Group Dynamics in Higher Education

Abstract

Although group work has been proven to be an effective method for enhancing active learning in the higher education, optimum planning is crucial for successful implementation. A deep understanding of teamwork dynamics and creation of inclusive environments helps groups to demonstrate their optimum performance and output. On this basis, the current research focuses on the important challenge of gender inclusiveness and required teacher interventions to encourage that. Towards this aim, three research hypotheses are developed and tested using student performance data in a series of individual, group, and hybrid assessment. Findings show the significantly different performance of female and male students in group activities. It is also found that instructor interventions to form gender-inclusive groups significantly improve group performance and output. This works contributes to the higher education literature by exploring dynamics of collaborative learning and interfaces with gender inclusiveness. Educators can utilize the findings to better design and implement team activities.

Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization

“…Holistic modeling can result in the accurate prediction of academic performance [14]. This will ensure the provision of timely support to students and improvements in learning experience/retention rates [4,6].…”