AN EXPOSITION OF GUILFORD'S SI MODEL AS A MEANS OF DIAGNOSING AND GENERATING PEDAGOGICAL STRATEGIES IN COLLEGIATE BUSINESS EDUCATION Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 34 An Exposition of Guilford’s SI Model as a Means of Diagnosing and Generating Pedagogical Strategies in Collegiate Business Education Jeanne H. Burns, Southeastern Louisiana University Alvin C. Burns, Louisiana State University ABSTRACT Of those few occasions where ABSEL thinking has been guided by a learning/teaching model, Bloom’s taxonomy of cognitive learning objectives has been exclusively adopted. While Bloom’s model is highly regarded, it has problems. Also, numerous other such models exist in the education literature. Guilford’s Structure of Intellect model is chosen as appropriate to college-level business education. The model is described in detail. It is used to diagnose various approaches and generate alternative teaching strategies. INTRODUCTION Collegiate business pedagogical development has been criticized for its lack of sound conceptual frameworks (Butler, Markulis and Strang, 1985). Nonetheless, some ABSEL thinking has been influenced by the learning objectives taxonomy espoused by Benjamin Bloom (1956). About a decade ago, Gentry, McCain and Burns (1979) advocated the adoption of Bloom’s taxonomy not only as a framework for research on pedagogical effectiveness, but also as a vehicle useful in theory construction and simulation/game development. Some ABSEL authors have sought to incorporate the taxonomy in their work (Butler, Markulis, and Strang, 1985; Gentry and Burns, 1981; Anderson and Lawton, 1988; Lewis, Yates and Gomolka, 1988); however, the adoption is far from universal. Bloom’s taxomony of the cognitive domain of learning objectives is briefly summarized in Figure 1. As can be seen, it proposes six different and increasingly more complex levels of learning: (1) basic knowledge, (2) comprehension, (3) application, (4) analysis, (5) synthesis and (6) evaluation. One can find ample evidence of the adoption of the taxonomy by educators at various levels. Three important advantages of Bloom’s paradigm have been noted by Maker (1982). They include widespread acceptance of the taxonomy by educators in general, relative simplicity and consequent easy applicability, and the useful guides, which the taxonomy provides for teachers. On the other hand, Marker (1982) also points out some significant problems with Bloom’s taxonomy. First, little research support exists for it. Second, it has limited scope, and third, its basic assumption of sequential, hierarchical learning may not be valid. There are, in fact, a great many models to be found in the education literature. Joyce and Weil (1979) have conducted an extensive review and identified over eighty different learning models. They categorized these into four classes: social interaction models, personal models such as those dealing with development of the self concept, behavior modification models, and information-processing models. Bloom's model falls into the last category as does a number of others. Many of these are competing, while others are complementary. For example, there is Krathwohl’s (1964) Affective Domain Taxonomy, which was developed as a companion to Bloom’s Cognitive Domain Taxonomy. Bruner’s (1960) theory on the basic structure of a discipline, on the other hand, is a fully developed philosophy about education, which sometimes clashes with others. Parnes (1967) has developed an elaborate process model intended to enhance the creative problem solving abilities of adults; while Williams (1970) has advanced a three-dimensional framework associated with teaching strategies for thinking and feeling. Also, Treffinger (1979) has promoted his model, which facilitates self-directed learning. The models cited above are simply exemplary of the rich body of literature and theory available with regard to frameworks for information-processing learning. This paper reviews one such model and illustrates how it can be applied to collegiate business courses at various levels as a means of diagnosing the learning process (es) involved and of suggesting alternative pedagogies. It should be obvious that the models differ with respect to underlying assumptions about the learning environment, learning processes, teacher intervention, and student intellectual maturity. Consequently, in reviewing the numerous alternative models and selecting the one presented, the authors applied five criteria. First, the model must be applicable to collegiate classroom environments. Second, the model had to be course-oriented rather than discipline or curriculum-based. Third, the model must be complex rather than simplistic, i.e., multidimensional. Fourth, the model should be capable of diagnosing a pedagogical strategy In current use; and fifth, the Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 35 model should provide for alternative teaching strategies to effect similar or better results. GUILFORD’S STRUCTURE OF INTELLECT MODEL The learning model, which best satisfied the five criteria just reviewed is Guilford’s Structure of Intellect model, popularly referred to as the “SI” model. The model