STUDENT ATTITUDES ABOUT POLICY COURSE SIMULATIONS Development In Business Simulation & Experiential Exercises, Volume 18, 1991 105 STUDENT ATTITUDES ABOUT POLICY COURSE SIMULATIONS John B. Washbush, University of Wisconsin-Whitewater Jerry J. Gosenpud, University of Wisconsin-Whitewater ABSTRACT The purposes of this study are (1) to describe the use of the Simulation Participation Attitude Scale (SPAS) to measure attitudes of business students toward whole enterprise simulations and (2) to examine student attitude differences associated with exposure to different simulations. BACKGROUND Numerous studies have documented participant attitudes favorable to the use of simulations in academic courses and particularly in business courses (Waggener, 1979; Wolfe, 1985; Williams et al., 1986; McLaughlin and Bryant, 1987). Additionally, Hergert and Hergert (1990) have concluded that student perceptions of simulation usefulness can be linked to the factors of course structure, student characteristics, game effort and performance, and game parameters. The question of attitude sets particular to specific simulations is an open question. The present researchers began this study with the concern that, in their own courses, they should explore the attitudinal efficacy of using different simulations as complementary activities to case analysis and formal lecture. This task seemed appropriate if for no other reason than to evaluate sets of learning activities in an attempt to improve student acceptance and, perhaps, student motivation. Both researchers routinely incorporate whole enterprise simulations in their administrative policy courses and have recently used the games Micromatic (Hinton & Smith, 1985) and Stratplan (Scott & Strickland, 1985). We were therefore interested in comparing student perceptions of each simulation. These simulations are run on microcomputers and are both intended for use in learning environments such as are found in business major administrative policy courses, and they are sufficiently complex for undergraduates. Micromatic requires more detailed analysis and planning in the functional areas (particularly production and operations) than does Stratplan. Micromatic is focused at the business level while Stratplan has more of a corporate level perspective. Therefore, Micromatic more specifically reflects the decision demands of the functional areas (accounting, finance, marketing, production) the typical undergraduate student is exposed to in common core courses. On the other hand, Stratplan is more specifically integrated with theoretical approaches to business strategy and policy. In both games students make as many as 60+ decisions per round with decisions recorded on floppy disks which are processed by the game administrator. Stratplan allows a maximum of 6 companies per industry while Micromatic permits as many as 15. The run length of Stratplan is a maximum of 10 decision rounds (10 years); that of Micromatic is considerably higher, with a practical maximum of about 12 decisions rounds (12 quarters). Micromatic is played on a simulated quarter-to-quarter basis with a single product, three-area scenario. Typical student decisions include advertising mix, sales force size and distribution, selling price, product improvements, workforce size, material orders, production scheduling and distribution, plant capacity and efficiency investments, environmental information requests, capital budgeting, and cash management. Stratplan offers a two-product environment with three marketing areas, the game can also be internationalized, and it is played on a year-to-year basis. Typical student decisions include advertising expenditures, sales force size and distribution, selling prices, product improvements, sales branch numbers, sales commissions, production scheduling and distribution, plant capacity and efficiency investments, capital budgeting, and cash management. RESEARCH DESIGN Research Questions This study attempted to evaluate student attitudes toward the use of whole enterprise simulations in undergraduate business major administrative policy courses by answering two questions: (1) What are student attitudes toward the use of simulations in policy courses? (2) Are there any differences in attitudes of students depending on the game used? These questions were used to construct the following research hypotheses: H1: Students have neutral attitudes toward the use of simulations in policy courses. H2: Student attitudes toward the use of simulations are independent of the game played. H3: Student attitudes toward the use of simulations are independent of student major. H4: There is no association between student attitudes toward the use of simulations and simulation performance. Hypothesis 2 is the central focus of this study. The other hypotheses are important because they could help explain variations in attitude, especially if attitudes did not vary across games played. Population and Sample The population for this study is all students enrolled in undergraduate business degree programs that are accredited by or conform to the curriculum guidance of the American Assembly of College Schools of Business (AACSB). The sample used for this study was comprised of three sections of