the null form. Hypothesis III stated that the presage variables would predict the management variables in a consistent order. The pattern of cor- relation coefficients did conform to the order predicted in Corollary 3a where self-monitoring serves as the predictor variable. However, the data provide little or no support for corollaries 3b (classroom self-monitoring) and 3c (locus of control); the predicted pattern of correlation coefficients did not occur for these two predictor vari- ables. Further, since none of the simple correlations between pre- dictor and criterion variables was significantly different from zero when alpha was fixed at .05, it would have been impossible to provide 75 definitive evidence in support of the three corollaries even if the order of correlation coefficients had conformed to the predicted pat- tern. Thus, Hypothesis III and its three corollaries must be accepted as stated in the null form. Hypothesis IV predicted that classroom self-monitoring would be the best predictor of classroom management behaviors. This was not the case. Self-monitoring was the best predictor. Correlations for self-monitoring ranged from a low of .13 to a high of .48; the corre- sponding range for classroom self-monitoring was -.05 to .23. Thus, Hypothesis IV must also be accepted as stated in the null form. Graphic Representation of Correlational Data The correlations between presage variables and classroom manage- ment measures that are summarized in Table 5 were considerably lower than expected. Self-monitoring appeared to be the only promising predictor variable. However, because correlation coefficients pro- vide an index of the degree of linear relationship, there is still a possibility that a nonlinear relationship exists between a given pre- dictor and criterion variable. For these and other reasons that will be described later, relationships between each predictor and each criterion variable were pictorially represented by constructing scat- tergrams. Figure 7 presents the graphic representation of correla- tional data for the three predictor and four criterion variables. An examination of Figure 7 suggests that these data do not con- tradict the earlier findings that (a) a positive statistical rela- tionship may exist between self-monitoring and the management mea- sures and (b) no strong relationship apparently exists between the other combinations of predictor variables and criterion variables. WITHITNESS SHOOTHNESS 76 SCRTTERGRRM: HITHITNESS 9ND SELF-MONITORING 6&3“ 4; - \ 5.500 LOOQ> / / 0 350 : 4%, 47 +47e7 : t 4 #7 0 .200 .400 .000 .000 1.000 SELF—MONITORING SCRTTERGRRH: SHOOTHNESS 8ND SELF-MONITORING 0.0:: h .. 5.flw l / I \ \ 6.000» / \ \ / \\ x l. / / / 8.700) / / O ‘7 0-000‘> J. 5;: e t : 445’ ¢ 4: : t 4 0 .200 Am .000 .000 l .000 SELF-HONITORING OVERLHPPING MOHENTUH SCRTTERGRRH: OVERLRPPING 9N0 SELF-MONITORING 0. A; 5.0001» \ v I O 3.000» , _ \ ’ \ / \ / \ «p / \ \ / \ 2-000" / \ / \ \ v41- 0 130 t t ; : e c t : 200 .400 .000 .0” 1.000 SCRTTERGRRH: MOMENTUH FIND SELF-MONITORING s... < : SELF-MONITORING I \ \ o ’ I ‘ ‘ ~ ... ... v ’ O ‘F/o—fl/ 5.000” f ..... ‘ o I I O x \ \ I / O ‘ 1’ ‘ I \ / A manor 5.600” (- SOZWP ir s.-- : 4:7 t :7 : : t t 0 .2” m .0” .000 I.” SELF-MONITORING HITHITNESS HOHENTUH SCRTTERGRRH: 77 HITHITNESS 9ND CLRSSROOH S-M 5.500" 5 .000“ 4 .500" 4 .0001t 3.530 A / 0 J \ A A L L 0 r ipo‘f .400 Y .000 .000 1.000 CLRSSROOH SELF-MONITORING SCHTTERGRRH: HOHENTUH RNO CLRSSROOH S-H 0;: : S .000 0.000» / \ / \ / / 0.400y 41 0.200» 0 suwv c 4: 404 ¢ A .4444 4 .4 o .200 .000 .000 .000 1.000 \o CLBSSROOH SELF-MONITORING OVERLRPPING SHOOTHNESS SCHTTERGRRH: OVERLHPPING 9ND CLRSSROOH S-H 0.0: c \ / \ /° ‘ 0 5.000» 0 0.000» 0 o 0 0 30000" ~ / \ 4)- / \ / \ 2.000» / / ° \ 1.0: 0 .500 I .100 1.000 I .000 ‘ 1.000 CLRSSROOH SELF-MONITORING SCHTTERGRRH: SHOOTHNESS 9N0 CLRSSROOH S-H 0w 3* 0.000» / ’ \ 0.00m / \ / \ o / \ / \ 0.700» / \ / o 4 / \ smm» \ ’ \ 5.53.. A 3 3 3 3 3 3 3 3 0 .200 .000 .000 .000 LEW CLHSSRUOH SELF-HONITORINO 78 22 7 IO LOCUS OF CONTROL (EXTERNRL TO INTERNRL) SEEIJERGRRH: HITHITNEES 9ND LOCUS OF CONTROL SCRTTERGRHH: OVERLRPPING RNO LOCUS OF CONTROL .-.. v 0.2: : \ o o / 4» 0 / o o 0 \”’° 5.000» 0.000» 0 1. 0.000» e , 3 g m S .. ’T\ & z / A : / \ E 3 / \ ° / \ / \ / 4.000» / \ 2.000» / \ / \ \ / \ / \ o / ° / 3.50 : : 4 e t 1.33 . : ‘ o 7 u 22 7 ‘14 ' 22 LOCUS OF CONTROL [EXTERNRL TO INTERNRL) LOCUS OF CONTROL (EXTERNRL TO INTERNRL) scniTERoRnn: nonENTUH gNo LOCUS OF CONTROL SCRTTERGRAH: SHOOTHNESS RND Locus OF CONTROL 0.3: x : ...... 3. \ / \‘~_p’/ ° 0 o {h o o o o o 0.000» "’°°’ o I " ¢ ‘ o \ / \ \ 1’ / / \ \ N 1’ _ / / I \ \ 0.000» / / a: 5400' / \ s / E ’ \ e / a . ’ \ LE, 4. / o / \ o / o / I: t w / \ 0.000» 0.700» / / \ / 0 g .. \ \ 0.200» 0.000» 5.0:- ¢ 444: ‘ S-va 4* : 7 x 22 . 0 LOCUS OF CONTROL (EXTERNRL TO INTERNHL) Note: The scale on the X axis is reversed for the Locus of Control measure (i.e., 22 = O and O = 22). Figure 7. Graphic representation of the relationships between pre- sage and criterion variables. 79 Given the small sample size, it is difficult to determine whether the relation between the predictor variables and the management measures can be described as linear or curvilinear. Thus, these figures also support the earlier interpretations of findings for tests of Hypothe- ses I, III, and IV. Relations among Criterion Measures The four classroom management measures may be classified into two categories. Withitness and overlapping concern ”deviancy management,” and momentum and smoothness describe "movement management." Therefore, the relationship between measures in these two categories are of in— terest in this investigation. These relations serve as the focus of Hypothesis V. Hypothesis V. The magnitude of intercorrelations among the four classroom management measures will conform to the following patterns: Corollary 5a. The simple correlation between the two de- viancy management measures (withitness and overlapping) will be greater than correlations between either of those measures and the two move- ment management measures (momentum and smoothness): 1 r r r r > (rwm O —ws 0 3-0m 0 -£ E-wo os Corollary 5b: The simple correlation between the two movement management measures (momentum and smoothness) will be greater than the correlations between either of these measures and the two deviancy measures: r or r or r or r Ems) (—mw —mo -—sw ~50) Table 6 summarizes the intercorrelations among the criterion variables cited in Hypothesis V. 80 Table 6 Intercorrelations among Classroom Management Measures (N_= 9) Overlapping Momentum Smoothness Withitness .75** .63** .90** Overlapping .57* .86** Momentum .57* * p < .05 ** p < .01 An examination of Table 6 indicates that all of the correlations among criterion measures were significantly different from zero when the alpha level was fixed at .05. Unfortunately, however, the rela- tive magnitude of these correlations does not provide support for Hypothesis V. The correlations involving the management measure smoothness were far higher than predicted and, therefore, the key fac- tor in the decision to accept Corollary 5a as stated in the null form. The relative magnitude of correlations between this variable and the two deviancy management measures (withitness and overlapping) were also the key factor in the decision to accept Corollary 5b as stated in the null. Relations Among Predictor Variables One objective of this investigation was to construct a classroom version of the Self—Monitoring Scale which was similar, but not paral- lel to, the Self-Monitoring Scale. This served as the basis for Hypothesis VI. 81 Hypothesis VI. The simple correlation between classroom self- monitoring and self-monitoring will be greater than .40, but less than .60. .40< [ CS (classroom self—monitoring/self-monitoring)< .60 The Self-Monitoring Scale and the Classroom Self-Monitoring Scale were administered to two groups of classroom teachers. The correla- tion between these two measures was .70 for the Phase I sample (N_= 32) and .79 for the Phase II sample (N_= 9). Both of these cor- relation coefficients were significantly different from zero when alpha was fixed at .01. However, since both exceeded the upper limit of .60 suggested by Hypothesis VI, this hypothesis must be accepted as stated in the null form. In other words, the obtained correlation coefficients indicate that the two scales were more parallel in na- ture than desired. Multiple Regression Analyses Multiple regression analyses were used to determine whether pre— dictions based on all three predictor variables were superior to those provided by any one predictor variable alone. The relative magnitude of multiple correlation coefficients provided by these analyses served as the focus of Hypothesis VII. Hypothesis VII The magnitude of the multiple correlation coefficients between the three predictor variables and each criterion variable will vary in the following order: 82 R1 (classroom self-monitoring + self-monitoring + locus of control/withitness)? .32 (three predictor variables/overlapping)> .33 (three predictor variables/momentum)? 