is also known as the Sol” model based on Mary Meeker’s (1985) popularization of Guilford’s theories. The SI model was developed by Guilford based on his extensive testing and performance appraisal work with air force pilots (Maker, 1982). It is partially empirically based as it draws heavily on factor analyses results compiled by Guilford across a multitude of intelligence, achievement, and aptitude tests over multiple subject pools. Three fundamental assumptions (Guilford, 1966) underlying the SI model can be contrasted to Bloom’s taxonomy. First, Guilford assumes that there are many different types of intelligence within the adult mind; whereas, Bloom’s taxonomy implicitly assumes intelligence is a unidimensional concept. Next, Guilford believes that these intellectual capacities can be developed through alternative, specific strategies; while Bloom provides only general strategies. Finally, Guilford’s model is morphological (Gowan, Khatena, & Torrance, 1979); whereas, Bloom’s is hierarchical. That is, Bloom assumes that learning progresses uniformly upward from level to level in sequential fashion, while Guilford holds that each intellectual capacity is independent of others, and a person can display strengths in one intellectual area without necessarily displaying strengths in other related areas. Guilford’s model identifies where one can teach rather than what one should teach. His system is best represented by a three dimensional cube The authors have adapted Guilford’s original model and labeled the three dimensions as: Intellectual Operations; Representations; and Organization. The dimensions examine (1) five intellectual thinking processes that can be used; (2) as individuals respond to four different representations of information; (3) which can be organized in six different ways. Guilford maintains that all individuals are capable of performing tasks, which relate to the three dimensions; however, the degree and extent to which they demonstrate proficiency is highly dependent upon the development of separate categories within each dimension. Each cell in Guilford’s cube (i.e., 120 cells) represents the interaction of different categories across dimensions. To fully understand how this model can help educators diagnose learning processes involved in classroom based tasks, an understanding of the meaning of each dimension and its individual categories must be attained. Intellectual Operations. The first dimension represents five categories of intellectual thinking that individuals utilize when responding to various types of tasks (Guilford, 1977; Meeker, 1985). Cognition is the most basic of the categories and represents a person’s simple recognition, comprehension, and understanding of information. As an example, cognition would be displayed if an individual accurately identified the makes of Ford, Chevrolet, and Pontiac in a picture containing three cars. Memory involves the storage and retrieval of previously comprehended information. If asked one day later to name the three cars previously shown in the picture, an individual would retrieve from memory the terms: “Ford, Chevrolet, and Pontiac.” Evaluation, in turn, requires individuals to make comparisons, judgements, and decisions about information already comprehended. A task, which requires an individual to look at a picture of a Ford, Chevrolet, and Pontiac and select the car, which is most economical, would involve evaluative thinking. Divergent Production and Convergent Production rely upon Memory (i.e., retrieval of information) and Cognition (i.e., understanding of information). Both require individuals to generate new information from existing information, yet differ in how individuals respond to a situation. With convergent production, one uses analytical and logical thinking to arrive at one accepted response, while Divergent Production requires the use of flexible and original thinking as a variety of logical responses are generated for a given situation. A task involving convergent thinking might require an individual to specify how Pontiac could alter its existing models to make the automobiles as economical as Fords. In contrast, a task involving divergent thinking would require the same individual to specify how manufacturers could make future cars more economical. Representations of Information. The second dimension pertains to different ways in which information can be presented to individuals and involves four categories (Guilford, 1977; Meeker, 1985). Figural representations are the most basic of the four and appear as graphic images or concrete objects. A picture of a Ford, Chevrolet, and Pontiac car would be a figural representation. Symbolic representations are represented by symbols (i.e., letters, numbers, signs, equations, notations, etc.) which have no significance by themselves yet they represent something else. The Pontiac symbol could represent car sales on a graph. Semantic representations are expressions of meaning and appear in the form of words, sentences, and paragraphs. For Pontiac, the semantic representation might be the copy in an advertisement. Behavior representations are nonverbal signs (i.e., body language, Facial Expressions) that