Studying Knowledge Retention through Cooperative Learning in an Operations Research Course

Studying Knowledge Retention through Cooperative Learning in an Operations Research Course Reinaldo Moraga and Regina Rahn College of Engineering and Engineering Technology Northern Illinois University DeKalb, IL 60115, USA Abstract Cooperative learning is defined as the instructional use of small groups so that students may maximize their own learning and each other s learning. The benefits of cooperative learning are well known in literature. In this paper, an experiment using cooperative learning is presented, which was conducted in the first foundational Operations Research course for the industrial and systems engineering program during the fall semester of 2006. The variable knowledge retention was used as the performance measure in order to study the success of this technique. In general, results are promising. This paper presents the methodology used, the experiments, results, conclusions and future line of research. Keywords Operations research, cooperative learning, knowledge retention, engineering education. 1. Introduction There is a clear and unmistakable need to improve teaching and learning methods in engineering education not only nationwide [1] [10-11] but also statewide as asserted by Illinois Commitments Goal 2: Higher education will join elementary and secondary education to improve teaching and learning at all levels (A Citizens Agenda for Illinois Higher Education The Illinois Commitment: Partnership, Opportunities, and Excellence; IBHE, 1999.) This not only represents a call for action but also re-activates what the scholarship of teaching in engineering education should be [16]. In a recent study that shows 2004 graduates as significantly better prepared than their counterparts from a decade ago, Lattuca et al. [9] conclude the weight of evidence indicates that engineering education in the US has changed dramatically after the implementation of the new ABET Engineering Criteria 2000. These results demonstrate that ABET accreditation philosophy based on assessments of student learning and continuous improvement principles was a milestone in the right direction. However, as pointed out by Sullivan [14], scattered approaches to reforming engineering education have not [yet] resulted in a systemic change and therefore call for action to produce substantial changes in engineering education remains far still active. An important aspect is the need to prepare engineering students to function in a rapidly changing world. Nationally, less than 55 percent of students who start engineering studies complete them. Kenney and Dossani [7] say this rate might be severely affected during the next years as outsourcing trends maintain or accelerate in response to ongoing pressure to reduce costs due to economic globalization, unless the engineering curriculum adapts to address this new reality. In this new much more globalized context, the prediction is that engineers of the future might likely take one of two directions; either they become global project managers or entrepreneurs. Consequently, Kenney and Dossani [7] argue engineering students will need an educational system that provides them with the tools to succeed. To educate engineers two decades from now, the National Academy of Engineering (NAE) suggests engineering courses should be taught in such a manner that students get engaged and their curiosity arisen. In other words approaches such as active learning and cooperative (or collaborative) learning should be incorporated in classrooms to produce learner-centered, assessment-centered and knowledge-centered learning environments. The research evidence establishes that cooperative learning promotes deep learning and enhances knowledge retention in students. Based on this premise, this article presents a first attempt to infuse the cooperative learning approach into the first course of Operations Research (OR), which is part of the undergraduate core within the Industrial Engineering (IE) curriculum at Northern Illinois University. In the following sections, a brief discussion on 1

cooperative learning is presented as well as the methodology used, the experiments, results, conclusions and future line of research. 2. Cooperative Learning Cooperative learning does not simply mean students working in groups; it goes richly beyond and on top of that. Within the cooperative tasks, individuals look for outcomes that are of benefit to themselves and to all other group members. Johnson, Johnson and Smith [5] define cooperative learning as the instructional use of small groups so that students work together to maximize their own and each other s learning (p.1-14). The disposition into groups is to provide students with an environment of social interdependence or mutual dependence rather than competition. Under this idea, the way how social interdependence is structured will determine how group members interact which in consequence affects the outcome achievements. Cooperation or positive interdependence results in more interaction as group members encourage and facilitate each other s learning. On the contrary, a negative interdependence or competition results in oppositional interaction as group members obstruct each other s learning. The absence