34 (three predictor variables/smoothness) Multiple regression analyses were computed on three separate oc- casions. On each occasion the findings were called into question be- cause the beta weights did not conform to a reasonable pattern as sug- gested by the simple correlations. A specialist in educational sta- tistics was, therefore, consulted in an attempt to identify the source of these questionable findings. It was his opinion that multiple re- gression analyses were inappropriate due to the small sample size. He recommended that the multiple regression analyses should be abandoned in favor of a straight forward examination of simple scattergrams. Figure 7 is the direct result of this recommendation. A table summarizing the multiple correlation analysis can, never- theless, be found in Appendix I. In addition to the problem of ques- tionable beta weights, it should be noted that none of the multiple correlations was significantly different from zero when alpha was fixed at .05. However, the order of the magnitude of the multiple correlations involving all three predictor variables did generally conform to the pattern predicted by Hypothesis VII for three of the criterion measures. Although the results were somewhat encouraging, it is clear that Hypothesis VII must be accepted as stated in the null form. 83 Group Analyses Computation of group means for the criterion variables withitness and overlapping served as the basis for testing Hypotheses II and VIII. Teachers in the Phase II sample were grouped according to their levels of self-monitoring (Hypothesis VIII) and according to their levels of self—monitoring and locus of control orientation (Hypothesis II). Since classroom self-monitoring scores were highly correlated with self-monitoring scores but did not seem to be significantly related to measures of classroom management, only self-monitoring scores were considered in group analyses. In addition, because of the disappoint— ing findings for measures of movement management, only the deviancy management measures were used in group analyses. Self-Monitoring Group Comparisons According to theoretical conjectures described in Chapters I and II, high self—monitors should be more sensitive to situational influ- ences and, therefore, better classroom managers than low self—monitors. The nine subjects were, therefore, grouped according to their scores on the Self-Monitoring Scale. High self-monitoring was defined as a score of .48 (n= 4) or greater, and low self-monitoring was de- fined as a score of less than .48 (p_= 5). The grouping of high and low self-monitoring individuals is consistent with Snyder's (1975) groupings for high and low self-monitors using a median split of .44. General Hypothesis VIII The magnitude of mean scores on the management measures (withit- ness and overlapping) will differ significantly when teachers are grouped according to their levels of self-monitoring. 84 Corollary 8a. The group mean score for withitness will be significantly larger for high self-monitors than for low self-monitors. Corollary 8b. The group mean score for overlapping will be significantly larger for high self-monitors than for low self-monitors Table 7 summarizes the performance of high and low self-monitor- ing teachers for the two measures of classroom management. Table 7 Self-Monitoring Group Means (N_= 9) Withitness Overlapping Groups 2 M E. 3 II a I. High S-M 4 5.83 .17 4.45 1.45 Low S-M 5 5.10 .92 1.73 3.91 1.72 .56 An examination of Table 7 suggests that, as predicted, the mean withitness and overlapping scores for high self-monitors were larger than the corresponding means for low self-monitors. T-tests were, therefore, computed to determine if the observed differences were statistically significant. The results of these tests were also sum- marized in Table 7. Neither test suggests that differences in ob- served means were statistically significant when alpha was set at .05. Hypothesis VIII must, therefore, be accepted as stated in the null form. Self-Monitoring/Locus of Control Group Comparisons The self-monitoring construct suggests that individuals who score low on the Self-Monitoring Scale are more affected by personal traits 85 than individuals who score high on the Self-Monitoring Scale. In order to test this theoretical conjecture, the Phase II sample was grouped according to self-monitoring and locus of control scores. Comparisons of the classroom management behaviors of these four groups provided the basis for testing Hypothesis II. Figure 8 provides an overview of how the nine teachers in the sample were subdivided for this analysis. Locus of Control External Internal > ""' Self-Monitoring (- 115 (< 11) G1‘0UP 1 Group 2 High (_2 .48) (.0 =1) (3 = 3) Group 4 Group 3 Low ('< .48) (2.: 2) (p_= 3) Figure 8. Self-monitoring by locus of control subgroupings. Hypothesis II The magnitude of mean scores on the management measures (withit- ness and overlapping) will differ significantly when teachers are grouped according to their levels of self—monitoring and internal- external orientation. The districution of mean scores will conform to the following pattern: (high self-monitoring, internal locus of control)> (high self-monitoring, external locus of control) and (low self-monitoring, internal locus of control) > ( M. M. M. M_ low self-monitoring, external locus of control) bw—‘N Summary statement: (M 2 > (M and M 3) > M l 4 86 Table 8 summarizes the means for withitness and overlapping for individuals in each of the three groups that had at least two members. Table 8 Self-Monitoring/Locus of Control, Group Meansa (M_= 9) Withitness Overlapping Group 11 M g _F_ Ratiob g _s_ 5 Ratiob 1 (High s-u, External) 1 5.86 O 3.14 0 2 (High S-M, Internal) 3 5.82 .20 4.88 .92 3 (Low S-M, Internal) 3 5.08 1.28 3.77 2.35 4 (Low S-M, External) 2 5.13 .30 .70 4.13 .75 .36 aSince Group 1 contains only one member, it is not statistically correct to consider that individual's score a mean. bBased on Groups 2, 3, and 4 only. An examination of Table 8 indicates that the high self-monitoring group (Group 2) had the highest mean average for both withitness and overlapping. Most likely this was simply a function of their levels of self-monitoring. However, the magnitude of the means for Groups 3 and 4 were not distributed in the predicted direction. Analysis of variance tests were, nevertheless, computed, and it was determined that the differences in observed means were not significant when alpha was set at .05. The results of these tests are also summarized in Table 8. Since the group means did not differ as predicted, Hypo- thesis II must be accepted as stated in the null form. 87 A Post Hoc Analysis During data collection and in the follow-up interview, it was noted by the observers that one member of the research sample was not well planned and expressed a desire to leave the field of teaching. In order to determine the effect of this aberrant teacher on the re- sults of the group analysis, means were computed excluding this individual. The aberrant teacher was a member of Group 3. When this indivi- dual was dropped from the sample, the means for Group 3 increased from 5.08 to 5.81 for withitness and from 3.77 to 5.00 for overlapping Thus, the omission of this subject did affect the pattern of group mean scores. Under these conditions, the hypothesis that Group 4 would be the least effective classroom managers was supported. How- ever, when an analysis of variance test was computed, it was deter- mined that the differences in observed means were not significant despite this adjustment in the sample (alpha = .05). Given these results and the fact that the omission of an aberrant teacher was a post hoc analysis, these findings do not affect the decision to ac- cept the null form of Hypothesis II. Graphic Representation of Group Data In order to pictorially describe the interaction of locus of con- trol orientation and self—monitoring level, the relations between these two variables and the criterion measures of withitness and over- lapping were portrayed in scattergrams. Figure 9 presents these two pictorial representations. 