undergraduate business students, enrolled in the Administrative Policy capstone course, at a medium-sized mid-western university with a large, accredited business college. The study was completed Development In Business Simulation & Experiential Exercises, Volume 18, 1991 106 during the spring 1990 semester. The three sections were all taught by the same instructor (Instructor A) and contained 101 students (33, 34, and 34 students respectively), including 59 males and 42 females. To evaluate possible instructor differences and influences, two additional sections (ii - 32, 26) taught by the other researcher (Instructor B) were examined using the attitude survey. With the exception of simulation exposure, the three experimental sections were identically structured, were exposed to the same instructional and case materials, and were similarly managed and graded. Each section consisted of 10 student groups (3-4 students), groups being formed by student self-selection. One section used Micromatic in all groups throughout a 12-week period. In the second section each student group used Micromatic for 6 weeks and Stratplan for 6 weeks. The third section’s groups used only Stratplan for 12 weeks. In each section, students played for six weeks, were graded on simulation performance, and then commenced a new round of simulation play, with modified market growth scenarios, for the second six weeks. The two comparison sections used only Stratplan for 10 weeks of play, one maintaining a group format throughout play, the other beginning in-group format but shifting to individual play at the mid-point. Instrumentation A survey questionnaire called the Simulation Participation Attitude Scale (SPAS) was developed by the principal researcher and was administered at the end of the semester following completion of simulation play. The original SPAS used a summated Likert-scale format and consisted of 55 statements to which students responded according to their feelings by Indicating their agreement and strength. Item-to- total score Pearson correlations were computed for item analysis purposes. Using a technique outlined by Guilford (1965), total instrument reliability was Calculated by using the mean item-test correlation as an estimate of the mean item intercorrelation in the Spearman- Brown formula. Filler Items and several items having low or negative correlations, and one item containing a potentially confusing spelling error, were removed. The statistical reliability of the instrument in final form was estimated at .894 (entire instrument reliability, without items removed, was estimated at .843). Analysis of Data Data analysis was conducted using Minitab release 7.2 on an microcomputer. Total attitude-scale scores were compiled and mean item scores were computed on a section-by- section basis. Oneway analysis of variance (ANOVA) was conducted on total attitude-scale scores. Regression analysis was performed comparing simulation attitude-scale scores to simulation performance grades. Descriptive statistics were also calculated for the two sections of students taught by the second researcher and ANOVA was additionally performed on data from all five sections. FINDINGS Hi: Students have neutral attitudes toward the use of simulations in policy courses. Hypothesis 1 was tested by computing mean item scores for each experimental group. The mean item scores were examined by t-test to determine whether they were significantly greater than 3.5 (a neutral response score). In all cases the group mean item scores were positive and significantly greater than 3.5. Hypothesis 1 was rejected. The finding of positive attitudes expressed by students is consistent with previous research findings. Table 1 summarizes these data for Instructor A’s three experimental groups and Instructor’s B’s comparison groups. TABLE 1 MEAN TOTAL AND ITEM SCORES BY GROUP SIGNIFICANCE TESTS OF MEAN ITEM SCORES Inst Simulation Mean Total Scores(Std Dev) Mean Item Scores (Std Dev) t-ratio A All Micromatic Micromatic- Stratplan All Stratplan 169.06 (12.59) 163.18 (10.21) 156.53 (16.79) 4.696 (.035) 4.533 (.284) 4.348 (.466) 19.65~ 21.23~ 1O.60** B All Stratplan All Statplan 152.64 (12.70) 155.90 (20.73) 4.240 (.353) 4.331 (.567) 11.87~ ** p <= .001 Development In Business Simulation & Experiential Exercises, Volume 18, 1991 107 H2: Student attitude toward the use of simulations are independent of the game played. Hypothesis 2 was tested by performing a one-way analysis of variance (ANOVA) of total attitude scores by group. The analysis was performed once on the experimental groups and once on all five groups including the comparison groups. A significant F score was found in both cases with the highest group mean attitude scores occurring in the all-Micromatic group, the next highest in the group which used both Micromatic and Stratplan, and the lowest in the all Stratplan groups. Hypothesis 2 was rejected. More positive student attitudes were associated with the playing of the Micromatic simulation as compared to the Stratplan simulation. Table 2 summarizes these data for the three experimental groups and the two comparison groups. H3: Student attitudes toward the use of simulations are independent of student major. Hypothesis 3 was tested