THE RELATIONSHIP OF COGNITIVE STYLE MAPS TO THE PREFERENCE FOR EXPERIENTIAL LEARNING OF UNDERGRADUATE STUDENTS Developments in Business Simulation & Experiential Exercises, Volume 9, 1982 54 THE RELATIONSHIP OF COGNITIVE STYLE MAPS TO THE PREFERENCE FOR EXPERIENTIAL LEARNING OF UNDERGRADUATE STUDENTS Marta B. Calás, University of Puerto Rico at Mayaguez Marta Colon de Toro, University of Puerto Rico at Mayaguez José H. Romaguera, University of Puerto Rico at Mayaguez ABSTRACT An exploratory study was undertaken to determine if cognitive styles of undergraduate business administration students would influence their preferences for learning through experiential methodologies. Cognitive maps for each student in the sample were obtained from Hill’s Cognitive Style Interest Inventory, while their preferences on experiential exercises were determined by the scores on an evaluating instrument which was administered after completing each exercise. This procedure permitted the comparison of the elements in the cognitive maps of those who had low preference versus those who had high preference for experiential exercises. Results indicated few differences between the cognitive maps of both types of students. Moreover, additional comparisons suggested that their preferences might also be influenced by the similarities or dissimilarities between their cognitive styles and those of their instructors. INTRODUCTION The relationship of learning styles to instructional methodologies has become of particular importance to academicians in recent years. This interest appears to derive from certain developments which have occurred in the educational field over the past two decades. Some of these are: 1.The increasing evidence that motivation to learn and actual learning are closely related [8; 6; 26; 5]. 2.The availability of alternative pedagogies and instructional modes which might augment the motivation within the learning situation. 3.The development of models which describe cognitive styles, and the design of instrumentation to determine cognitive styles of individuals. These styles have been related to preferred learning environments and activities. For those instructors and researchers who have been using experiential methodologies in their courses and projects, Kolb’s four-stage experiential learning model [2o]and its related instrument, Learning Style Inventory (LSI)[21] are well known. One important use given to the LSI has been to compare perceived learning in pedagogically different training situations, and to imply that certain pedagogies are better suited to specific learning styles[12;1;3519] . Nonetheless, over the past three years there have been some studies that indicate a definite bias on the current version of the LSI, rending it unreliable as a measuring instrument, even though not necessarily as a result of the limitations of the model upon which it has been developed [10; 4]. On the other hand, for those involved in teaching within the business and management fields, the conceptual framework of the Educational Sciences and the Cognitive Style Interest Inventory have seldom been applied for the purposes described above. Developed by Hill [15] at Oakland Community College, Michigan, it holds the assumption that learning has four distinctive groups of behaviors: A.Behaviors which deal with receiving information, categorized as follows: 1. Being able to read and understand written or printed messages in (a) words, T(VL) or (b)numbers, T(VQ). 2. Being able to listen and understand spoken messages in (a) word; T(AL) or (b) numbers, T(AQ). 3. Sensitivities to stimuli not directly affected by the culture, received by the five senses: (a)Sight- all those images not in coded language, Q(V). (b)Sound- all those images not in coded language, Q(A). (c)Smell- odors, scents, aroma, etc., Q(O). (d)Touch- softness, hardness, coarseness, heat, cold, etc., Q(T) (e)Taste- sweetness, sourness, acidity, bitterness, etc., Q(S) 4. Sensitivities to stimuli affected by culture, received as sensory images through the five senses: (a)Empathy- receive data through sensitivity to the feelings of others, Q(REM). (b)Esthetics- receive data through perceiving beauty, Q(RES). (c) Histrionics- receive data through perceiving staged behavior or role playing, Q(RH) (d)Kinesics- receive data through understanding body language, Q(RK). (e)Proxemics- receive data through judging the social and physical distance others desire, Q(RPR). B.Behaviors dealing with the setting in which data is interpreted, categorized as follows: 1. Individuality- work independently to interpret data, I. 2. Associates- work with peers or associates to interpret data, A. 3. Authority Figures- work with authority figures to interpret data, F. C.Behaviors dealing with reasoning to conclusions or decisions about data, categorized as follows: 1. Magnitude- reason inductively through the naming, organizing or classifying of data according to rules, policies, and/or definitions, M. Developments in Business Simulation & Experiential Exercises, Volume 9, 1982 55 2. Difference- reason inductively through contrasting and differentiating data, D. 3. Relationship- reason inductively through relating and comparing data, R. 4. Appraisal- reason inductively through reflecting on or appraising data using all three of the above modalities, finally selecting one of the three to make a decision, L. 5. Deductive- reason deductively through analyzing a Gestalt so as to discover its component parts, 0. D.Behaviors dealing with expressing data, categorized as follows: 1. Having to do with expressing data through coded written (a) words or (b) numbers, T(EW). 