individuals project when communicating information. Two salesmen might verbally present the same information about the cost effectiveness of a Pontiac to a group of potential buyers; however, one Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 36 individual might convey a totally different message than the other individual due to behavioral manifestations. Organizations. The third dimension pertains to how Figural, Symbolic, Semantic, or Behavioral Information has been organized in a task and contains six categories (Guilford, 1977; Meeker, 1985). Units are the most basic of the six classes and involves an individual’s ability to react to single, unrelated items of information. Counting the number of Pontiacs sold in 1989 would be an example of thinking involving “units.” Each Pontiac represents one unit. Classes involve an individual’s ability to deal with information that has been grouped into meaningful sets because of similarities. Asking an individual to compile a list of cars that were economical would be an example of thinking involving “classes. Relations require an individual to respond to information, where connections, associations, or correlation’s exist between units of information. Prioritizing models of cars from least to most economical would involve relational” thinking. Systems are more complex than classes or relations and involve information that is interrelated. The development of a plan that would increase the gas efficiency of Ford would involve the use of “systems”. Transformations involve the modification, redefinition, or revision of Existing information in order to create something that is new or different. Requiring an individual to examine strategies of existing economy automobile companies and then recommend strategies to increase the economical aspects of Ford automobiles would be an example of thinking involving transformation. Finally, implication involves the use of existing information in order to determine consequences or make predictions about future events, Projecting future changes in the car industry based upon changes in the past would involve implication. APPLICATION OF GUILFORD’S MODEL Each cell in Guilford’s model corresponds to different types of learning situations in collegiate classrooms and the business world. The diversity of the learning situations can be seen in Figure 3 as the five different types of intellectual operations can interact with the four different types of information representations which can interact with the six different ways in which information can be organized for a given task. Guilford’s model clearly shows that there are many different ways in which one can examine an individual’s understanding of material in collegiate courses. Educators using traditional approaches to assess knowledge fail to tap many other aspects of learning that are equally important. Guilford’s model helps educators reassess areas of learning that are routinely being examined and recognize important areas that are being unintentionally ignored. Figure 4 illustrates typical examples. With basic business courses, the majority of the class assignments require students to recognize relevant information that they are studying (Cognition), recall the information when needed (Memory), and/or apply the information in order to answer a question correctly (Convergent Production). The students interact primarily with written/verbal words/sentences (Semantic) or numbers/symbols (Symbolic). They typically respond to details (Units), categories (Classes), or associations (Relations) when processing the information. The combination of these categories result in the kind of activities commonly found on examinations. It is not until students start to enter higher level business courses and become deeply involved in case studies, simulation, critiques and business plans that they are exposed to tasks which involve the use of some creative problem solving (Divergent Production) and evaluation thinking (Evaluation). It is also at this point that students become exposed to activities that allow them to see how information fits together into a whole (Systems). Developments In Business Simulation & Experiential Exercises, Volume 17, 1990 37 By matching experiential activities commonly found in individual professors’ classrooms (e.g., simulations, case studies, plans) to corresponding cells in Guilford’s model, one can clearly identify the various types of learning actually taking place in different courses. As can be seen In Figure 5, many such activities may involve the use of convergent thinking rather than divergent or evaluative thinking. Yet research has found that individuals who possess well developed divergent thinking abilities have a greater tendency to suggest Innovative ideas while Involved in their jobs (Guilford, 1977). College students may be rarely exposed to activities that require them to transform existing information or make implications, yet they are expected to demonstrate that ability when making projections or providing strategies in the business world. Collegiate courses also rarely provide students with feedback regarding their behavioral presentation of information