Simulations and Experiential Exercises - Do They Result in Learning? Have We Figured it out Yet? Developments in Business Simulation and Experiential Learning, Volume 33, 2006 SIMULATIONS AND EXPERIENTIAL EXERCISES - DO THEY RESULT IN LEARNING? HAVE WE FIGURED IT OUT YET? Barbara Howard SUNY Geneseo HowardB@Geneseo.edu Peter M. Markulis SUNY Geneseo Markulis@Geneseo.edu Daniel R. Strang SUNY Geneseo Strang@Geneseo.edu Joshua Wixom SUNY Geneseo JAW13@Geneseo.edu ABSTRACT In 1985, Butler, Markulis and Strang conducted a study to explore two key issues with respect to ABSEL research: First, the degree to which ABSEL papers conceptualized or utilized an educational framework, and second; the degree to which ABSEL papers used a standardized research design. This study continues the work of Butler and his colleagues by examining ABSEL contributions since the 1985 study. The goal of the continuation study is to determine if systemic shifts have occurred in published ABSEL research since its inception (in 1974) to the present. The authors found that papers appearing during the first 15 years of ABSEL did not differ significantly from ABSEL papers during the past 15 years in terms of research design or their use of an educational learning theory. Despite this consistency, there has been a slight increase in use of “treatment” and “treatment” coupled with “control” during the past 15 years. INTRODUCTION In 1985, Butler, Markulis, and Strang (referred to as Butler in the remainder of the paper) reviewed and classified all the ABSEL research contributions from 1974 to 1985 (Butler, Markulis, and Strang, 1985). The review focused on applying two yardsticks to the ABSEL papers. First, did the paper apply or use a standard educational framework in proposing, evaluating or discussing learning and learning goals. Second, did the paper make use of standard research protocols in hypothesizing or evaluating educational outcomes? According to Butler, one of the principal reasons for their paper was to the review what ABSEL researchers have done in terms of linking simulations/experiential exercises and learning. To that end, Butler chose to use Bloom’s taxonomy, a well established taxonomy in the field of education (Krathwohl, Bloom and Masia, 1964) to classify learning objectives and outcomes. Bloom’s taxonomy classifies learning outcomes into three domains: (1) cognitive (or knowing), (2) affective (or feeling), and (3) psychomotor (or doing). The cognitive domain deals with knowledge, comprehension, application, analysis, synthesis, and evaluation and with the development of intellectual abilities and skills. The affective domain refers to the way in which people handle things emotionally, such as feelings, values, motivations, and attitudes. It includes such factors as the degree to which learners are sensitized to learning, willingness to learn, inquisitiveness, and the ability to organize. The psychomotor domain refers to the degree to which motor skills (like hand-eye coordination) are developed and measured. In terms of research protocols, Butler evaluated the papers with respect to their use of randomization, control groups, and experimenter control of the treatment variable. According to Butler, these three criteria were chosen based on a review of the research design literature. Butler does not contend that these are the only indicators or even the best indicators of research designs, but they are fairly standard and well documented. Rationale for their use can 100 mailto:HowardB@Geneseo.edu mailto:Markulis@Geneseo.edu mailto:Strang@Geneseo.edu mailto:JAW13@Geneseo.edu Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Papers Published in ABSEL YEAR '74 '75 '76 '77 '78 '79 Total papers 52 43 54 48 49 70 YEAR '90 '91 '92 '93 '94 '95 Condensed 58 31 47 46 22 46 Full 38 28 45 29 34 32 Total papers 96 59 92 75 56 78 be found in Campbell and Stanley, (1963) and Shad Cook and Campbell, (2002). Indeed, Campbell and Stan (1963) suggest that an experiment is the “only means settling disputes regarding educational practice, …the o way of verifying educational improvements, and the o way of establishing a cumulative tradition in wh improvements can be introduced without the danger o faddish discard of old wisdom in favor of infe novelties.” THE FIRST ELEVEN YEARS What follows is a brief summary of the major findi from the Butler work. The major findings from the learning dimens classification were: • The affective domain was observed in 9% of articles, but a marked increase in these studies (50 