2. Having to do with expressing data through coded spoken (a) words or (b) numbers, T(EV). 3. Having to do with expressing data in non-verbal modest (a)Histrionics- express data through staging behavior or playing roles, Q(EH). (b)Kinesics- express data through performing body movements such as facial expressions and gestures, Q(EK). (c)Transactional- express data through maintaining an interaction which influences the goals or actions of others in a positive manner, Q(ETR). (d)Ethic- express data through the use of behaviors indicative of commitment to the task or obligation, Q(EET). (e)Temporal- express data through the use of a time framework imposed by others, Q(ETM). As could be seen from the above descriptions, these learning behaviors are not described in the same terms as those in Kolb’s model (even though Kolb’s Convergers appear to be high in deductive reasoning, while Divergers and Assimilators appear to be high in the appraisal reasoning process according to Hill’s model). Rather, its dimensions define on a more specific basis those individual characteristics and learning environments which an individual prefers to use in searching for meaning when involved with an educational task. Also, different from Kolb’s and from other models [27;32;36] this model and its corresponding instrument were developed to identify specific strengths and weaknesses on the learning ability of individuals, in order to design educational prescriptions with alternative methods of instruction, as a mean to enhance students’ achievement in their courses [29] Numerous research studies support the view that when instruction strategies are matched to student cognitive styles a higher level of learning can be achieved C14; 33 16;34;24; 11] while few have failed to show otherwise [3] Moreover, Retzke [30] found that the use of cognitive style information in the classroom had a positive and significant effect the motivational level of the students. His research indicates that students whose cognitive styles may be described as experiential or project oriented, and independent, had lower motivational levels than other students in traditional learning environments. These students showed greater gains in motivational levels than students with different cognitive styles, when involved in non- traditional learning activities. Nonetheless, as previously mentioned, few studies have attempted to utilize Hill’s model in research regarding leaning of bus mess- related subjects [7;31] even though some suggested its application in personnel selection and allocation 28;22J and in marketing for audience segmentation [13]. Therefore, because Hill’s model, according to the review of the literature, appeared to be a promising alternative in the definition of learning styles which could be better related to certain pedagogies in business administration education, this study utilized the theory to determine whether any element in the cognitive style of business administration students was related to preference in learning from experiential activities [17] Furthermore, two major research questions were formulated for the investigation: 1. Are certain cognitive elements unique to those business administration undergraduates who have a preference for experiential exercises as a learning methodology? 2. Are certain cognitive elements unique to those business administration undergraduates who have a dislike for experiential exercises as a learning methodology? METHODOLOGY During the second week of classes, thirty five business administration students undergraduates who were enrolled in an introductory Personnel Management course for the first semester of academic year 1981-1982 responded to the Cognitive Style Inventory developed by Hill. These students comprised 62% of total enrollment for the course distributed in two sections, each with a different instructor. Student responses to the 232-question instrument were recorded and analyzed as to define a cognitive style map for each subject, listing the elements of their cognitive styles in the 29 categories within the four groups of behaviors identified by Hill. After the third week of classes, the instructor of each section initiated the use of one experiential exercise each week to illustrate the concepts being discussed in the course at that time. Once the exercise was completed and debriefed, the students had to evaluate it using a modified version of an instrument designed by Hoover and Whitehead [18] to evaluate courses using alternative teaching methodologies. This instrument is shown in Appendix I. The instructors chose the exercises by mutual agreement and maintained uniformity in the administration and debriefing procedures, to control for variation in perception regarding the exercise itself. The scores which resulted from the evaluation of six exercises were used to construct two groups with the 35 students. Group I, with 18 students, showed high preference for experiential exercises, while Group II, with 13 students, showed low preference for experiential exercises. High preference was defined as composite mean scores, in the evaluating instrument for the exercises, of 4.3 and above on scales with a range from 1 to 7. Also, they have to show scores above the mean preference scores for no less than three exercises. Low preference was defined as composite mean scores below 4.3 on the same scales, which were also below the mean preference scores for no less than three exercises. On account of these definitions, four cases which did not fulfill both requirements were eliminated from the original sample. Developments in Business Simulation & Experiential Exercises, Volume 9, 1982 56 Thereafter, the 