Measuring the effectiveness of PBL through shape parameters and classification

Abstract

PurposeThis paper utilizes data mining to study the effect of Problem Based Learning (PBL), an innovative pedagogical approach that has been implemented in undergraduate education at a private university in India for teaching Statistics and Operations Research (OR) to techno-management students.Design/methodology/approachThe study follows the assumptions of an in-situ experiment. It employs BBA (IT) and BCA student(s) as a subject and their end of semester GPA as a performance indicator. The pedagogical approach to this study is integrating PBL with classroom teaching. The paper uses a combination of statistics and data mining to analyze the impact of PBL and establish research conclusions.FindingsThe study concludes that the introduction of PBL positively results in an improved GPA for students with a math background. PBL is more effective for BBA (IT) male students. Female students seem to be performing equally well irrespective of the inclusion of PBL. Pattern analysis of shape parameters evidences the impact of PBL, and the results are established through the decision tree and test of proportions.Research limitations/implicationsThe study is limited to students from a single institute.Practical implicationsThis Pattern analysis, as applied in this paper, can be scaled to evaluate the impact of any innovative pedagogical approach agnostic of the field of study. Facilitators can use the process defined in the paper to implement PBL for teaching Statistics and Operations research. Shape parameters of the batch in the previous semester can be utilized by facilitators to plan remedial action for the next semester by classifying students as desirable/non-desirable. Techno-management institutes can alleviate the dread and fear of mathematical subjects by integrating PBL with classroom teaching.Originality/valueThe study utilizes an innovative analytical approach of combining shape parameters with classification. It further provides uniqueness in arriving at a classification of batch performance as desirable/non-desirable and utilizes data mining to emphasize a delineating impact of PBL across both critical parameters of the batch and the student. The study also defines a framework for the implementation of PBL for a techno-management program in Statistics and Operations Research.