88 SCRTTERGRRH: NHITNESS RNO SELF-MONITORING SCHTTERGRRH: MRLRPPING RNO SELF-MONITORING 0.00“ 3 ‘ 0. ‘ \ ‘ ‘ \ V / \ \ W l ‘ 0 o \ / \ ® ’ \ / ~ — o 5.500» 0.000» ,, El 5.000» 0 0.00 » a e 0 o g 0. L”. E l E E E E > o 0 .5001 / o 3.000. I , - \ / / \ \ / \ <1- / 0 / \ \ / / \ 0.000) / 2.000» / \ / \ \ ’ ' " / co) / (:7 / 3 50., a. t : 0 4 fl: ‘T : : 3.3:: t : t : 4. ¢ ¢ ¢ : 0 .200 .000 .000 .000 1.000 0 .200 .600 .000 .000 1.000 SELF—MONITORING SELF-MONITORING Figure 9. Graphic represenation of self-monitoring/locus of control groups and criterion variables. [3 Low self-monitoring/external locus of control. (:) Low self-monitoring/internal locus of control. Since low self-monitors are purported to be particularly sensi- tive to their personality traits, the low self-monitoring points on each scattergram were identified by internal-external locus of control orientation. High self-monitoring points were not identified by locus of control orientation since high self-monitors are not theoretically affected by their personality traits. An examination of Figure 9 sup- ports the group analysis findings for Hypothesis II. Specifically, the withitness scattergram indicates that internal locus of control/low self-monitoring teachers were more effective classroom managers than external/low self-monitoring teachers. The previously mentioned 89 aberrant teacher was the only individual who did not fit this general- ization. The second scattergram provides a graphic portrayal of the group mean results for overlapping and self-monitoring/locus of control. In addition to the aberrant teacher, one other low self-monitoring/inter- nal subject did not fit the predicted pattern in Hypothesis II. In other words, predictions of overlapping based on both self-monitoring and locus of control measures did not appear to be superior to those based on self-monitoring scores alone. Summary The results of the investigation were summarized in Chapter IV. Five hypotheses were tested using correlational analyses, one hypothe— sis was tested using multiple regression analyses, and two hypotheses were tested using analysis of variance. The eight research hypotheses and the findings for each may be briefly summarized as follows. Hypothesis I It was predicted that the magnitude of the simple correlations between self—monitoring and each measure of classroom management would be significantly greater than zero. Although all the correlations were positive, they were not significantly greater than zero. Thus, the data did not support this hypothesis. Hypothesis II It was predicted that when teachers in the Phase I sample were grouped according to their levels of self—monitoring and locus of con- trol orientation, the low self-monitoring, external locus of control group would exhibit the smallest mean score on the management measures 9O withitness and overlapping. The data did not support this hypothesis. However, Subsequent post hoc analyses suggest that these findings may be traced to a single aberrant teacher in the sample. Hypothesis III It was predicted that the magnitude of the simple correlations between each predictor variable (classroom self—monitoring, self— monitoring, and locus of control) and each measure of classroom man- agement would vary in the following order: [ (predictor/withitness) >.£ (predictor/overlapping) 7 p (predictor/momentum) > :_(predictor/ smoothness). The data did not support this hypothesis. Hypothesis IV It was predicted that the magnitude of simple correlations be— tween each predictor variable and the entire set of criterion vari— ables would vary in the following order: §_(classroom self—monitoring /set of criterion variables) > p_(self—monitoring/set of criterion variables) > :_(locus of control/set of criterion variables). The data did not support this hypothesis. Hypothesis V It was predicted that the simple correlation between the two de- viancy management measures (withitness and overlapping) would be greater than the correlations between either of those measures and the two movement management measures (momentum and smoothness) and that the simple correlations between the two movement management mea- sures would be greater than the correlations between either of those measures and the two deviancy management measures. The data did not support this hypothesis. 91 Hypothesis VI It was predicted that the simple correlations between classroom self-monitoring and self-monitoring would be greater than .40, but less than .60. The magnitude of this correlation for both the Phase I and Phase II samples was greater than .60. Hypothesis VII It was predicted that the magnitude of multiple correlation coef- ficients for the three predictor variables and each criterion variable would vary in the following order: R_(multip1e predictors/withitness) 7_R (multiple predictors/overlapping)>’_M (multiple predictors/momen- tum)> R (multiple predictors/smoothness). The data did not support this hypothesis. Hypothesis VIII It was predicted that the mean scores on the management measures withitness and overlapping would be significantly larger for high self-monitors than for low self-monitors. Although the means were distributed in the predicted direction, the differences were not statistically significant. Thus, the data did not provide convincing support for this hypothesis. CHAPTER V DISCUSSION AND IMPLICATIONS In this chapter a summary of the study is presented, followed by a discussion of the findings for each of the eight research questions. The final two sections outline implications for investigators working in presage-process research. Summary: Design of the Study The design of this investigation was based upon Dunkin and Biddle's (1974) model for the study of classroom teaching. The model recognizes four sets of variables: presage, context, process, and product. Figure 10 provides a pictorial representation of the Dunkin and Biddle model and identifies the specific variables that were con- sidered in this investigation. The arrows in the model represent causal assumptions. The study focused only on relationships between presage and process variables. Thus, the purpose of the study was to investigate relationships be- tween self—monitoring, locus of control;and the classroom management behaviors of elementary teachers. As a requisite to satisfying the purpose, two measurement instru- ments were designed. First, a specific Classroom Self-Monitoring Scale was developed as an adaptation of Snyder's (1974) Self-Monitor- ing Scale. The scale was written in terms that captured the high self-monitoring environment of the traditional, self-contained, 92 93 Presage Variables Teacher Properties Process Variables \‘ \ \ Self-Monitoring Locus of Control .7 Teacher Behaviors a Product Variables ,r’ Withitness Achievement ’," Overlapping Attitudinal Context Variables ’ Momentum Elementary Smoothness Self-Contained ,3<‘ Recitation Activities Student Behaviors Urban Freedom from Deviancy Work Involvement Note. ———3 Relations which were examined in this study. ---9 Relations which have been demonstrated in the literature. Figure 10. Critical variables in the research design. elementary school classroom. Second, a Classroom Management Observa- tion System was developed based on the work of Jacob Kounin (1977). The system includes (a) Guide for the Judgment of Teacher Classroom Management Behavior, (b) Classroom Management Observation Instrument, and (c) Daily Observation Schedule. It was designed to provide reli- able measures of teacher management behaviors in a live observation setting (see Appendix G). In order to test the properties of the Classroom Self—Monitoring Scale, a Phase I sample of 34 practicing teachers was selected. This group was administered the Self-Monitoring Scale and its derivative, the Classroom Self-Monitoring Scale. The purpose of UnaPhase Istudy was to statistically test and refine the classroom form of the Self- Monitoring Scale. The coefficient alpha for the initial 25-item ver- sion of this scale (.53) was lower than anticipated. Therefore, the 94 point-biserial correlations were examined, and five items which de— tracted from the internal consistency of the scale were dropped. When these five items were deleted, the alpha level for the scale increased to .66. The revised 20-item Classroom Self-Monitoring Scale was used in Phase II. Using the Classroom Management Observation System, two observers participated in a training process which relied primarily on the ob- servation, discrimination, and coding of classroom videotapes. Inter- rater reliabilities for the four management measures were determined during the main study. They were above .90 for three of the measures (withitness, overlapping, and smoothness). However, the inter-rater reliability for momentum was lower than anticipated (p_= .33). Eight research questions and their accompanying hypotheses were suggested by potential relationships among the presage variables, the process variables, and the presage-process variables. In order to empirically examine these relationships, a relatively small sample of self-contained elementary teachers was selected. Nine teachers in an urban school district volunteered to participate in Phase II. The teachers were of mixed racial backgorunds, and all were female. Data for Phase II were collected using three presage variable measures: Snyder's Self—Monitoring Scale, the Classroom Self—Monitoring Scale (designed to measure the self-monitoring construct in the social con— text of the classroom), and the Locus of Control Scale. Observations of the managerial behaviors of the nine classroom teachers served as the basis for four measures of process variables: withitness, over— lapping, momentum, and smoothness. Various statistics were computed 95 in an attempt to test the hypotheses. These included group means, scattergrams, simple correlations, and multiple regression analyses. Discussion of the Findings Relations among the Presage Variables: The Two Self-Monitoring Scales Efforts to establish the construct validity of the specific Classroom Self—Monitoring Scale prompted the need to examine the de- gree of similarity between the new scale and Snyder's (1974) Self- Monitoring Scale. Since the new scale was written in terms of the high self—monitoring environment of the classroom it was expected to be similar to, but not parallel with, the Self-Monitoring Scale. The obtained correlations between the two measures (:_= .69 for Phase I; 3 = .70 for Phase II) indicated a stronger relationship than desired. This analysis provided the first indication that a specific form of