of interdependence results in no interaction since group members are going to be more focused on individual efforts [12]. Extensive research has been done in cooperative learning at least 600 studies since 1897 [12]; most of these studies show that cooperative learning favors higher individual achievement than both competitive and individualistic approaches [13]. Just as an example, Hake [4] shows that interaction between students during class time is related with a greater percentage gain on the Force Concept Inventory (measure of students conceptual understanding of mechanics) when compared with traditional lecture courses. Johnson et al. [5] discuss three possible implementations for cooperative learning: informal cooperative learning, formal cooperative learning, and cooperative base groups. Informal cooperative learning consists of having students work together to achieve specific learning goals through temporary groups that last from a few minutes to one session period [5]. Formal cooperative learning is subject to the presence of the following five elements: (1) positive interdependence, team members must be linked to one another in such a way that they maximize their own productivity and that of all other group members; (2) individual accountability, all students in a group are held personally responsible to achieve group goals by doing their share of the work and easing the work and effort of other group members; (3) promotive (Face to Face) interaction, team members must encourage and facilitate each other s efforts to complete tasks and challenge one another s conclusions and reasoning in order to reach group goals; (4) social skills, students must be taught and motivated to develop and practice interpersonal and small group skills; and (5) group processing, team members must reflect on group member actions and assess them to decide upon direction [5]. Cooperative base groups are long-term, heterogeneous cooperative learning groups with stable membership where students primary responsibility is to provide one another with encouragement, to be accountable, and to ensure all members are academically progressing [5]. Felder and Brent [3] affirm that a growing body of research continues to confirm the effectiveness of using cooperative learning in higher education. Among the characteristics that cooperatively taught students exhibit when compared to students traditionally taught are the following: higher academic achievement, greater persistence through graduation, better high-level reasoning and critical thinking skills, deeper understanding of learned material, lower levels of anxiety and stress, more positive and supportive relationships with peers, more positive attitudes toward subject areas, and higher self-esteem [15]. Cooperative learning is not only claimed to produce deep learning, which in turn helps students to apply knowledge in other contexts, but also is claimed to promote a positive attitude toward the subject matter and thus increase knowledge retention [2] [6]. When students are successful their self esteem enhances and they tend to view the subject matter with a very positive attitude that creates a reinforcement cycle of good performance, helping to improve both the individual s and group s self esteem [8]. The research evidence establishes that cooperative learning promotes deep learning and enhances knowledge retention in students. Based on this premise, this article presents a first attempt to infuse the cooperative learning approach into the first course of Operations Research (OR), which is part of the undergraduate core within the Industrial and Systems Engineering (ISYE) curriculum at Northern Illinois University. This study is intended to answer the two following research questions: a) Does individual learning vs. cooperative learning result in differential knowledge gains as indicated by a traditional cognitive test? b) Does individual learning vs. cooperative learning result in differential knowledge retention as indicated by a final exam? 2

With respect to this research matter, cooperative learning has been a recurrent topic within the contents of the Informs Annual Teaching of Management Science Workshop during the last three years. However, no research study addressing the effects of cooperative learning on OR knowledge retention has been found in literature to date. 3. Methodology In order to examine the impact of cooperative learning versus individual learning on knowledge gain in the form of the two research questions stated above, a sample consisting of 18 students enrolled in the section of the ISYE 370 Operations Research: Deterministic Models course, which is part of the core of the ISYE program. In this course, students are first exposed to fundamental methods and applications of deterministic operations research models. The course was separated in two overall groups and students randomly assigned to one of them. Additionally, working teams were formed within each overall group. Literature recommends that each team in cooperative learning should be comprised by two or three members [5]. In this experiment, the working teams were formed out of two and three students. The experimental design will consist of two treatments: (a) individual learning and (b) cooperative learning, as presented in Table 