Integrating Analysis and Communication Skills into the Decision Science Curriculum*

The teaching of decision sciences presupposes that careful attention is directed toward improving students' critical thinking and analytical skills. This paper presents an approach to teaching quantitative methods classes that focuses on developing student skills in the areas of analytical and critical thinking through written and oral communication. The approach requires very little additional instructor preparation time and does not require the instructor to make major changes in either the content or organization of the course. While the instructor's investment is minimal, the benefits to the students appear to be substantial.     

Education CREATIVE THINKING AND INNOVATIVE EDUCATION IN THE DECISION SCIENCES

Creative problem solving is seldom addressed directly in the decision sciences literature. The first half of this paper reviews current thinking about creativity and its educational importance. The remainder addresses creative problem-solving processes and, in particular, the process developed by Parnes, Noller and Biondi [24] and Osborn [23]. This process has been integrated into an OR/MS problem-solving course which is described. Conclusions and implications for decision sciences education and practice in general are discussed.     

An Analysis of the Pedagogical Effects of Expert System Use in the Classroom

An experiment that examines the use of expert systems to enhance student learning in an introductory Production and Operations Management (POM) class is discussed. An experimental expert system, SCHEDULER, was built within the domain of scheduling. It provided students with the opportunity to experience working with and integrating scheduling heuristics, constraints, and management requirements. The experiment also exposed students to using, rather than having to build, computerized decision aids, and expert systems in particular. Measurements of student learning and assessments of student perception regarding use of expert systems indicate expert systems can provide a valuable enhancement to the learning environment.     

INSTRUCTING OPERATIONS DESIGN: AN EXPERIENTIAL APPROACH

Teaching an operations design course has major pedagogical challenges. (1) The design topics—output, process, facility, and work design—are necessarily taught sequentially, yet the decisions are integrative. (2) Instruction must be generic to service or product producers. (3) Discussing output design is difficult since students typically have had no exposure to the “product language” of engineering graphics. (4) No text is available which examines in sufficient depth all the operations design decisions. (5) Cases necessarily depict historical situations—process technologies and economic data—while operations managers must plan future directions for their productive systems. (6) While the commercial world contains fresh information and data, students are inexperienced in obtaining knowledge from the real world. (7) While the course presents an operations management perspective, students must recognize the information, data, and cooperation necessary from the other functional areas to successfully complete the operations design. To help overcome these seven pedagogical challenges, the students in the undergraduate and graduate operation design courses complete a comprehensive feasibility study for a new product or service and the entire productive system.     

Education TEAM-SIZE EFFECTS ON BUSINESS GAME PERFORMANCE AND DECISION-MAKING BEHAVIORS

The effects of various decision-making team sizes in a complex business game were studied. Firm size was associated with nonlinear performance results and decision curves resulting in differential learning outcomes, learning sources, attrition rates, and decisionmaking behaviors. A three-member format produced the highest learning levels while two-member firms experienced only marginally significant knowledge increases. Single-member firms experienced the most bankruptcies and dropouts. A contingency view of gaming effectiveness is suggested.     

An Investigation into the People-Sequential Heuristic Method of Group Formation

This study investigates the people-sequential heuristic method of group formation as proposed by Beheshtian-Ardekani and Mahmood [2] and examined by Muller [9]. Responding to Muller's call for continued research on this topic, we first replicate the seven hypothesis investigations presented in that study and then consider several additional hypotheses designed to more fully examine the value of the process to the group members themselves. The results of this study indicate that the balanced groups assignment method is not effective as a sole means of increasing learning or satisfaction with the project. Of the twelve hypothesized relationships, which, if supported, would favor the use of balanced groups over randomly assigned groups, only one was supported. These findings and their relationship to group learning theory are discussed.     

Assigning Students to Groups for Class Projects: An Exploratory Test of Two Methods

Beheshtian-Ardekani and Mahmood [1] recently offered a means of assigning students to groups for class projects to achieve a balanced distribution of student skills within groups. They assumed- but did not show-that the instructor would give weaker students a better chance to learn from stronger group members, that there would be greater synergistic learning effects, and that students would be happier with the project experience. This experiment tests the balanced-group method of assigning students using the people-sequential heuristic by comparing its effectiveness against the results achieved by random assignment to groups. The findings show that balanced groups have a modest advantage over groups formed randomly. Students in balanced groups felt slightly more satisfied with and challenged by the group and shared the work load more evenly. Within randomly assigned groups, student perceptions of the quality of the group-project learning experience were less homogeneous.     

A Quantal Choice Model for the Detection of Copying on Multiple Choice Examinations

It is difficult to devise a statistical test to detect one student copying from another. Many prior efforts falsely accuse students of cheating. A general methodology based on the quantal choice model of decision theory overcomes these problems. Three steps are involved: (1) for each item estimate the probability and the variance that a given respondent will select each response, (2) for pairs of respondents, these probabilities determine the expected number of matches, and (3) compare the critical value to the number of items matched. Methods differ based on the probability estimation technique. Four methods (simple frequencies, Frary, Tideman, and Watts modification [8], logit, and multinomial probit) are compared on theoretical and empirical grounds. Theory and results show that it is crucial to incorporate the variance of the probability estimates. The probit model has theoretical advantages over the other methods and produces more accurate results.     

An Evaluation of the Role and Performance of a Decision Support System in Business Education*

With the rapid growth in end-user computing, there has been an increasing demand on business schools to train managers in the use of computers for effective decision support. While computer-aided instruction (CAI) has been in vogue for over a decade, there are very few studies that evaluate the impact of computers on decision-making skills in a business education context. The study makes use of a controlled experiment to evaluate the impact of computers on the accuracy and quality of decision making in a business decision support context. It also addresses the relationships between decision performance and various student characteristics such as aptitude, attitude, domain experience, domain expertise, gender, and system experience. The study revealed that computer support positively influenced both dimensions of decision performance.     

A Comparative Analysis of the Relative Effectiveness of Four Dynamic Lot-Sizing Techniques on Return on Investment

The relative performance of dynamic lot-sizing techniques has been of considerable interest to researchers in recent years. While research has addressed performance in terms of cost-effectiveness, researchers have not determined the impact of dynamic lot-sizing techniques on return on investment (ROI) as it applies to finished goods' schedules. The purpose of this research is to explore the relative performance of four dynamic lot-sizing techniques with regard to ROI, namely the Wagner-Whitin, Incremental Part Period, Silver-Meal, and Groff techniques. Computer graphics are employed to analyze the relative ROI effectiveness.