the Self-Monitoring Scale would not have the proper— ties suggested by the theoretical conjectures on which it was based. The analysis of relations between the two Self-Monitoring Scales and the four measures of classroom management, which will be described later in this chapter, also failed to support this conjecture. Relations among the Classroom Management Measures The four classroom management measures were classified into two categories: deviancy management (withitness and overlapping) and movement management (momentum and smoothness). It was expected that the correlations among subscales within each category would be greater than correlations among subscales in different categories. The coreelation between withitness and overlapping (deviancy management) was .75 which was greater in magnitude than the 96 correlations between these two measures and momentum (p_withitness/mo- mentum = .63; p_overlapping/momentum = .57). However, the correspond- ing correlations with smoothness were larger than expected (p_withit— ness/smoothness = .90; p overlapping/smoothness = .86). The correla~ tion between the two measures of movement management, momentum and smoothness (p_= .57), was less than or equal to all the other correla— tions among process measures. It, therefore, also failed to conform to the predicted pattern. The prediction that the correlations among subscales within each category would be greater than the correlations among subscales in different categories was, in retrospect, unwarranted. The relative magnitude of correlations within categories provides some indication of construct validity, since the subscales are conceptually related. But, this conceptual realtion does not indicate that a large relation- ship should not exist between the ability to manage deviancy and the ability to manage movement. Relations Between Presage and Process Variables One of the two primary hypotheses in this investigation concerned the relationship between self—monitoring and the classroom management measures. In addition, three secondary hypotheses focused on theore- tical conjectures (described in Chapter II) concerning the relations between the presage variables (self-monitoring, classroom self—moni- toring, and locus of control) and the classroom management behaviors of teachers. In general, the results failed to provide consistent evidence in support of the relationships that were hypothesized. Ra— ther, these data prompted the following list of conclusions: 97 The simple correlations between self-monitoring and the four process variables ranged from a low of p_= .13 for smoothness to a high of :_= .48 for withit- ness. Although these correlations were not statis- tically significant, they were of sufficient magni— tude to encourage further research in this area. Classroom self-monitoring was not, as hypothesized, the best predictor of classroom management behaviors. The clear superiority of the Self-Monitoring Scale in predicting classroom management behaviors sug— gests that Snyder's scale is not situation—specific and is probably generalizable to a wide range of social contexts. The magnitude of correlations between the three pre- sage variables and the four management variables did not conform to the predicted order (i.e., 5's presage variables/withitness pfs presage/overlapping [f5 presage/momentum E's presage/smoothness). This sug- gests that sensitivity to the social context (high self—monitoring and an internal locus of control) may supply salient information for all areas of class— room management and not the deviancy management mea- sures in particular. The 12 simple correlations between the three presage and four process variables ranged from a low of 98 p = -.05 for classroom self-monitoring and overlapping to a high of [_= .48 for self—monitoring and withitness. None of the correlations were significantly different from zero when alpha was fixed at .05. With the pos- sible exception of the correlation between self- monitoring and withitness, the magnitude of each of these relations was consistent with the ”+.3O ceiling” reported by Mischel (1968) for correlations between personality measures and cross-situational behaviors of individuals. Interactions Between Self—Monitoring and Locus of Control The second of the two primary hypotheses in this investigation concerned self—monitoring's purported ability to act as a moderating variable, identifying ”for whom” personality variables, such as 10- cus of control, are most likely to influence behavior. Therefore, the Phase I sample was grouped according to level of self-monitoring and locus of control orientation. Because scores on the Classroom Self—Monitoring Scale were generally parallel to those on the Self- Monitoring Scale, they were not included in the analysis of group means. In addition, because of the problems observers experienced in coding momentum and smoothness behaviors as well as low inter-rater reliabilities for momentum, only withitness and overlapping were in— cluded in the analysis of group means. Figure 11 provides an over- view of how the nine teachers in the sample were subdivided. Group 1 contained only one member and was omitted from the analy- sis. Given the predicted relations between self-monitoring and locus 99 Locus of Control Self-Monitoring Group 1 Group 2 High S—M/ High S-M/ External Internal Group 4 Group 3 Low S-M/ Low S-M/ External Internal Figure 11. Self—monitoring by locus of control subgroupings. of control, the Group 2 means were hypothesized to be larger than Group 3; and they, in turn, were expected to be larger than the means for Group 4. However, the order of group means did not conform to this pattern. Most surprising was the observation that the Group 4 means were not the smallest. The results, therefore, fail to sup— port the expectation that self-monitoring acts as a moderating vari- able, determining the relative influence of personality variables on human behavior. A Secondary Analysis of the Relation Between Self-Monitoring and Classroom Management Behaviors The relation between self-monitoring and measures of classroom management were also examined by comparing the mean levels of class- room management performance for groups of high and low self—monitoring teachers. Mean scores for high self-monitors were larger for withit- ness (M_= 5 83) and overlapping (M_= 4.45) than the corresponding mean scores for the low self—monitoring group (M_withitness = 5.10; M over- lapping = 3.91). Although these differences were not statistically lOO significant, they were of sufficient magnitude to suggest that these relations should be reexamined with a larger sample of teachers. Implications for Research Although this investigation was based on established theoretical conjectures, it would not be improper, from a methodological point of view, to classify it as a pilot study. It, therefore, may be useful to examine the imperfections in the design and conduct of the study as a guide to future research that attempts to link presage and process variables. 1. The most glaring weakness in the design of this study was the small sample size. The problem stemmed in large measure from the fact that classroom management measurement was time consuming and necessitated the use of a small sample. The relatively low power of the statistical tests that resulted from the small sample made it difficult to interpret the results. Future researchers who wish to consider classroom management measures are also likely to encounter the problem of low statistical power due to small sample size. One approach to increasing sample size may be to reduce the complexities of data collection by con- sidering only one process measure. According to the results of this study, withitness would be the best single measure. It was most easily observed and coded, it had a large inter-rater reliability, it 101 was consistently correlated with other management mea- sures, and it was most highly correlated with self- monitoring. A second approach to enlarging the sample may be to engage in collaborative research, in which management data are collected by several researchers. The advantages of the collaborative model over the single investigator approach should be readily ap— parent. A second method of increasing the power of the statis- tical tests would be to conduct classroom observations of management behaviors for individuals who fall at the extremes of the distribution on presage measures (i.e., high and low thirds). This approach would be most feasible in situations in which researchers can gain the initial cooperation of a large group of teach- ers. Given the relatively low correlations that were observed in this study, it is likely that future re- searchers will need to use one of these methods to generate a more powerful research design in order to demonstrate that there is a relationship between self- monitoring and classroom management if, in fact, that relationship exists. This investigation took place in the middle of the school year when classroom routines had already been established. Thus, the frequency of management 102 behaviors was probably lower than at the beginning of the school year when students "tested” the teacher to determine the boundaries of acceptable behavior. In addition, at the time of this study, teachers had al- ready established a clear sense of which students were deviancy prone, decreasing the likelihood of incorrect desists. In brief, it may be easier to demonstrate the relationship between self-monitoring and classroom management early in the school year when teachers are most actively engaged in establishing classroom routines. In general, the development of a Classroom Management Observation System was successful. Despite the complexities of live classroom ob- servations, inter-rater reliabilities were high across three of the four subscales. Given the centrality of management skills in pre— service and inservice teacher preparation programs, this live observa- tion system may be very useful to teacher educators. However, as a result of the experience of conducting this investigation, the re- searcher is convinced that two relatively minor modifications should be made in the system prior to its use in future research or instruc— tion. 3. During this study, when a teacher had an opportunity to desist a deviant student but ignored or was unaware of the misbehavior, the event was not coded. This suggests the need to consider a third category for withitness--ignored. This category may have three possible meanings. 