1. After these two treatments are performed there were two posttests to collect data with which the research questions were answered. Table 1: Individual Learning vs. Cooperative Learning Course Treatment Posttest 1 Posttest 2 Group 1 Individual Learning Traditional Test Final Group 2 Cooperative Learning Traditional Test Final The actual delivery of the treatment conditions alternated across content areas and groups, as shown in Table 2. For this delivery model to work there needs to be an even number of content areas with a minimum of two. Therefore, the following four content areas were considered: I. Formulation/Graphical Method II. Formulation of Larger Problem III. Simplex Method IV. Duality Theory Group I Table 2: Order for Treatments Treatments II III IV 1 Individual Cooperative Individual Cooperative 2 Cooperative Individual Cooperative Individual Group 1 was the individual learning group for content areas I & III while Group 2 was the individual learning group for content areas II & IV. This adds to the validity of the design and enhances the fairness of the treatment conditions within the student groups. Activities assigned during each content area were worked separately by both groups and thus two rooms were needed for this purpose. For the content areas where Groups 1 and 2 became a cooperative learning group, the group was split into working teams for the effectiveness of the approach. For fairness to students, each content area was weighted approximately equally within both posttests. After the administration of the Traditional Test (Posttest 1) the distinction between the groups was dissolved with instruction 3

and assessment activities delivered to all students equally. Question 1 was addressed by comparing the Posttest 1 means under the individual and cooperative learning conditions. Question 2 was addressed with similar comparisons on the Posttest 2 means. Each content area was lectured first and then the class was divided into cooperative and individual groups. Both groups worked on the same in-class assignment during 40 minutes according to certain instructions. The cooperative learning group was required to follow the instructions and time as shown in Figure 1. Whereas the individual learning group was basically required to solve the problem in 30 minutes and then students were exposed to the solution in 10 minutes. Figure 1: Instructions for cooperative learning group 4. Results In total eight teams were formed and kept in the class throughout the semester; six teams made up of two members and other two teams of three members. As explained in the methodology section, after the experiment both groups took the midterm exam. This exam consisted of 25 multiple-choice questions to make more objective the evaluation of the diverse contents. Twelve selected questions from the midterm were again given to the students as part of the comprehensive final exam, but the format and the wording were changed. Table 3 shows the results of this experiment. Table 3: Experiment results Midterm Final N Mean StDev SE Mean Mean StDev SE Mean Individual 18 29.111 7.977 1.880 3.444 1.381 0.325 Cooperative 18 25.778 9.124 2.150 3.333 1.680 0.396 Difference 18 3.333 7.669 1.807 0.111 1.231 0.290 95% CI mean difference (-0.48069, 7.14736) (-0.501248, 0.723471) P-value 0.083 0.707 Since students within each overall group alternate between individual and cooperative learning styles for different contents as shown in Table 2, each student is tested actually based upon both styles. Therefore, a paired-t test was performed to compare the difference between individual learning versus cooperative learning. Table 3 shows the results of the 25 and 12 multiple-choice questions for the Midterm and Final examinations respectively. For instance, the values of 29.111 and 25.778 for Midterm indicate the average scores students obtained in questions for those contents where they worked under individual and cooperative learning styles respectively. In addition, Table 3 shows that the 95% confidence interval for the mean difference between both types of learning used does include zero, which suggests there is no statistical evidence to reject the null hypothesis. The large p-values in both cases (0.083 and 0.707, respectively) further suggest that the data are consistent with H 0 : µ d = 0, that is, both groups perform equally. This result implies that for the experiment conducted both learning styles produced neither differential knowledge gains nor differential knowledge retention with respect to each other, as response to the questions stated in Section 2. 5. Conclusions and Recommendations 4