by performing one-way ANOVA of total attitude scores by major. The analysis was performed once on the experimental groups and once on all five groups. No significant F scores resulted in either case. Hypothesis 3 was not rejected. Student attitudes were not associated with undergraduate major. Table 3 summarizes these data for the three experimental groups and the two comparison groups. TABLE 2 ONEWAY ANALYSIS OF VARIANCE OF TOTAL ATTITUDE SCORES BY GROUP Groups Simulation Played Mean Scores F Experimental 1 (33) 2 (34) 3 (34) Micromatic Only Micromatic/Stratplan Stratplan Only 169.06 163.18 156.53 7.25** All 1 (33) 2 (34) 3 (34) 4 (32) 5 (26) Micrornatic Only Micromatic/Stratplan Stratplan Only Stratplan Only (group) Stratplan Only (group to individual) 169.06 163.18 156.53 152.64 155.90 6.44** ** p <. .001 TABLE 3 ONEWAY ANALYSIS OF VARIANCE OF TOTAL ATTITUDE SCORES BY MAJOR Groups Undergraduate Major Mean Std Dev F Experi- Accounting (19) 165.95 16.46 mental Finance (21) 163.76 10.84 N=l0l Economics (2) 153.50 19.09 Mgt Computer Sys (5) 167.60 14.64 General Business (6) 163.00 9.82 Production/Opa (2) 156.25 10.96 General Management (6) 156.58 14.17 Personnel/HRN (6) 173.17 10.50 Office Adinin (1) 171.00 0.00 Marketing (29) 159.72 16.84 Financial Planning (4) 160.00 5.23 0.89* All Accounting (36) 159.43 15.84 N=159 Finance (35) 164.23 13.72 Economics (2) 153.50 19.09 Mgt Computer Sys (5) 167.60 14.64 General Business (14) 158.79 13.72 Production/Ops (4) 153.37 10.55 General Management (8) 155.31 12.21 Personnel/HRN (13) 159.46 24.02 Office Admin (1) 171.00 0.00 Marketing (37) 156.53 16.66 Financial Planning (4) 160.00 5.23 * Not significant Development In Business Simulation & Experiential Exercises, Volume 18, 1991 108 H4 There is no association between student attitudes toward the use of simulations and simulation performance. Hypothesis 4 was tested for experimental groups by performing linear regression of simulation performance grades on total attitude scores and then regressing total attitude scores on simulation performance grades. The simulation performance grades used were those assigned by the instructor at the 6-week (weeks 1-6) and 12-week (weeks 7-12) periods of play. These grades were awarded on a group basis, with each person in a group receiving the same simulation performance grade. Grades were determined by ranking the teams on a continuous scale (70-100) using the following factor weights: Micromatic Sales 20% Income After Taxes 40% Earnings Per Share 20% Return on Sales 5% Return on Assets 5% Return on Equity 5% Stock Price 5% Stratplan Market Share 20% Profits 40% Share Holder Value 20% Total Assets 6.6% Return on Investment 6.7% Stock Price 6.7% For the regression performed with simulation grades awarded at the 6-week point, no significant regression coefficients resulted and no variance explanation occurred. For those performed with grades awarded for the second six weeks of play, significant regression coefficients and substantial variance explanation was found. Thus, there was a positive relationship between second-round simulation performance and attitudes (and vice-versa). The relationship between simulation performance and attitudes is consistent with the findings of Wolfe (1985). Additionally, it is not possible to assert causality between attitude and performance or performance and attitude. Hypothesis 4 was rejected. Table 4 summarizes these data for the experimental groups. DISCUSSION The most students favor of important displayed Micromatic finding of this study is that significant attitude differences in over Stratplan. While it is not possible to assert causality, speculate on possible causal Stratplan, Wolfe and Nielson Stratplan is inconsistent in functional area detail. The decisions apply to marketing pertaining to production and For example, game players do it is reasonable to factors. In a review of (1987) noted that its handling of firm majority of detailed variables while those finance are very general. not have to consider TABLE 4 LINEAR REGRESSION OF SIMULATION PERFORMANCE GRADES AND TOTAL ATTITUDE SCORES FOR EXPERIMENTAL GROUPS Regression Coefficient t-ratio Adj R2 (%) 6-week grade on total attitude score .03823 .86* 0.00 Total attitude score on 6-week grade .19240 .86* 0.00 12-week grade on total attitude score .17855 3.69** 11.20 Total attitude score on 6-week grade * Not Significant ** p < = .01 Development In Business Simulation & Experiential Exercises, Volume 18, 1991 109 capacity change lead times, they do not purchase and manage raw materials and work-in-process inventories, they do not directly manage the workforce, and they do not differentiate between bonds and loans. On the other hand, Micromatic players must manage all these types of practical, concrete details and more. Micromatic is therefore more balanced in analytic demands and decision specifics required in the functional areas of marketing, finance, and production. Also, the concrete nature of Micromatic analyses and decision making permits easier accounting analysis and more precise cost and income projections. Thus, there appear to be two explanations for the presence of more positive attitudes expressed by Micromatic players. First, that game is more consistent