occurred between the first four (1974-1979) second four years (1980-1984) of ABSEL • The cognitive domain was observed in 21% of all articles • The combination of cognitive and affective doma was observed in 25% of all articles • No ABSEL paper dealt with the psychomotor domai • The other category was the most frequent classificat observed in 45% of all articles In terms of research design, the most salient findings wer • 12.4% of all papers used a some type of control grou • no papers used randomization • 2% of the papers had treatment • 4.3% used control and randomization • 3% used control and treatment • no papers showed the use of randomization and con group • 2.6% of papers utilized all three research criteria • 71% of the papers reviewed were categorized as ei prescriptive or other The present paper is a continuation of the Butler analysis. The remainder of this paper presents a review o ABSEL published proceedings from 1985 to the present, using the twofold criteria established by Butler. Table 1 Proceedings Each Year, 1974 - 2005 '80 '81 '82 '83 '84 '85 '86 '87 '88 '89 69 80 78 43 67 49 67 64 62 45 '96 '97 '98 '99 '00 '01 '02 '03 '04 '05 27 40 40 39 24 14 11 8 18 10 24 42 31 42 34 35 39 35 46 54 51 82 71 81 58 49 50 43 64 64 ish, ley for nly nly ich f a rior METHODOLOGY The authors reviewed all the articles in Developments in Business Simulation & Experiential Learning, otherwise known as the ABSEL Proceedings, throughout its history from 1974-2005. Carefully following the classification scheme used by Butler, each of the articles was classified based on two aspects: the learning domain researched and the research design of the study. The three learning domains, based on Bloom’s framework, are; cognitive (mental skills or knowledge), affective (feelings or emotions), and psychomotor (actions or physical skills). The research design classifications consisted of; control group (C), randomization (R), experimenter control of a treatment (T), prescriptive (P) and other (O). ngs ion In order to provide results for this study that were consistent with the study conducted by Butler the researchers made every effort to use the same criteria and faithfully adhere to the same protocols as those used in the earlier study. For example, the authors first chose to review all the ABSEL proceedings (1974 to the present) to determine if their results matched with the findings of Butler. The authors found that there was very little difference between their review and Butler’s. all %) and the ins n This being said, the reader should note a few important caveats. First, ABSEL itself has evolved. To illustrate several obvious elements of this evolution, in ABSEL’s infancy many of the simulations were dependent on the available technology (i.e. main-frame computers and Fortran). Most of the new iterations of simulations are PC based. So changes in technology have clearly had an impact on the focus of ABSEL research. Second, ABSEL recently added a new Online track to respond to new modalities of pedagogy. One could imagine that this change might have an impact on ABSEL’s pedagogical paradigms. Finally, in 1990 ABSEL decided to designate research submissions as either a condensed paper or a full paper. As a result, it would be remarkable if observable changes were not apparent in the scholarly works that ABSEL published. Since condensed papers are likely to provide minimal insights into the dimensions that the researchers of this project were focusing on, it was decided to omit condensed papers in this analysis. ion, e: p trol ther f 101 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Percentage of Articles by D Affective Cognitiv 1974-1989 5.7 19.0 1990-2005 2.2 20.9 Combined 4.4 19.8 Percentage of Articles by Desig C R T CR 1974-1989 8.9 2.3 6.2 2.8 1990-2005 6.1 2.6 15.3 1.9 Combined 7.9 2.4 9.7 2.4 Legend: C = Control, R = Randomization, Control & Treatment, RT = Randomization RESULTS Prior to engaging in the comparative analysis might be appropriate to present a basic picture of ABS research, based upon the published articles in the ABS proceedings from its inception in 1974 until 2005. Tab provides information on the numbers of articles publis each year. As indicated earlier, ABSEL elected to pub both full and condensed papers in 1990. Exclud condensed papers, there are a total of 1528 arti published in ABSEL’s proceedings from its incep through 2005. The mean number of papers per year been about 48, with a high of 80 occurring in 1981, an low in 1996 of 24. The number of articles (by percentage) which w determined to have used Bloom’s taxonomy to evaluate discuss learning or learning outcomes was as follows: • The affective domain was observed in 4.45% of articles • The cognitive domain was observed in 19.85% of articles • The combination of cognitive and affective doma was observed in 32.1% of all articles • The psychomotor domain was observed in .7% of articles • The other category was observed in 43.1% of articles In terms of elements of research design over ABSE history, the authors found the following: • 7.9% of all articles have included elements of contro • 2.4% claimed to have used randomization • 9.7% have some kind of a treatment • 2.4% have elements of both control and randomizati • 4.7% coupled control and treatment • 2.5% had randomization and treatment Table 2 omain with Data Split Longitudinally e Psychomotor Affective/Cognitive .7 29.7 .5 36.1 .7 32.1 Table 3 n Elements with Data Split Longitudinally CT RT CRT None Other Pres 3.9 2.0 3.1 15.5 30.9 24.5 6.0 3.2 3.2 21.1 30.3 10.4 4.7 2.5 3.1 17.7 30.6 19.0 T = Treatment, CR = Control & Randomization, CT = & Treatment, CRT = all 3 elements, Pres = Prescriptive • 3.1% indicated the use of all three research design criteria • 17.7 of the articles claiming to be “research” exhibited none of the three research design elements , it EL EL le 1 hed lish ing cles tion has d a • 30.6% were categorized as “other" • 19.0% were simply prescriptive. In order to see if appreciable systemic shifts had occurred in ABSEL over its 32 years, the researchers decided to split the results into two halves, 1974 to 1989 and 1990 to 2005. It is interesting to note that this split matches the ABSEL decision in 1990 to categorize papers as either “full” or “condensed.” Tables 2 and 3 present the results of the first half and second half split. The most notable outcome from Table 2 is that there is no apparent change in terms of the percentage of articles focused on any of Bloom’s domains from the first half to the second half of ABSEL’s history. With respect to elements of research design, if any pattern arises in comparing the first half of ABSEL’s history to its second half, Table 3 shows that there seems to be a greater incidence in the use of “treatment” and “treatment” coupled with “control” in the latter half of ABSEL’s history. No other major change seems to be apparent. These results are notable ipso facto. Both could lead one to the conclusion that little evolutionary change has occurred in published ABSEL research over its history. ere or all all ins all all The authors then took the articles represented by each of the domains specified in Bloom’s taxonomy and compared them to the total number of articles published by ABSEL each year. Figures 1 through 4 present the results in terms of the three domains. A trend line was added to each figure. The trend line is thought to provide an indication of systematic shifts in focus, if they occurred. L’s l The trend lines in Figure 1 (affective domain) and Figure 2 (cognitive domain) do not appear to reveal any significant long-term shifts. Perhaps there has been a modest decline in the articles focusing on the affective domain over time. on 102 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Figure 3 (psychomotor domain) shows a great deal of “noise” from year to year, but on careful scrutiny it is apparent the range of articles swings from a low of 0% to a high of 7%. In this case the smoothed trend line traces out at virtually 0%, suggesting no major shifted occurred over time. Figure 4 (cognitive and affective domains) present the percentage of papers that focused on both domains. There are two aspects of that figure that warrant consideration. First, the has been a great deal of volatility from year to year in terms of the percentage of articles with both domains with the lowest percentage at 7.4 and the highest at 48.1. Second, the trend line reveals a consistent pattern that about a third of articles published in the proceedings focus on the combined affective and cognitive domains. Figure1. Affective Domain Figure 2. Cognitive Domain Year C% 2004199919941989198419791974 35 30 25 20 15 10 Percentage of Articles Focusing on the Cognitive Domain With smoothed trend line Year A % 2004199919941989198419791974 14 12 10 8 6 4 2 0 Percentage of Articles Focusing on the Affective Domain With smoothed trend line Year P % 2004199919941989198419791974 7 6 5 4 3 2 1 0 Percentage of Articles on the "Psychomotor" Specific Domain With smoothed trend line Year A