29 elements in the cognitive maps of students in Group I were compared to the same elements in the cognitive maps of students in Group II, using t-tests to measure the differences in the scores. RESULTS Only two cognitive elements appeared to be significant in the differences between Group I and Group II. These were: preference to receive data through perceiving beauty Q(RES) and preference to express data through maintaining an interaction which influenced the goals or actions of others in a positive manner Q(ETR). in both instances, Group I (those with a high preference for experiential exercises) had high scores in the cognitive elements while Group II (those with a low preference for experiential exercises) had low scores. The differences were significant at the .01 level. Moreover, since only two differences were found, an additional inspection of the data was performed. At this time each group was separated by instructor, and cognitive elements of each were again compared. It was suspected that the similarities in the cognitive styles of high preference and low preference groups could be a result of students indicating preference for the exercises on account of their like or dislike for the instructor rather than for the exercise as such. Other studies have shown that a high degree of match between the cognitive maps of students and teachers could account for positive perceptions of each other, while the opposite might hold true when the cognitive maps are dissimilar (25; 2; 23]. In this case the instructors’ cognitive maps presented differences between themselves in 13 of the 29 cognitive elements, which could ,therefore, influence the preference of students in opposite directions. Groups I from both sections were compared and no significant differences were found, but the comparisons between Groups II indicated significant differences (at the .05 level) in their preference to work with authority figures F, and their preference to express data through performing body movements such as facial expressions and gestures, Q(EK). Furthermore, these two elements were different in the cognitive maps of the instructors. The responses indicated a tendency to have low preference for the exercises if there were low similarities between the cognitive elements of the students and of the instructors, while the opposite was true for those who had high preference for the exercises. Comparisons between Group I and Group II for each section showed significant differences (at the .05 level) in the four items mentioned above. DISCUSSION The results indicate that the cognitive style concepts as defined by Hill, and the Cognitive Style Interest Inventory could provide a functional system to determine if experiential methodologies could be successful in a particular course. The criterion of success, however, was defined as preference for the methodology and its ensuing motivation, rather than the degree of achievement in the course. On the other hand, interactions between the cognitive elements of students and instructors, as well as the cognitive elements which might be required by the methodology, could help to explain some of the ambiguities observed. For example, high Q(RES) and high Q(ETR) appear to be logical elements in the cognitive maps of those who might have high preference for experiential exercises, but the same could be said for other factors such as T(EV), Q(A), Q(V), Q(R~21), Q(RH), Q(RK), A, L, Q(EH), Q(EK), Q(EET), and Q(ETM). However, most students in the sample were high in these elements, regardless of their preferences for experiential exercises. This suggest that consideration should be given to other factors before prescribing the experiential methodology in courses where students indicate high scores in cognitive elements such as those mentioned above. Further, Group I in one section had high scores in F, which is the preference to work with authority figures to interpret data, while Group Tin the other section had low scores in the same element, but their scores, within each section, were similar to that of the instructor. It is implied that high scores in this particular element should be considered a negative factor for the experiential learning situation, unless accompany by high scores in A, the preference to work with peers and associates to interpret data. Nevertheless, all the groups (I and II) in both sections were low in A, while the instructors were high in that element. The above observations suggest complex relationships derived from the application of the Educational Sciences concepts to the experiential pedagogies, but these results should be interpreted with caution since the data were obtained from a limited sample, and only a small number of experiential exercises were performed. Also, the validity of the instrument used to evaluate preference for the exercises could be challenged. CONCLUSIONS AND RECOMMENDATIONS Cognitive Style Maps permitted to define learning characteristics of business administration undergraduates, and to determine those elements which might influence their preference for experiential learning methodologies. Some of these elements appeared to be related to preferences for experiential exercises, while other appeared to be influenced by the instructors’ cognitive styles. Nevertheless, limitations in the data prevent further generalizations. Future studies, with larger samples, and within more intensive experiential courses, could permit the definition of a cognitive profile for those who derive motivation when learning in experiential environments. Moreover, other investigations should indicate if there are any relationship between achievement and certain cognitive elements in experiential courses. 