103 a. It may be an indication of a deliberate effort to extinguish the behavior and may, therefore, represent an appropriate approach to controlling student behavior. b. It may indicate a lack of withitness. c. It may be an indication of a withit teacher separating events which require attention from events which do not need attention. Although the origin of the action may be ambiguous, it is obvious that the failure of a teacher to de- sist a deviant student is an important aspect of classroom management. Future studies in this area should, therefore, consider this third category of withitness. Movement management variables (momentum and smooth- ness) were not as highly correlated with each other as was predicted. However, these results may re- flect the manner in which these two variables were measured. Perhaps the most basic problem was the ob- servation of these behaviors using six-second inter- vals. Data based on arbitrary time units assumes that movement management behaviors are evenly dis- tributed across the total observation period. This is generally not the case. There may be long periods of time in which movement management behaviors will not occur (e.g., deviancy management behavior). 104 Therefore, it may be more valid to base the data on analytic or psychologically meaningful units, such as the number of negative movement management events per lesson. If this approach were followed, observ- ers would simply tally negative momentum and smooth- ness events, not record the number of six-second in- tervals spent in negative movement behavior. The four recommendations outlined above focused on improvements in the design of this or a highly related research study. They would, therefore, be appropriate in a simple replication of this investiga- tion. In addition to these refinements in methodology, future re— searchers may wish to consider more substantive alterations in the investigation of presage-process relations. Alterations of this type include the following: 5. It is generally conceded that human beahvior is deter- mined by many interacting variables. However, in this investigation, only two classes of presage variables were considered: self-monitoring and locus of control. In future research it may be more fruitful to address several interacting person variables simultaneously. Person variables from several other theoretical per- spectives could be included: self-concepts, person- ality traits, information processing constructs, be- liefs, and values. The presage variables considered in this investiga- tion were also limited to personality constructs. 105 Many other important presage variables may impact upon the management behaviors of teachers. These include the level of professional development of teachers, the type of preparation programs in which the teacher has participated, the level or type of supervision re- ceived during training, and so forth. In brief, use of a collaborative research model may make it possible to study the effectiveness of a wide range of presage variables on the management skills of teachers. While collecting data for this study, the researcher noted that overlapping was more situation-specific than originally thought. This conclusion was suggested by the greater frequency of overlapping events in the lower elementary classrooms than in upper elementary classrooms. The explanation for this difference in frequency is simple. In lower elementary classrooms, teachers are much more involved in small group activi- ties than are teachers in upper elementary classrooms. This observation gives rise to a more general premise that the nature and magnitude of relations between pre- sage and process behaviors may vary across contexts. In other words, productive teaching behaviors may be context-specific and important presage relationships may only be revealed when the investigator builds into the research design the proper contextual limitations. 106 For example, if overlapping behavior does not occur in upper elementary with regularity, it will be dif- ficult to find a relationship between presage vari- ables and overlapping in upper elementary level classrooms. Therefore, it may be important for fu- ture researchers to build context variables into the design of their studies. Such contexts may include subject-matter, grade level, and student characteris- tics. Concludipg,Statement The goal of presage-process research is to identify teacher char- acteristics that are related to productive teacher and student beha- viors. This investigation fell short of this goal in that it found no clear relations between the presage and process variables that were examined. Nevertheless, the study did succeed in realizing one of its major objectives and did generate at least some results that are worthy of further consideration. In general, the objective of developing a reliable classroom man- agement observation system was realized. When improvements outlined earlier are made, this sytem should provide a reliable measure of the management skills of teachers. The ability to measure these skills in live observation situations should be of considerable value to re- searchers and teacher educators. The clearest finding pertained to the development and testing of a specific form of the Self-Monitoring Scale. In simple terms, this instrument failed to yield more precise predictions than the general 107 version of the scale developed by Snyder (1972). The results of this investigation also failed to support predictions regarding the moderat— ing function of the self-monitoring construct. However, these results should be viewed tentatively. The failure of the self-monitoring variable to function as predicted in this investigation may be due to methodological problems such as the small sample size. Other investi- gators have shown that the self-monitoring construct does function as a moderating variable, identifying ”for whom'l attitudes would impact upon behavior (e.g., Snyder and Swann, 1976). Although not statistically significant, the correlations between self-monitoring and withitness and differences in group deviancy mea— surement means for high and low self-monitoring individuals were en- couraging. With a more narrowly defined contextual focus and a larger sample, future research may provide more definitive evidence of these and other relations. In simple terms, this investigation provides at least some rationale for further study of relations between presage and process variables in research on teaching. REFERENCE NOTES Jackson, P. W. The way teaching is: A report for the seminar on teaching. Association for Supervision and Curriculum Development and the Center for the Study of Instruction of the National Educa- tion Association. Washington, D. C., 1966. Anderson, L. M., Evertson, C. M., & Brophy, J. E. The first grade reading group study: Technical repprt of experimental effects and process-outcome relationshipsTTReport No. 4070). Austin, TX: Research and Development Center for Teacher Education, University of Texas at Austin, 1978. Brophy, J. E., & Putnam, J. G. Classroom management in elementary grades (Research Series No. 32). East Lansing, MI: Institute for Research on Teaching, Michigan State University, October, 1978. Good, T., & Grouws, D. Process-product relationships in fourth grade mathematics classrooms, Final Report, Grant NEG-OO-3-0123, National Institute of Education, 1975. Anderson, L. M., Evertson, C. M., & Emmer, E. T. Dimensions in classroom management derived from recent research. In S. Dasho (Chair), Perspectives on classroom manggement research. Symposium presented at the Annual Meeting of the American Educational Re- search Association, San Francisco, Calif., April, 1979. Garland, H., & Beard, J. F. The relationship between self- monitoring and leader emergence across two task situations. Unpublished manuscript, College of Business Administration, University of Texas at Arlington, 1978. James, W. H. Internal versus external control of reinforcement as a basic variable in learning theory. Unpublished doctoral dis— sertation, Ohio State University, 1957. 