C% 2004199919941989198419791974 50 40 30 20 10 Percentage of Articles Focusing on the Affective and Cognitive Domains With smoothed trend line Figure 3. Psychomotor Domain Figure 4. Affective & Cognitive Domains Year Co n% 2004199919941989198419791974 20 15 10 5 0 Percentage of with "Control" With smoothed trend line Year R an % 2004199919941989198419791974 12 10 8 6 4 2 0 Percentage of Articles with "Randomization" With smoothed trend line Figure5. Control Figure 6. Randomization 103 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 Year Tr t% 2004199919941989198419791974 10 8 6 4 2 0 Percentage of Articles with a "Treatment" Wither smoothed trend line Year CR % 2004199919941989198419791974 12 10 8 6 4 2 0 Percentage of Articles with "Control" and "Randomization" With smoothed trend line Figure 7. Treatment Figure 8. Control & Randomization Year CT % 2004199919941989198419791974 18 16 14 12 10 8 6 4 2 0 Percentage of Articles with "Control" and a "Treatment" With smoothed trend line Year R T% 2004199919941989198419791974 7 6 5 4 3 2 1 0 Percentage of Articles with "Randomization" and a "Treatment" With smoothed trend line Figure 9. Control & Treatment Figure 10. Randomization & Treatment Year CR T% 2004199919941989198419791974 9 8 7 6 5 4 3 2 1 0 Percentage of Articles with All Three Elements With smoothed trend line Year No ne % 2004199919941989198419791974 35 30 25 20 15 10 5 0 Percentage of Articles with No Research Design Elements With smoothed trend line Figure 11. All 3 Elements Figure 12. No Research Elements Figures 5 through 12 present the yearly percentages of articles with respect to the elements of research design. As with the learning domains, a smoothed trend line has been calculated to help visualize various trends. Figure 5 indicates what might be reasonably judged to be a systematic downward shift in the percentage of articles that had control as an element of research design. The trend line declines from about 11% to essentially 1% over the history of ABSEL. Figure 6 presents the percentage of articles with randomization and shows at most a very modest upward shift. Figure 7 provides evidence of some increase in the incidence of articles that include a treatment. It would seem that stronger research designs would have more than one of the three elements of research design. Figures 8, 9 and 10 depict the percentage of articles with pairs of the research elements coupled. Viewing Figure 8, it is apparent that no shift seemed apparent in terms of articles that contain both control and randomization. Interestingly, Figure 9 reveals what appears to be a small increased emphasis on articles that utilize the elements of control and treatment. Further, Figure 10 reveals a pattern of increased emphasis on the two elements of research design, randomization and treatment. Figure 11 reveals that a pattern of published research that shows any shift in articles displaying all three of the elements of research is equivocal at best with a trend line vacillating between 1% and 5%. Finally, and potentially most disturbing, the appearance of a long term trend of published ABSEL articles for which none 104 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 of the elements of research design are present is unquestionably upward. Explanations as to why that may be the case are left to the conjecture of the reader. Stating that “fundamental difficulties exist in the customary measurement of learning,” Gentry, Stoltman, and Mehihoff (1992) discuss measuring experiential learning. They note that it is difficult to know whether the student had obtained the desired knowledge prior to the experiential activity, that assessment of learning is inherently subjective, and that most tests of learning are not subjected to reliability and validity assessment. They do suggest that a common solution to properly measuring learning has been to use Bloom’s classification scheme identifying the different levels of cognitive learning. DISCUSSION In their 1985 study of research articles published in the ABSEL proceedings, Butler and colleagues found the following major conclusions: • ABSEL publications have generally fallen short of specifying clear learning objectives for simulations and experiential exercises, and Anderson and Lawton (1997) contend that without appropriate objective variables for a broad range of learning outcomes, the learning effectiveness of simulations will not be supported. They state that there is “little hard evidence that simulations produce learning or that they are