with the demands that can made on the learning experiences of students who have progressed through the traditional functional common core of business subjects. Secondly, Stratplan requires more abstract, corporate-level analyses and decisions, concepts less familiar to business undergraduates. We suspect that the issue is rooted in students’ perceptions of the degree of congruence between academic experience and their valid expectations of soon finding employment as managers of functional, concrete responsibilities. The abstractness of Stratplan, however, may be more appropriate for and comfortable to graduate students who have substantial functional-area managerial experience. The fact that systematic differences were independent of academic major suggests that the game itself was a major factor in influencing student attitudes toward the use of whole enterprise simulations in administrative policy courses. Additionally, these data suggest a performance- attitude-motivation link. In the Micromatic-only section, simulation performance grades for the second 6 weeks of play were higher than those for the other two experimental sections. Although these differences were not statistically significant, we suspect that higher Micromatic grades (i.e., better simulation performance) improved attitudes, influenced motivation, and enriched the learning environment. APPENDIX Listed below are the statements in the final form of the Simulation Participation Attitude Scale (SPAS). Complete instrument copies may be obtained from: John Washbush Management Department University of Wisconsin-Whitewater Whitewater, WI 53190 (414) 472—5457 1. Business policy courses should NOT use management simulations. 2. It is important to learn how to analyze practical business problems and make decisions to solve them. 3. It is NOT important to take responsibility for decisions one makes in business. 4. I am more easily motivated to be involved in a simulation than a text case. 5. Simulations should focus on strategic variables. 6. Simulations should effectively integrate the core courses of the business major. 7. Simulations should include financial details such as cash management decisions, negotiating the conditions under which capital is raised, and capital structure. 8. Business policy courses should focus more on top-level management problems. 9. Business simulations should NOT group students in teams, rather students should play alone. 10. I liked playing the simulation. 11. I have NOT been adequately prepared for the kinds of analysis required to make simulation decisions 12. I would have rather done more case analyses and NOT have spent so much time making simulation decisions. 13. Simulation decisions are easier to make after gaining several rounds of experience. 14. Our simulation decision sessions were dominated by one or two team members. 15. Playing the simulation did NOT help me gain a better understanding of the complexity of business decision making. 16. I feel better prepared to accept managerial responsibilities as a result of my simulation experience. 17. It is important to be aware of and involved in day to day operational details of a company. 18. A manager can get into trouble by NOT knowing how to make marketing decisions. 19. A manager can get into trouble by NOT knowing how to make accounting decisions. 20. A manager can get into trouble by NOT knowing how to make finance decisions. 21. A manager can get into trouble by NOT knowing how to make operations decisions. 22. Inventory management is important to business effectiveness. 23. I understand the importance of effectively managing cash. 24. I understand the importance of effectively managing inventory. 25. I understand the importance of effectively managing the size and training of the work force. 26. Costs can be more important to profitability than sales volume. 27. I understand financial leverage and its implications for earnings per share. 28. I understand operating leverage and its implications for effective cost control. 29. I learned a lot about things outside my major. 30. I do NOT like simulations in which there are many specific details to evaluate and manage. 31. I like simulations where the problems are at the strategic level. 32. Making a business work effectively requires the cooperative efforts of people with differing skills. 33. I know why my company finished where it did. 34. Top managers do NOT need a rounded exposure to marketing, accounting, finance, and operations. 35. After several decisions the simulation was NO LONGER challenging. 