108 APPENDICES APPENDIX A DEMOGRAPHIC DATA (PHASE I) A1 Instrument Used to Collect Demographic Data (Phase 1) A2 Summary Table of Phase I Demographic Data U‘l-DLAJN-A APPENDIX A1 Instrument Used to Collect Demographic Data (Phase I) Sex: Male_____ Female______ How old are you? For how many years have you taught? How many different school systems have you taught in? What grade levels have you taught? How many years have you taught at each grade level? c. What subjects did you teach? a b c Grade Level Years Taught Subjects Taught Have you ever been a substitute teacher? a. How many years? b. Are you presently a substitute? c. Are you a part-time teacher? ______ How many different courses and workshops have you taken (both undergraduate and graduate) that focus on communication skills? Do you teach in a a. Public school? b. Parochial school? c. Private school? _____ Which best describes the students in your school? a. More than one-half come from urban neighborhoods. b. More than one-half come from suburban neighborhoods. c. More than one-half come from small town or rural neigh- borhoods. 109 10. 11. 12. 110 Which best describes the educational level of the parents of the students in your school? a. More than one-half are college graduates. b. More than one-half are high school graduates. c. Less than one-half are high school graduates. What are your future plans? a. To continue classroom teaching. b. To become an administrator c. To leave education d. To enter another educational area. Specify: Have you ever been an actor? Yes No Have you ever made presentations to large groups? Yes No Please explain 111 APPENDIX A2 Summary Table of Phase I Demographic Data (M_= 33) §§x_ Male a Female p_ 11 (33) 22 66) 5g§_ 21-30 31—40 41-50 51-60 p_ 16 49) 9 27) 7 (21) 1 (3) Years Taught 1—5 6-10 11-15 16-20 21-25 M 20761) 5 15) 5 15) 113) 2 6) Number of School Systems Taught inb l_ 2_ 3 M 22 (67) 8 (24) 3T9) Junior High Grade Level Taught Elementary Middle School Secondar n 20 (61) 6 (18) 6 (18) Special Education l (3) Substitute ExperienceC Yes No p_ 25—T76) 8 (24) Communication Course Work Yes Mp_ _n_ 24—173) 9 (27) Type of School Taught in Urban Suburban Rural p_ 12 36) 10 (30) 12 36) Educational LEVGI of Parents Colle e a H.S. Grads H. S. Grads .p l (31 24 (73) 8 (24) Continue Leave Enter Another Future Plans Teaching Administration Educ. Area of Educ. p_ 20 (61) 6 (18) 6 (18) l (3) Acting Eyperience Xg§_ Mg 2. 5 (15) 28 (85) Grogp Presentation Experience Yes No M 21764) 12736) aNumbers in parentheses indicate percentages bAll subjects were public school teachers CNone of the subjects was presently substitute teaching APPENDIX B RESEARCH APPLICATIONS B1 First Research Application B2 Second Research Application B3 Outline of Proposed Research APPENDIX B1 #1 First Research Application OBJECTIVE To examine the relationships between two presage variables: Locus of Control (Rotter), and Self-Monitoring (Snyder); and the class- room management behaviors (Kounin) of selected elementary teachers. The presumed relationships are suggested by social learning theory as described by D. Bem and A. Allen. PROCEDURE I Building Level Collection of Data A. Random selection of 10 out of 44 elementary school build- ings in the School District. Administration of the (general) Self-Monitoring Scale (Snyder) to all self—contained classroom teachers in the randomly selected buildings. Identification of volunteer teachers willing to partici- pate in the study of classroom management. II Classroom Collection of Data A. "Blind selection” of six (6) volunteers with high self- monitoring scores. ”Blind selection” of six (6) volunteers with low self— monitoring scores. Classroom observation of volunteer teachers. 1. Minimum of two observations. 2. For the duration of a math class. 3. Two observers present. Administration of Rotter's Locus of Control measure to selected volunteers (15 minutes). Administration of (specific) Self-Monitoring Scale (Knapp) to selected volunteers (15 minutes). Taped interview with selected teachers concerning class- room management (20 minutes). 112 13. 113 #1 BENEFITS Judging from reports of comparable studies, teachers who parti- cipate in this study should benefit from the feedback I supply after I have observed their classroom management behaviors. Feedback will only be given if requested by the classroom teacher and only after all classroom level data have been collected. Participating building staffs may wish to be involved in an inservice-type discussion of the various measures used in this study and their contribution to our knowledge of effective management techniques. Feedback regarding how each teacher might interpret his/her score on Snyder's Self-Monitoring Scale would also be offered. I will provide inservice programs of this type in any building that wishes to participate. APPENDIX 82 #2 Second Research Application 5. OBJECTIVE To examine the relationship between two presage variables: Self- Monitoring (Snyder) and Locus of Control (Rotter); and the class- room management behaviors (Kounin) of selected elementary teachers. The presumed relationships are suggested by social learning theory as described by D. Bem and A. Allen. 6. PROCEDURE I BUILDING LEVEL COLLECTION OF DATA A. Administration of the (general) Self-Monitoring Scale (Snyder) to all self-contained classroom teachers in two large elementary buildings (10 minutes). B. Identification of volunteer teachers willing to partici- pate in the study of classroom management. C. ”Blind selection" of six (6) volunteers with high self- monitoring scores. ”Blind selection” of six (6) volunteers with low self- monitoring scores. 11 CLASSROOM COLLECTION OF DATA* A. Classroom observation of selected volunteer teachers. 1. Three observations a. One observation with two observers. b. Two observations with one observer. 2. For the duration of a recitation lesson. B. Administration of (specific) Self-Monitoring Scale (Knapp) to selected volunteers (10 minutes). C. Administration of Rotter's Locus of Control measure to selected volunteers (15 minutes). * Classroom data will be collected over approximately a two month period. 114 DIRECTIONS: APPENDIX Dl 25-ITEM CLASSROOM SELF-MONITORING SCALE The statements on the following pages concern your per- sonal reactions to a number of different situations. No two statements are exactly alike, so consider each state- ment carefully before answering. If a statement is TRUE or MOSTLY TRUE as applied to you, check the space marked T. If a statement is FALSE or NOT USUALLY TRUE as applied to you, check the space marked F. l. I find it hard to imitate the behavior of other teachers. 2. My classroom behavior is usually an expression of my true inner feelings, attitudes, and beliefs. 3. When with a group of colleagues, I do not make a special point to do or say things that they will like. 4. When working with students, I can only argue for ideas in which I already believe. 5. I can teach impromptu lessons even on topics about which I have almost no information. 6. I guess I put on a show to impress or entertain students. 7. When I am uncertain how to act in the classroom, I look to the behavior of students for cues. 8. Judging from my classroom behavior, I would probably make a good actor. 9. I rarely need the advice of other teachers when choos- ing instructional materials or activities. 10. I sometimes appear to students to be experiencing deeper emotions than I actually am. 11. I laugh more when I watch a comedy with my class than when I watch a comedy alone. 12. When with a group of colleagues, I am rarely the center of attention. 120 13. 14. 15. l6. 18. 19. 20. 21. 22. 23. 24. 25. 121 In different classroom situations or with different students, I often act like very different persons. I am not particularly good at making students like me. Even if I am not enjoying myself while teaching, I often pretend to be having a good time. While teaching, I'm not always the person I appear to be. I would not change my opinions (or the way I do things) in order to please students or win their favor. I have considered being an entertainer. In order to get along and be liked in the classroom, I tend to be what students expect me to be rather than anything else. I do not enjoy joining students in role-playing ac- tivities like charades or improvisational acting. I have trouble changing my behavior to suit different students or different classroom situations. In classroom discussions, I depend upon students to keep the interaction going. I feel a bit awkward in front of a new group of stu- dents and do not show up quite so well as I should. I can look students in the eye and tell a lie with a straight face (if for a right end). I may deceive certain students by being friendly when I really dislike them. APPENDIX D 25—ITEM CLASSROOM SELF-MONITORING SCALE D1 DZ 25-Item Classroom Self-Monitoring Scale Phase I Point—Biserial Correlations for the 25-Item Classroom Self- Monitoring Scale APPENDIX D2 Phase I Point-Biserial Correlations for 25-Item Classroom Self-Monitoring Scale (M_= 32) Corrected Item-Total Alpha If Item Correlation Item Deleted 1 .23 .50 2 .15 .52 3 .20 .51 4 .18 .51 5 .18 .51 6 .33 .49 7* -.18 .37 8 .35 .48 9 .08 .53 10 .54 .45 11 .33 .49 12 .06 .53 13* -.08 .55 14* -.O8 .55 15* -.14 .56 16 .16 .52 17 .37 .48 18 .36 .49 19 .11 .52 20* -.27 .58 21 .01 .54 22 .21 .51 23 .08 .53 24 .44 .47 25 .27 .50 * Items chosen to be deleted. 