superior to other methodologies.” A lack of rigor in the methodology and the selection of dependent variables are cited as the major issues. • ABSEL published proceedings generally failed to employ basic research methodologies. This paper, after reviewing all ABSEL publications since 1974, found similar conclusions to that of the Butler article. The call for stronger research and research designs has been echoed by several ABSEL scholars over the years. For example, Wolfe (1976) addresses this issue with respect to simulations and gaming and suggests that “Campbell and Stanley’s posttest-only control group design should serve as the barest minimum.” He goes on to say that even more rigorous designs such as the pretest-posttest control group design should be used because random assignments to the groups is difficult to achieve in practice. Wolfe contends that the research design is important, “but that the perfect theoretical implementation has not been obtained.” Five years later, an article by Wolfe (1981) reviewed the ABSEL Proceedings from 1976-1980 and found an abundance of pre-experimental designs and a dearth of true experimental studies. He contends that, at that time, none of the studies appearing in the proceedings met the criteria for external validity. According to Wolfe, the lack of rigorous studies added to the confusion about the effectiveness of simulations and even resulted in a loss of credibility with those outside the simulation area. Cooke, in a 1986 article, attests to the difficulty in designing and conducting research that measures the effectiveness of educational innovations. He argues that innovative teaching methods are often rejected based on a misunderstanding and application of Type I and Type II errors. Cooke goes on to suggest ways to alleviate this problem. A review of 25 years of simulation gaming research by Faria (2000) details the progression in ABSEL research from examining the relationship between performance and participant characteristics, to factors related to simulation performance, to the team vs. individual player characteristics debate. The article also looks at the effectiveness of games in strategy classes. He concludes that there is some evidence of the effectiveness of computer- based general management games used in strategic management classes and that the simulations are superior to the case method. However, a study to measure behavioral learning in a marketing simulation had mixed results. Finally, questions about the use of Bloom’s taxonomy as an appropriate way in which to not only study learning outcomes, but also to frame the issues related to learning have been raised. Schumann, Anderson, Scott, and Lawton (2001), for example, take a critical look at Bloom’s Taxonomy as a framework for assessing simulations as educational tools. Again citing the lack of definitive research results, Schumann, Anderson, Scott, and Lawton suggest that perhaps Bloom’s Taxonomy provides a framework for establishing learning objectives but may not be as helpful in assessing learning. They introduce a framework by Kirkpatrick (1998) and suggest that it may be a better framework for assessing the efficacy of simulations. Gosenpud (1990) contributed to the research design discussion by presenting problems inherent in experiential learning itself and the difficulty of designing rigorous evaluation studies. He focuses on three types of studies: straight evaluation studies, contingency studies, and studies pertaining to features of experiential learning. He concurs with the use of Bloom’s Taxonomy as an appropriate way to categorize outcomes. But his review of the literature again comes to the conclusion that there are very few “good” studies. Suggestions for future research include: tying outcome measures to learning goals, evaluating experiential learning on the basis of specified attitudinal outcomes, assessing the external validity of experiential learning and theory-based research. Cannon and Feinstein (2005) suggest that Bloom’s Taxonomy is quite popular because of both its simplicity and robustness. However, they contend that it is not the only approach. They state that “it is inadequate, because it is only one perspective on a phenomenon that occurs in nature, which is inherently so complex that no single framework could capture its every aspect.” Cannon and Feinstein think that the revision to Bloom’s Taxonomy as presented by Anderson and Krathwohl (2001) may be a better framework. The revised taxonomy addresses two dimensions of learning, a cognitive process dimension and a knowledge or content dimension. 