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Table of Contents Volume 9, 1982 The Value of Conjoint Analysis in Enhancing Experiential Learning The Effect of Participation in a Collective Bargaining Simulation on the Expectations and Attitudes of Union and Management Representatives Conflict Resolution in Experiential Learning The Use of Simulation to Test Theories of Bargaining in a Business Context The Nominal Group Technique: A Vehicle for Improving Case Method Courses A Framework for Developing a Business Policy Case Produce Your Own Video Cases for Classroom Use: A Demonstration An Experiential Effect from Charismatic Encounters Nine Topic Oriented Mini Simulations: Descriptions, Purposes, and Observations A Hospital Simulator (HOSPSIM) A Report of the Model and Results Expected from Field Testing An Evaluation of SLIM (A System Laboratory for Information Management) An Experiential Exercise Introducing Students to the Role Ambiguity Faced by Salespersons The Advertising Research Project as an Innovative Experiential Learning Technique The Small Group Research Project: An Experiential Learning Approach for Undergraduate Marketing Research Students The Relationship of Cognitive Style Maps to the Preference for Experiential Learning of Undergraduate Students The Learning Style Inventory Debate Revisited: An Empirical Assessment fo the Construct Validity Issue Related to Experiential Learning Theory Conducting a Classroom to Facilitate Career Goal Attainment Corporation Executives' Ratings of Policy Learning Techniques The Generation and Application of Evaluation Criteria for Management Policy and Strategy Simulation Games Experiential Opportunities with Microcomputers Leading Students to Learning: The Teacher's Obligation An Experiment in Teaching Principles Courses: The Mini Debate Formula Developing Creative Thinking Through Experiential Learning Heuristic and Systematic Evaluation of Policy: Exercise in Decision Making A Case Study Approach for the Litigation Decision: Employing Decision Analysis to Determine When a Business Should Settle or Go to Court Learning Negotiation Skills Through Simulation Union vs. Management: A Simulation of Collective Bargaining in Action Inside the Black Box: An Analysis of Underlying Demand Functions in Contemporary Business Simulations A Review of Channel Exercises and the Description of a New Alternative SIMCON I: A computer Based Simulation Model for Evaluating Physical Distribution Strategies Involving Order Consolidation Toward Competency-Based Management Education: The Interpersonal/Communications cluster The Value of Pre-Teaching in Role Playing Some Effects of Positive Personal Reinforcement upon Socializing Students in an Experiential Learning Course Who Gains and Who Does Not from Experiential learning Toward the Ultimate Experiential Exercise, the Student View Simulating Professional Writing Experiences in the Classroom The Johari Window as a Measure of Personal Development Windows Into Management: A Participative Aid to Learning Get Your Faculty Involved A Pedagogical Approach to Business Gaming for the Commuter Student Super Service for Computer Game Administrators Expand the Role of Simulation with Creative Scenarios The Delivery, Administration, and Evaluation of an Executive Development Program Using a Total Enterprise Business Game An Application of Experiential Learning in International Trade and Foreign Direct Investment International Management: Building Bridges Analysis of a Business Simulation Exercise: Organizational Survival and Success The FALRIS Organizational Scavenger Hunt Trainee V. Trainee Subordinates' Evaluation of Experiential Learning Longitudinal Analysis of an Innovative Teaching Intervention Student Perceptions of Effective Teacher Behaviors Revisited Realism and Learning: The Evolution of a Management Game A Merger and Acquisition Simulation A Stock Market Investor Simulation Experiential Learning in Consumer Behavior: Perceptual and Attitude Change Exercises The Recycling Industry Problems of Women in Management: A Role Playing Exercise for a Course in Contemporary Organizational Problems Experimental Three Weekend Course: Empirical Results A Process for the Analysis and Development of Course Content and Instructional Methodology for Large Class Sections Problems Associated with the Assessment of Experiential learning Using the Multiple Choice Test Combining Lecture and Simulation Teaching Methodologies Qualitative Determinants of Team Performance in a Simulation Game The Effects of Different Team Sizes on Business Game Performance Comparison of Problem-Solving Technologies: A Free Simulation Approach Consistency in Business Games A computer Simulation of Personnel Selection Decisions Giving Praise Exercise Job Enrichment A Look at the Spoken and Written Word in Organizations A Pattern of Group Communication A New Generation in Business Simulation Adapting Mainframe Business Simulations to Min Computers File Access is the Essential Prerequisite to Time-Flexible and Interactive Computer Simulation A Microcomputer Simulation for Teaching Retail Location Strategy Blocks & Chips: A computer-Assisted, Geno-Typical Entrepreneurial Game Development of a Self-Paced Course in Business Statistics The Involvement of Student Bodies in the Teaching of Advanced Technical Concepts Systems Learning Sequence: An Experiential Course Module for Management Information Systems An Experiential Approach to Developing Managerial Competencies Communication Research, Inc. An Experiential Learning Activity Developed as a Practicum for a Course in Organizational Communication