Results are clearly not the ones expected according to literature and thus they should be interpreted carefully and in light of this experiment only. In practice, it was particularly difficult to isolate within one single course the real effect of using cooperative learning from individual learning, due mainly to the fact that the students cannot be treated unfairly. Secondly, a content size reduced makes difficult to treat the content properly, which could have happened in this experiment, but again a larger content size may have a negative impact on the fairness. Third, the sample size becomes an important issue in this type of study. Finally, the size of the teams also had an effect in the results. Three-member teams easily got along and worked in general better than some of the two-member teams, in which took longer to unfreeze members before starting to work steadily. However, the majority of the students reported to feel highly pleased to work and learn cooperatively in teams on their respective topics. It is interesting to note that the content related to OR modeling was reported to be hard and intimidating by those who worked on this topic individually. All students coincided on that cooperative learning should be kept as a teaching method of all OR contents for future courses. This is important because one advantage of working cooperatively in student teams as instructor is that teams were easier to supervise and interact with. Instructors can observe students working on assignments together and individually within their teams, but when students work alone it is hard for the instructor to observe the performance of all of them. In addition, it was noticed that student participation in the topics increased, most of them looked more comfortable with providing opinions, comments, and suggestions within their teams for solving problems related to their topics. The meta-cognitive technique of repeating what students are doing with each other was reported to be effective for their learning. Some of the students said they felt like their ideas were reinforced in them while repeating and explaining a solution to their partners, this is because through this mechanism students were forced to reflect what they are learning. In conclusion, although results in this experiment do not support the evidence from experiences from other areas reported in the literature with respect to retention gains, neither are they unpromising. The infusion of this cooperative learning type in the Operations Research course has clearly showed an increased level of motivation and participation in the OR contents. Therefore, a recommendation would be to continue the infusion of cooperative learning in OR topics. In the future, teams should be formed not randomly as they were in this experiment, but by also considering students learning styles. In addition, the incorporation of the learning cycle (Why? What? How? What if?) should also be stressed in the different activities of teams. Acknowledgement References 1. ASEE (American Society for Engineering Education) Engineering Deans Council and Corporate Roundtable, (1994). Engineering Education for a Changing World, American Society for Engineering Education, Washington, D.C. 2. Bligh, D.A., (1972). What's the use of lectures, Karmondsworth, England: Penguin. 3. Felder, R.M., and R. Brent, (2003). Designing and Teaching Courses to satisfy the ABET Engineering Criteria, Journal of Engineering Education, v.92 n.1, pp.7-25. 4. Hake, R., (1998). Interactive-Engagement vs. Traditional Methods: A Six-Thousand Student Survey of Mechanics Test Data for Introductory Physics Courses, American Journal of Physics, v.66 n.1, pp.64 74. 5. Johnson, D.W., R.T. Johnson, and K.A. Smith, (1998). Active Learning: Cooperation in the College Classroom, 2nd ed., Interaction Book Company, Edina, MN. 6. Johnston, C.G., R.H. James, J.N. Lye, and I.M. McDonald, (2000). An Evaluation of Collaborative Problem Solving for Learning Economics, Journal of Economic Education 31(1):13-29. 7. Kenney M., and Dossani R., (2005). Offshoring and the Future of U.S. Engineering: An Overview, The Bridge: Linking Engineering and Society, Vol. 35, No. 3, pp.3-12, Fall 2005 5

8. Kulik, J.A., C.L Kulik, (1979). College Teaching, in Peterson and Walberg (Eds.) Research in Teaching: Concepts, findings and implications, McCutcheon Publishing, Berkeley, CA. 9. Lattuca, L.R., P.T. Terenzini, J.F. Volkwein, and G.D. Peterson, (2006). The Changing Face of Engineering Education, The Bridge: Linking Engineering and Society, Vol. 36, No. 2, pp.5-13, Summer 2006. 10. NAE (National Academy of Engineering), (2004). The Engineer of 2020: Visions of Engineering in the New Century, National Academies Press, Washington, D.C. 11. NAE, (2005). Educating the Engineer of 2020: Adapting Engineering Education to the New Century, National Academies Press, Washington, D.C. 12. Smith, K.A., S.D. Sheppard, D.W. Johnson, and R.T. Johnson, (2005). Pedagogies of Engagement: Classroom-Based Practices, Journal of Engineering Education, v94 n1, pp.87-101. 13. Springer, L., M.E. Stanne, and S.S. Donovan, (1999), Effect of Small Group Learning on Undergraduates in Science, Mathematics, Engineering and Technology: A Meta-Analysis, Review of Educational Research, v.69 n.1, pp. 21 51. 14. Sullivan, J.F., (2006). A Call for K 16 Engineering Education, The Bridge: Linking Engineering and Society, Vol. 36, No. 2, pp.17-24, Summer 2006. 15. Terenzini, P.T., et al. (2001). Collaborative learning vs. lecture/discussion: Students reported learning gains. Journal of Engineering Education, v.90 n.1, pp.123 130. 16. Wankat, P.C., R.M. Felder, K.A. Smith, and F.S. Oreovicz, (2002). The Scholarship of Teaching and Learning in Engineering, In M.T. Huber and S.P. Morreale (Eds.) Disciplinary Styles in the Scholarship of Teaching and Learning: Exploring Common Ground, American Association for Higher Education and The Carnegie Foundation for the Advancement of Teaching, Washington, D.C. 6