36. After several decisions the simulation was NO LONGER fun. 37. I feel that I could NOT effectively continue playing the simulation alone. Development In Business Simulation & Experiential Exercises, Volume 18, 1991 110 Guilford, J.P. (1965) Fundamental Statistics in Psychology and Education New York: McGraw-Hill. Hergert, M., and Hergert, R. (1990) “Factors Affecting Student Perceptions of Learning in a Business Policy Game”, Developments in Business Simulations & Experiential Exercises, 17, 92-96. Hinton, R.W. & Smith, D.C. (1985) Stratplan Englewood Cliffs, NJ: Prentice-Hall. McLaughlin, F.S. & Bryant, G.M. (1987) “A Comparison of Student Perceptions With Accepted Expectations for Business Simulations”, Developments in Business Simulations & Experiential Exercises, 14, 135-137. Scott, T.W. & Strickland, A.J. (1985) Micromatic: A Management Simulation. Boston, MA: Houghton Mifflin Waggener, H.A. (1979) “Simulation vs. Cases vs. Text: An Analysis of Student Opinion”, Journal of Experiential Learning and Simulation, 1, 113-118. Williams, R.H., McCandless, P.H., Robb, D.A., & Williams, S.A. (1986) “Changing Attitudes with Identification Theory”, Simulation & Games, 17, 25-43. Wolfe, J. (1985) “The Teaching Effectiveness of Games in Collegiate Business Courses”, Simulation & Games, 16, 251-288. Wolfe, J. & Nielson, G. (1987) “Business Game Review: Stratplan”, Simulation & Games, 18, 153-159. Table of Contents Volume 18, 1991 Personality Types and Total Enterprise Simulation Performance Using DIS 'n DAT as a Decision Support System for a Marketing Simulation Game Theoretical Derivation of a Market Demand Function for Business Simulators The Ethnographic Case Study: An Experiential Approach to Teaching Retail Management Electronic Bulletin Board Systems (BBS): Support Software for Computer Simulations The New Budget Game Negame: A Cross-Cultural Role-Play to Introduce Students to the Familiarization Stage of Negotiations Modeling Short-Run Cost and Production Functions Using Sheppard's Lemma in Computerized Business Simulations Increasing Simulation Realism through the Modeling of Step Costs Predicting Simulation Performance: Differences Between Groups and Individuals A Facility Location Case to Stimulate Classroom Interaction Educational Effectiveness of Business Simulation Gaming: A Comparative Study of Students and Practitioner Perspective Ethical Dilemmas in Experiential Learning: Issues and Strategies A Critical Review and Assessment of ABSEL's Award-Winning Procedures and Protocols Political Risk: A Simulation for Business Practitioners Upside Down: A Cross-Cultural Game in Experiential Learning Gorby's Dilemma: From Communism to Free Enterprise in Two Hours Strategic Market: Planning with the COMPLETE Product Portfolio Analysis Package: A Marketing Decision Support System Career Concepts and Total Enterprise Simulation Performance Experiential Learning in Human Resources: A Performance Appraisal Application Managerial Motivation and Realism Among MBA Student as Viewed through The Looking Glass, Inc. Simulation An Experiential Approach to Teaching Data Analysis Using MYSTAT: Rationale, Procedures and Results Practicing What Was Preached: A Sequential Learning Model put to the Test Student Attitudes about Policy Course Simulations An Investigation of the Relationship Between Simulation Play, Performance Level and Recency of Play on Exam Scores The Effect of Leadership and Cognitive Processing Styles upon Peer Performance Evaluation: Implication for the Utilization of Simulations in Business Pedagogy On the Transfer of Market Oriented Business Games to Socialist Cultures An Application of Financial Analysis of the Business Firm in a Simulated Competitive Environment Collective Bargaining Simulation: An Exercise based on a Familiar Theme Making Business Policy a Strategic Management Experience A Student Exercise for Intergrating the Concepts of Power and Motivation The Boundaries Extended: An Experiment Comparing Dialectical Inquiry, Devil's Advocacy and Consensus Using the Executive Game Using a Simulation Package to Develop a Simulation Exercise in Cost Accounting Success Factors in Experiential Training for Creative Problem-Solving Teams An Experiential Approach for teaching Quality management Critical Success Ratios: A Comparison of Two Business Simulations in a Multi-Year Environment Stocklogs: A Classroom Exercise for Teaching the Logistical Relationship of Location and Inventory The Organizational Leadership Program Simulating Business Decision-Making: Using Statistical Cases for Classroom Exercises Scripting for the Classroom Upgrading the Business Strategy and Policy Game Developing Student Team-Building and Leadership Skills Using Computer-Aided Experiential learning Strategies Organizing and Outward Bound Field Trip An Architecture for Extensible Simulation Games Performance in the Capstone Business Course: What is the effect of Pedagogy, Learning Styles, and Student Motivation? Operational Strategy with Participant-Modifiable Parameters An Example of a Personal Selling Case Transformed into a Role Play Scenario Instructional Software: It's Evolution and Current State of the Art in the Business Curriculum Ascertaining Performance Variables for use in Determining Student's Grades in Courses Employing a Business Simulation Designing Management Seminars Using Business Simulations The Accounting Information Systems Course: Bridging the Gap between the Classroom and the Real World The Good Cooks Guide to Training Excellence: Working with Passion A Demonstration on Multiple Data Collection Methods: Seeing Strategic Issues Through the Looking Glass Simulation Systems Analysis and Design: Why Undergraduate Education gets a Failing Grade Accommodating Organizational Culture: An Evaluation of Management Development Delivery Modes in Varying Organizational Cultures Modeling Total Quality into Business Simulations The Political Futures Game Meeting Meeting Objectives