when speaking in front of a group, yet this is an important factor that often determines whether a client accepts a new idea. The preceding exposition reveals the diagnostic power afforded by the SI model: by analyzing what he or she does, an educator may discover over- or under-emphasis on certain, critical intellectual process(es) development. It can also be used to suggest alternative representations of information or their organization to broaden the array of educational vehicles conceivable. While not a panacea, Guilford’s SI model clearly provides for a much more comprehensive framework than does Bloom’s Taxonomy and we recommend that collegiate business educators consider its adoption. REFERENCES Anderson, Philip and Leigh Lawton, (19S8), ‘Assessing Student Performance on a Business Simulation Exercise,” Developments in Business Simulation and Experiential Exercises, Vol. 15, Patricia Sanders and Tom Pray (eds.), 241-245. Bloom, Benjamin S., (1956), Taxonomy of Educational Objectives: The Classification of Educational Goals, Handbook I: The Cognitive Domain, New York, NY, Longman, Greens and Company. Bruner, J, (1960), The Process of Education, Cambridge, MA, Harvard University Press. Butler, Richard, Peter Markulis and Daniel Strang, (1985), “Learning Theory and Research Design: How has ABSEL Fared?”, Developments in Business Simulation and Experiential Exercises, Vol. 12, James Gentry and Alvin Burns (eds.), 86-90. Gentry, James and Alvin Burns, (1981), “Operationalizing a Test of a Model of the use of Simulation Games and Experiential Exercises,” Developments in Business Simulation and Experiential Exercises, Vol. 8, William Biggs and David Fritzsche (eds.), 48-52. Gentry, James, Kenneth McCain and Alvin Burns, (1979), Relating Teaching Methods with Educational Objectives In the Business Curriculum,” Insights into Experiential Pedagogy, Samuel Certo and Daniel Brenenstuhl (eds.), 196-198. Gowan, J. C., Khatena, J., & Torrance, E. Paul, (1979), Educating the Ablest, F. E. Peacock Publishers, Inc. Guilford, J. P, (1967), The Nature of intelligence, New York, NY: McGraw Hill Book Company. Guilford, J. p, (1977), Way beyond the IQ, Buffalo, NY, Creative Education Foundation, Inc. Joyce, B. and B. Weil, (1972), Models of Teaching, Englewood Cloffs, N.J., Prentice-Hall, Inc. Krathwohl, D.R., B. Bloom, and B. Masia, (1964), Taxonomy of Educational Objectives The Classification of Educational Goals. Handbook II: Affective Domain, New York, NY, David McKay Co. Lewis, William, Rebecca Yates and Eugene Gomolka, (1988), Developments in Business Simulation and Experiential Exercises, Vol. 15, Patricia Sanders and Tom Pray (eds.), 170-174. Maker, C. J, (1982), Teaching Models in Education of the Gifted, Rockville, MD: Aspen Systems Corporation. Meeker, R, (1985), SOl Training Manual, El Segundo, CA, SOl Institute. Parnes, 5., (1967), Programming Creative Behavior, Buffalo, NY, State University of New York at Buffalo. Treffinger, D. and R. Barton, (1979), Fostering independent Learning,” G/C/T, 7, 3-6; 54. Williams, F., (1970), Classroom Ideas for Encouraging Thinking and Feeling, Second Edition, Buffalo, NY, D.O.K. Publishers. Table of Contents Volume 17, 1990 The Impact of Decision Support Systems on the Effectiveness of Small Group Decisions - Revisited The Relationship Between Financial Performance and Other Measures of Learning on a Simulation Exercise Use and Effectiveness of an Analogy-Based Expert System Suggestions for Computerized Business Authors Dealing with Power: An Experiential Exercise Using Movie and Personal Diary Analysis Techniques A Model for Developing Student Skills and Assessing Outcomes Through Outdoor Training Computer-Aided Exercises Versus Workbook Exercises as Learning Facilitator in the Principles of Marketing Course An Exposition of Guilford's Si Model as a Means of Diagnosing and Generating Pedagogical Strategies in Collegiate Business Education Formal Planning and Simulation Team Performance: A Cross Sectional Approach Cases: Real Organizations in Real Time in the Classroom An Empirical Investigation of the Internal Validity of Marketing Simulation Game An Empirical Evaluation of the Pedagogical Value of Playing a Simulation Game in a Principles of Marketing Course Factors Affecting Effective Teaching of Strategic Planning: Some Preliminary Evidence An Experiential Exercise for Learning About the Relationship Between Organizational Form & the Project Management Process Accounting Communication Skills can be Taught in the Auditing Course Modeling Cost Functions in Computerized Business Simulation: An Application of Duality Theory and Sheppard's Lemma A Life Cycle Analysis of Decision Making for a Strategic Management Team What's the Problem? A Dynamic Model for Teaching Problem Solving Skills Experientially International Currency Fluctuations: Money$im, A Simulation Superstores: A Specialized Retailing Simulation Within a Specialized Marketing Curriculum Factors Affecting Student Perceptions of Learning in a Business Policy Game VC + EL = VL The Name Game: An Experiential Exercise in Intergroup Relations The Effects of Experiential Accounting Work Experience on Student Performance in Intermediate Accounting