105 Developments in Business Simulation and Experiential Learning, Volume 33, 2006 106 CONCLUSIONS It is clear that many articles published in the ABSEL proceedings did not employ either a strong research methodology or educational paradigm to track learning and learning outcomes. Nonetheless, as others have suggested, ABSEL represents an important forum in which to share and exchange ideas and valuable experiences, which will in turn provide the fodder for future research. That being said, ABSEL scholars may wish to consider a common framework by which contributors can discuss and share learning outcomes. ABSEL may also consider the submission of more research-oriented contributions by providing various incentives. A complementary approach is to consider ways in which ABSEL members work conjointly on research projects. For example, to deal with the vexing problem of randomization in university settings, as noted by Wolfe (1981), inter-college research designs offer a reasonable surrogate in many cases. Undoubtedly, ABSEL researchers will have to think critically as well as creatively on both these issues to maintain the vibrancy of the organization. REFERENCES Anderson, Lorin W. and David R. Krathwohl (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York: Longman. Anderson, Philip H. and Leigh Lawton (1997). “Demonstrating the Learning Effectiveness of Simulations: Where We are and Where We Need to Go.” Developments In Business Simulation & Experiential Learning, 24, 68-73. Reprinted in The Bernie Keys Library, 6th edition. Bloom, Benjamin S., Max D. Englehart, Edward J. Furst, Walker H. Hill & David R. Krathwohl (1956) Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook I Cognitive Domain. New York: David McKay Company, Inc. Butler, Richard J, Peter Markulis, and Daniel Strang (1985). “Learning Theory and Research Design: How Has ABSEL Fared?” Developments In Business Simulation & Experiential Exercises, 12, 86-90. Reprinted in The Bernie Keys Library, 6th edition. Campbell, Donald T. and Julian C. Stanley (1963). “Experimental and Quasi-Experimental Designs for Research.” Chicago: Rand McNally & Company. Cannon Hugh M. and Andrew Hale Feinstein (2005). “Bloom Beyond Bloom: Using the Revised Taxonomy to Develop Experiential Learning Strategies.” Developments In Business Simulation and Experiential Learning, 32, 348-356. Reprinted in The Bernie Keys Library, 6th edition. Cooke, Ernest F. (1986). “The Dilemma in Evaluating Classroom Innovations.” Developments In Business Simulation & Experiential Exercises, 13, 110-114. Reprinted in The Bernie Keys Library, 6th edition. Faria, A.J. (2000). “The Changing Nature of Simulation Research: A Brief ABSEL History.” Developments In Business Simulation & Experiential Learning, 27, 84- 90. Reprinted in The Bernie Keys Library, 6th edition. Gentry, James W., Jeffrey J. Stoltman, and Carol E. Mehihoff (1992). “How Should We Measure Experiential Learning?” Developments In Business Simulation & Experiential Exercises, 19, 54-57. Reprinted in The Bernie Keys Library, 6th edition. Gosenpud, Jerry (1990). “Evaluation of Experiential Learning.” Guide to Business Gaming and Experiential Learning, 301-329. Reprinted in The Bernie Keys Library, 6th edition. Kelley, Lane and Jeffrey Easton (1981). “Problems in Evaluation of Experiential Learning in Management Education.” Developments In Business Simulation & Experiential Exercises, 8, 137-140. Reprinted in The Bernie Keys Library, 6th edition. Kirkpatrick, Donald L., (1998). Evaluating Training Programs: The Four Levels (2nd Ed). San Francisco: Berrett-Koehler. Krathwohl, David R., Benjamin S. Bloom, & Bertram B. Masia (1964) Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook II Affective Domain. New York: David McKay Company, Inc. Schumann, Paul L., Philip H. Anderson, Timothy W. Scott, and Leigh Lawton (2001). “A Framework for Evaluation Simulations as Educational Tools.” Developments In Business Simulation & Experiential Learning, 28, 215-220. Reprinted in The Bernie Keys Library, 6th edition. Shadish, William, R., Thomas D. Cook, and Donald T. Campbell (2002). “Experimental and Quasi-Experimental Designs for Generalized Causal Inference.” New York: Houghton Mifflin Company. Wolfe, Joseph (1976). “Comments on the Perception, Identification, and Measurement of Learning from Simulation Games.” Computer Simulation and Learning Theory, 3, 288-294. Reprinted in The Bernie Keys Library, 6th edition. Wolfe, Joseph (1981). “Research on the Learning Effectiveness of Business Simulation Games—A Review of the State of the Science.” Developments In Business Simulation & Experiential Exercises, 8, 72. Reprinted in The Bernie Keys Library, 6th edition. Table of Contents Volume 33, 2006 Learning Assurance Using Business Simulations Applications To Executive Management Education Team Teaching In An Integrated Business Course Using Critical Problem Based Learning Factors In An Integrated Undergraduate Business Curriculum: A Business Course Success Personality Type And Strategic Planning Business Games As Strategic Management Laboratories The Relationship Between Students' Success On A Simulation Exercise And Their Perception Of Its Effectiveness As A PBL Problem Forecasting Accuracy And Learning: The Key To Measuring Simulation Performance The Business Strategy Game: A Performance Review Of The New Online Edition Using The Socratic Method And Bloom's Taxonomy Of The Cognitive Domain To Enhance Online Discussion, Critical Thinking, And Student Learning Using Negotiation Exercises To Promote Critical Thinking Skills Effective Leadership Experiences For Management Majors In A Futures Class The Role Of Learning Versus Performance Orientations When Reacting To Negative Outcomes In Simulation Games Is Pay Inversion Ethical? A Three-Part Exercise Simulations And Experiential Exercises - Do They Result In Learning? Have We Figured It Out Yet? Examining Program Management In Business Simulations: Student And Faculty Views Validating Business Simulations: Do Simulations Exhibit Natural Market Structures? Characterizing Business Games Used In Distance Education Utilizing Games In A Graduate Level Instructional Game Course Employment Interview Preparation: Assessing The Writing-To-Learn Approach Simulations - Bridging From Thwarted Innovation To Disruptive Technology Creating An Authentic Cultural Lens Using Case Dialogue Learning By Fire: Reflections Of A First Time Online Instructor An International Internship With A Service-Learning Focus Learner Participation In The Online Learning Experience: Help Or Hindrance? Any Given Sunday: Intervention In Pursuit Of Simulation Team Parity Beginning With The End: Creating An Experiential Exercise From Assessment Criteria Simulating Life Cycles: Life Span As The Measure Of Performance In Business Gaming Simulations It's Puzzling: Communications, Competition, And Cooperation Balanced Scorecard Implementation For Strategy Management: Variation Of Manager Opinion In Real And Simulated Companies Cases And Business Games: The Perfect Match! Three-Attribute Interrelationships For Industry-Level Demand Equations Using A Web-Based Module To Teach Information Literacy Decision Support System For Demand Forecasting In Business Games The Invalidity Of Profit=F(Market Share) PIMS Validation Of Marketing Games Online Market Test Laboratory With The MINSIM* Program The Gas Mileage Game - A Policy Simulation Delivered Cost And Differentiation Applied To Threshold 3rd Ed. The Effect Of Team-Leadership Modes On Team Performance: A Preliminary Study The Design And Use Of A Macroeconomics Simulation Using Maple Software: A Pilot Study The Instructor's Toolbox: A Meaning-Centered Framework For The Social Construction Of Experiential Learning Incorporating Strategic Product-Mix Decisions Into Simulation Games: Modeling The 'Profitable-Product Death Spiral' Group Composition And Groupthink In A Business Game A Direct Approach To Teaching Business Ethics A Decision Support System For Planning Sales, Production, And Plant Addition With Manager: A Computer Simulation Polish - American Entrepreneurial Business Cooperation Workshop Utilizing The Income/Outcome Simulation Student Leader Training Exercise Student Preference To Mode Of Learning In Hong Kong Experiential Learning For Technology-Based And Management Programme In Hong Kong: A China Study Tour A Price Game With Product Differentiation In The Classroom Discrete Event Modeling In A New Transportation Simulation Supply-Side Modeling In A Total Enterprise Simulation The Quality Game Towards A Massive Multiplayer Online Business Simulation Making The Connection: Improving Virtual Team Performance Through Behavioral Assessment Profiling And Behavioral Cues Individual Learning Producing A Learning Organization: 'Playing Dice With Polar Bears' Narratology and Ludology: Competing Paradigms or Complementary Theories in Simulation Framework For Evaluating Internet Research Using Children's Games To Illustrate Strategy Concepts: Is Less Better?