A Study of Team Formation Strategies and Their Impact on Individual Student Learning Using Educational Data Mining (EDM)

Abstract

with the advent of technology, the teaching-learning methods have improved and pedagogic practices used in the classroom are helping students to learn. We have different learning methods like game-based, experiment-based, self-learning and team-based learning to improve the individual learning. It has been demonstrated by authors [4] that Team-Based Learning (TBL) helps to enhance the individual learning. Further, the authors proposed work aiming at analyzing different team formation strategies and their impact on individual student learning using Educational Data Mining (EDM). The Project Based Learning (PBL) approach was used to conduct the projects at junior and senior years of engineering. These project groups used different team formation strategies to form the teams. The student teams were formed with strategies based on natural grouping, mixed grades, gender-based and with complementary skills. The data collection was done in mini, minor and capstone project of junior and senior years of engineering for the academic year 2013-14 and 2014-15. The results obtained from the different team formation strategies were subjected to statistical analysis like T-test and Chi-square test. One-tailed T-test value 0.000E-10 significantly showed that the performance of an individual significantly increases with the team strategy followed. Chi-square test conducted showed that there is the dependency between students' performance and strategy followed with mixed grades and complementary skills with the significant value of 24.4. The result shows that individual learning depends on the team formation strategies. The analysis also showed that individual performance increased with different team formation strategies and the influencing parameters enhanced individual learning in teams. The results hold good under the given population, the project and the characteristics under consideration.