Courses The Results of Using the Experiential Activity Group Performance Evaluation in a Business Policy Setting Using a Legal Database to Describe the Legal Environment of Marketing (and Business) Matching Environmental Uncertainty and Organizational Configuration An Instructional Computer Simulation of Tampering in QC Executive Evaluation of Student Learning in the Looking Glass Simulation Group Personality Composition and Total Enterprise Simulation Performance An Expert System for Selecting Analytical Techniques for Analyzing Marketing Research Data Effects of Cognitive Styles on Responses in an In-Basket Simulation A Psychometric Analysis of Kolb's Revised Learning Style-Inventory Selecting and Developing Experiential Exercises Using Movies Application of a Real-World Strategic Management Model in the Classroom Demand Equations which Include Product Attributes Consumption as the Objective in Computer-Scored Total Enterprise Simulations The Effects of Decision Format and Evaluation on Simulation Performance, Decision Time, and Team Cohesion The Effects of Computer Related Assignments on Student Performance in Business Administration The Money Game: A Dynamic Simulation Including Random Shocks for Money and Banking Courses Methods for Evaluating Performance on Business Simulations: A Survey The Effects of Synergogy on the Policy Course: Significant Improvements in Student Learning and Teacher Evaluation Conditions and Outcomes of Trust in a Two-Person Bargaining Exercise Bankgame Enhancing Computer Business Simulation with the Use of VGA Graphics An Experiential Approach to Entrepreneurship An Advanced Simulation Method (ASM) for Multiple Objective Problems The Influence of Experiential learning Techniques on Student Recognition of Non-Primary Learning Styles Negotiating Mergers and Acquisitions: A Cocktail Napkin Approach Identification of Unintended Effects in Experiential Laboratory Exercises An Experimental Comparison of Paper and Pencil and Computer Aided Decision Support Tools Porting a Simulation from the IBM World to the Macintosh World A Transaction Cost Analysis of Experiential Learning The Development of Experiential Exercises for Courses in Entrepreneurship and Small Business Management The Assessment Center as and Experiential Classroom Exercise Pricing Strategy Algorithms for Playing Business Simulations Organizational Structures for International Operations: An Experiential Activity Simulation Emphasis in the Business School Capstone Course An Integrated Approach to Computerizing the Business Curriculum Cross-Cultural Business Negotiations Exercise Organizational Socialization and Gender Differences in Students at Work Understanding Student Work Experience: A Content-Analytic Approach Introducing Executive MBA Programs with Management Games An Analysis of Improvement in Business Decision Outcome with Sequential Use of Two Simulation Games Teaching Business Policy Utilizing Mass Lecture and Individual Case Labs Potholes Along the Road to Evaluating Learning Outcomes: The Case of Outdoor Management Training Experiential Learning for Interior Design Students: Using CADD, Lotus 1-2-3, and Wordperfect Cognitive Learning Using a Computer-Based, Qualitative Interactive Business Simulation Sex Discrimination: Does the Woman get the Job or Does the Best Man Win? A Search for Visual Aids to Support Experiential Learning Through the 1990's An Experimental Analysis fo the Effectiveness of Student Role-Playing in Sales Training How to Have Students Learn from their Term Projects Self-Evaluation Exercise (SEE): An Assessment of Class Contribution A Study of the Influence of Team Formation on Attitudes and Performance in Management Games A Hardware Based CIM Simulation Laboratory Model Test Substance Abuse in Organizations Micro Computer Training Models Teaching Forecasting, Cash Budgeting and Inventory Model Building Using SBTools A Comparison of the Effects of Experiential Learning Activities and Traditional Lecture Classes An Adjunct Writing Instruction Assistant, The Computer; With an Illustration Classroom Software for ABC Analysis Utilizing Information Processing Technology to Enhance the Business Policy Simulation Experience Progressive Cases Realistic Job Previews Vs. Traditional Job Previews: Experiencing the Differences and Understanding the Consequences Investment Analysis Using the Pragmatic Multiplier Approach A Computer Simulation Interface for Competitive and Firm Analysis Self-Assessment of Ethical Decision Making Predispositions Preparing Managers for Overseas Assignments An Inquiry into Japanese Marketing: Workshop on Teaching Japanese Marketing The Performance Appraisal Feedback Interview: A Role Play for Human Resources Management Teaching Counselor Selling techniques Using Experiential Techniques to Teach International Topics International Management Simulation Gaming: Current Status and Future Developments A Realism Comparison of Simulation Technologies/Methodologies A Time-Efficient Game to Illustrate Concepts Taught in Management Courses and Management Development Programs Teaching the Management of Technology The Concept of Face and the Applicability of Experiential Exercises in an Oriental Culture's