122 APPENDIX E CLASSROOM SELF-MONITORING SCALE E1 E2 ZO-ITEM CLASSROOM SELF- MONITORING SCALE PHASE II POINT BISERIAL CORRELATIONS FOR THE 20- ITEM CLASSROOM SELF- MONITORING SCALE 13. 115 #2 0. Interview with selected volunteers concerning classroom management. BENEFITS Judging from reports of comparable studies, teachers who partici— pate in this study should benefit from the feedback I supply after I have observed their classroom management behavior. Feed- back will only be given if requested by the classroom teacher and only after all classroom level data have been collected. Participating building staffs may wish to be involved in an in- service-type discussion of the various measures used in this study and their contribution to our knowledge of effective man- agement techniques. Feedback regarding how each teacher might interpret his/her score on Snyder's Self-Monitoring Scale would also be offered. I will provide inservice programs of this type in any building that wishes to participate. APPENDIX 83 Outline of Proposed Research MEMORANDUM TO: FROM: Robert Knapp RE: Classroom Research DATE: February 19, 1980 OVERVIEW The research I am requesting teachers to volunteer for is an investi- gation into information processing and classroom management. The classroom social context contains a large amount of complex informa- tion. In order to deal with the situation, individuals must process information selectively. The Self-Monitoring Scale is used in this research to group indivi- duals according to two styles of information processing. Neither style should be considered ”better" than the other, only different. The two groups of information processors will be observed to deter— mine their classroom management styles. Two areas of classroom man- agement will be observed: (a) the management of student behavior, and (b) the management of lesson presentation. WHAT I AM ASKING TEACHERS TO DO 1. Take the Self-Monitoring Scale (10 minutes) 2. Be observed for three lessons (approximately 5 hour per observa- tion, spread over a two month period) 3. Take the classroom Self-Monitoring Scale (10 minutes) 4. Take the Locus of Control Scale (15 minutes) Observations will be prearranged. During one observation two obser- vers will be present. During two observations only one observer will be present. The observers will be as unobtrusive as possible. All information collected during the investigation is confidential. It will be shared with individuals upon request. No one will be iden- tifiable in the final report. 116 117 WHAT BEING INVOLVED CAN DO FOR THE TEACHERS Insight into the management of students and lessons can be gained by the teachers involved. In addition, I will gladly assist teachers who wish to use this experience as an evaluation for the School District. APPENDIX C SNYDER'S SELF-MONITORING SCALE APPENDIX E2 Phase II Point-Biserial Correlations for the 20-Item Classroom Self-Monitoring Scale (M_= 9) Corrected a Item-Total Item Correlation 1 .31 3 .46 4 .17 5* —.b3 6 .67 7 -.O7 8 -.03 9 .31 10 .11 11 .34 12 -.05 13 .72 15 .11 lb .09 17 .09 18 -.O7 19 -.20 20* -.50 a Items with no variance are deleted. Alpha If Item Deleted .18562 .11806 .23679 .48909 .02293 .31983 .31380 .18562 .25972 .17052 .30899 .01529 .26422 .26842 .26842 .30433 .34903 .45536 * Items deleted in computation of lB—Item Classroom Self- Monitoring Scale Point Biserial Correlations (alpha 125 .62) APPENDIX F INTERNAL-EXTERNAL LOCUS OF CONTROL SCALE DIRECTIONS: APPENDIX F INTERNAL-EXTERNAL LOCUS OF CONTROL SCALE (Rotter, 1966) This is a questionnaire to find out the way in which certain important events in our society affect different people. Each item consists of a pair of alternatives lettered g_or p, Please select the one statement of each pair (and only one) which you more strongly believe to be the case as far as you're concerned. Be sure to select the one you actually believe to be more true rather than the one you think you should choose or the one you would like to be true. This is a measure of personal belief: obviously, there are no right or wrong answers. Please answer these items carefully but do not spend too much time on any one item. Be sure to find an answer for every choice. Select the lettered statement which you find more true and circle that letter. In some instances you may discover that you believe both statements or neither one. In such cases, be sure to se- lect the one you more strongly believe to be the case as far as you're concerned. Also try to respond to each item independently when making your choice; do not be in- fluenced by your previous choices. 1. a. Children get into trouble because their parents punish them too much. b. The trouble with most children nowadays is that their parents are too easy with them. 2. a. Many of the unhappy things in people's lives are partly due to bad luck. b. People's misfortunes result from the mistakes they make. 3. a. One of the major reasons why we have wars is because people don't take enough interest in politics. b. There will always be wars, no matter how hard people try to prevent them. 4. a. In the long run people get the respect they deserve in this world. b. Unfortunately, an individual's worth often passes unrecog- nized no matter how hard he tries. 126 10. 11. 12. 13. 14. 15. 16. CTQJ UQJ C70) C79.) 127 The idea that teachers are unfair to students is nonsense. Most students don't realize the extent to which their grades are infleunced by accidental happenings. Without the right breaks, one cannot be an effective leader. Capable people who fail to become leaders have not taken ad- vantage of their opportunities. No matter how hard you try, some people just don't like you. People who can't get others to like them don't understand how to get along with others. Heredity plays the major role in determining one's personality. It is one's experiences in life which determine what that per- son is like. I have often found that what is going to happen will happen. Trusting to fate has never turned out. In the case of the well prepared student, there is rarely if ever such a thing as an unfair test. Many times exam questions tend to be so unrelated to course work that studying is really useless. Becoming a success is a matter of hard work; luck has little or nothing to do with it. Getting a good job depends mainly on being in the right place at the right time. The average citizen can have an influence in government deci- sions. This world is run by the few people in power, and there is not much the little guy can do about it. When I make plans, I am almost certain that I can make them work. It is not always wise to plan too far ahead because many things turn out to be a matter of good or bad fortune anyway. Ihere are certain people who are just no good. There is some good in everybody. In my case getting what I want has little or nothing to do with luck. Many times we might just as well decide what to do by flipping a coin. Who gets to be the boss often depends on who was lucky enough to be in the right place first. Getting people to do the right thing depends upon ability; luck has little or nothing to do with it. 1/. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 128 As far as world affairs are concerned, most of us are the victims of forces we can neither understand, nor control. By taking an active part in political and social affairs, the people can control world events. Most people don't realize the extent to which their lives are controlled by accidental happenings. There really is no such thing as "luck.” One should always be willing to admit mistakes. It is usually best to cover up one's mistakes. It is hard to know whether or not a person really likes you. How many friends you have depends upon how nice a person you are. In the long run the bad things that happen to us are balanced by the good ones. Most misfortunes are the result of lack of ability, ignorance, laziness, or all three. With enough effort we can wipe out political corruption. It is difficult for people to have much control over the things politicians do in office. Sometimes I can't understand how teachers arrive at the grades they give. There is a direct connection between how hard I study and the grades I get. A good leader expects people to decide for themselves what they should do. A good leader makes it clear to everybody what their jobs are. Many times I feel that I have little influence over the things that happen to me. It is impossible for me to believe that change or luck plays an important role in my life. People are lonely because they don't try to be friendly. There's not much use in trying too hard to please people; if they like you, they like you. There is too much emphasis on athletics in high school. leam sports are an excellent way to build character. What happens to me is my own doing. Sometimes I feel that I don't have enough control over the direction my life is taking. Most of the time I can't understand why politicians behave the way they do. In the long run the people are responsible for bad government on a national as well as on a local level. APPENDIX G CLASSROOM MANAGEMENT OBSERVATION SYSTEM G1 G2 G3 Guide for the Judgment of Teacher Classroom Manage- ment Behavior Classroom Management Observation Instrument Daily Observation Schedule II. APPENDIX 61 GUIDE FOR THE JUDGMENT OF TEACHER CLASSROOM MANAGEMENT BEHAVIOR Deviancy Management Codes WITHITNESS A teacher's communication to children that she knows or does not know what is going on in the classroom. A teacher communicates knowledge of classroom events to students by ”desisting” the correct deviant student and by timing that desist properly. Targeting Mistakes (a) Targets the incorrect student. (b) Targets a less serious deviancy when a more serious deviancy is present. Timing Mistakes (a) The deviancy spreads to other students before the teacher acts. (b) lhe deviancy increases in seriousness before the teacher acts. OVERLAPPING A teacher's ability to pay attention to two issues simultaneously. Success in handling the two issues is not important. Does the teacher become completely immersed in only one issue? In order for an overlapping issue to be present, the teacher must be oc- cupied with the total group gp_a subgroup and a deviancy occurs in another group pp_a student ”brings in" an issue to her when she is occupied with doing something else. Some Overlapping The teacher shows some attention to the "sphere group” while handling the deviancy or the stu- dent bring in. No Overlgpping The teacher completely drops the sphere group. There is often a change in manner or position and the teacher has trouble returning to the activity. 130 Movement Management Codes The movement codes (smoothness and momentum) are designed to measure the movement of academic activities. They answer the question, "How does the teacher maintain or disrupt the flow of activities that are programmed?" Uncontrollable events (such as a principal's message) are pp;_to be coded. I. SMOOTHNESS (JERKINESS) Any perceptible action by the teacher which produces a break or a stop in the activity flow. They may be very short. Smoothness may be applied to the following categories. 1. Stimulus-Boundedness. The teacher is engaged in some on- going activity with a group of children, happens to become aware of some stimulus or event that is minor and unrelated to the ongoing activity, becomes distracted by this stimu- lus, and reacts to it with sufficient involvement to war- rant judging that she is immersed in it to the point of dropping her focus on the ongoing activity. 2. Thrusts. A teacher's "bursting in" with an order or state- ment for which the students are not prepared. A thrust has a clear element of suddenness with no sign of sensitivity to whether the target group is in a state of readiness. 3. Dangles. To be coded when the teacher is involved in an activity and leaves it ”hanging in midair“ by going off to some other activity. She then returns to the original ac- tivity. Activity....irrelevant activity....new activity. 5. Flip-Flops. Coded at transition points. The teacher ter- minates one activity, starts another, and then returns to the terminated activity. Termination...new activity...re- turn to terminated activity. II._ MOMENTUM (SLOW-DOWNS) Slow-downs consist of behaviors initiated by teachers that clearly slow down the rate of movement in an activity. Their effect is to clearly impede the progress of an activity, to hold back and produce dragginess in the progress of an activity. Slow—downs are coded by six-second intervals. A slow-down lasting six seconds or less would be tallied as one unit. A slow-down last- ing 7-12 seconds would be tallied as two units, etc. Two cate- gories of slow-downs are to be coded: overdwelling and frag- mentation. Overdwelling is to be coded when the teacher dwells on an issue and engages in a stream of talk or actions that is clearly be- yond what is necessary for most studnets' understanding or get- ting on with an activity. Overdwelling can apply to either the I31 behavior of the student or to the task. Overdwelling may be applied to the following categories: 1. Behavior Overdwelling refers to teacher behavior which is focused on how students are behaving. Dwelling on misbe- havior beyond what is adequate to get the misbehavior stopped or to produce conformity. ”Nagging or preaching.” May be coded in addition to targeting and timing. Actone Overdwelling refers to the teacher's overemphasis on sub-parts or actions involved in student behavior. (Example: how to sit, where to put hands, etc.) Prop Overdwellipg refers to the props used in the lesson (519., books, pencils, etc.). A misplaced emphasis on props and their use rather than their purpose. Need not be accompanied by talk. Thus, a teacher may over empha- size props by passing out papers one at a time, there- fore producing significant waiting. Task 0verdwelling refers to the teacher's overelaboration of explanations or directions concerning the task which is clearly beyond what is required for most students to understand. Frggmentation is a slow-down produced by a teacher's breaking down an activity into sub-parts when the activity could be per- formed as a single unit. Two categories of fragmentation are coded: 1. Group Fragmentation is coded when the teacher asks indivi- dual members of a group to do something separately when the whole group could be doing it as a whole. This produces significant "waits" for individuals and, thus, slows down the movement. (Example: Asking children to come to a read— ing group singly when everyone could come at the same time.) Prop_or Actone Fragmentation is coded when the teacher fragments a meaningful unit of behavior into smaller compo- nents and focuses upon these sub-parts when the behavior could be performed as a single, uninterrupted sequence. (Example: Put away your math books...Take out your spelling books...etc.) APPENDIX G2 CLASSROOM MANAGEMENT OBSERVATION INSTRUMENT DATE TEACHER BEGINNING TIME ENDING TIME OBSERVER WITHITNESS For each teacher desist, record Targeting and Timing. For each separate student deviancy which increases in serious— ness or spreads, but is not desisted by the teacher, tally one under Timing. TARGETING TIMING Positive Negative Positive . Negative OVERLAPPING Tally one for each Overlapping event. SOME OVERLAPPING NO OVERLAPPING SMOOTHNESS Tally one for each six-second interval caused when the teacher disrupts the flow of programmed activities. Do pp;_code uncontrollable events. Stimulus—Boundedness Dangles Thrusts Truncations Flip-Flops MOMENTUM Code teacher behavior which produces a "wait" in the presen- tation of material. Tally one for each six-second slow-down. OVERDWELLING FRAGMENTATION Behavior Pr0p 'Prop Group or Actone Task Actone RECORD PERSONAL REACTIONS ON THE REVERSE SIDE. 132 OBSERVER APPENDIX G3 DAILY OBSERVATION SCHEDULE DAY/DATE TIME TEACHER ROOM GRADE TIME TEACHER RUOM GRADE TIME TEACHER ROOM GRADE TIME TEACHER ROOM GRADE 133 APPENDIX H PHASE II INTERVIEW TO. 11. APPENDIX H PHASE I INTERVIEW (taped) How many years have you taught? What grade levels have you taught? For how many years? Have you taken course work that focused on communication skills? What are your future plans? 10 continue classroom teaching. 10 become an administrator. To leave education. To enter another area of education. C10 O'QJ I know it's not easy to state clearly, but would you try to explain to me what you try most to achieve as teacher? What are you really trying to do as a teacher? Is it hard for you to tell how well you are doing as a teacher? a. On a day to day basis? b. On a year long basis? c. What things do you look for as an indication of your effec- tiveness? What kind of knowledge do you think a teacher must possess to do a good job? What kind of skills do you think a teacher must possess to do a goog job? Which is most important? What are your greatest strengths as a teacher? Some teachers seem to emphasize the importance of a teacher's getting students to work effectively. Others emphasize interrela- tionships with students. Which of the two do you consider more importnat? 1 34 135 12. What kind of reputation would you most like to have with the classes and students you deal with? 13. Why did you volunteer for this research project? APPENDIX 1 MULTIPLE CORRELATION COEFFICIENTS FOR PREDICTOR AND CRITERION MEASURES APPENDIX I Multiple Correlation Coefficients for Predictor and Criterion Measures (M_= 9) Criterion: Withitness Predictor Variables Beta Weights Multiple R Self-Monitoring 4.31 .48 Locus of Control - .03 .49 Classroom S—M -6.34 .70 Criterion: Overlapping Self-Monitoring 6.01 .17 Locus of Control - .20 .26 Classroom S—M -11.33 .54 Criterion: Momentum Self-Monitoring - .01 .14 Locus of Control - .OO .24 Classroom S-M .19 .27 Criterion: Smoothness Self-Monitoring .50 .28 Locus of Control - .00 .33 Classroom S-M - .88 .61 136 REFERENCES REFERENCES Amidon, E. J., & Flanders, N. A. The role of the teacher in the classroom. Minneapolis, MN: Paul S. Amidon & Associates, Inc., 1963. Anderson, H. H. The measure of domination and of socially integra- tive behavior in teachers' contacts with children. Child Development, 1939, 19, 73-89. Baumrind, D. Current patterns of parental authority. 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