Effect of different grouping arrangements on students’ achievement and experience in collaborative learning environment

ABSTRACT

The study aims to investigate the effect of homogenous and heterogeneous grouping on students’ achievement and experiences of learning in a collaborative environment. A collaborative learning environment has been used as a pedagogical tool for a long time now. However, there is no clarity on which grouping strategy to use. In this paper, we study the impact of grouping on students’ performances. We aim to examine how different grouping arrangements, leading to different learning environments, affect students’ academic achievement. Also, in most cases homogeneity or heterogeneity is decided on the basis of students’ ability. For group learning, students were grouped into two different settings on the basis of their learning perspectives derived from class notes and their personality types. In the present study, we used a novel algorithm based on k modes clustering. Grouping indeed improved students’ performance, particularly, the heterogeneous groups performed better than the homogenous groups. Students’ experience with learning in the two different environments indicates that they were more satisfied with homogeneous group settings.

KEYWORDS:

• Collaborative learning environments
• homogeneous grouping
• heterogeneous grouping

Acknowledgements

The study was conducted in a technical university where no institutional ethics committee oversees study with human subjects. It is ensured that no subject is disadvantaged in any way under any circumstances. Responses and analyses were gathered through unique identifiers rather than actual identities. The dataset used in the experiment is anonymous.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Kanika

Kanika is Senior Research Fellow at Netaji Subhas Institute of Technology (NSIT). She is working on developing educational tools, e-learning models and improving the quality of learning utilizing different environments.

Shampa Chakraverty

Shampa Chakraverty is a professor at the Netaji Subhas University of Technology. Her research areas include analysis of sentiment, emotion and human language, and e-learning, information retrieval and engineering pedagogy.

Pinaki Chakraborty

Pinaki Chakraborty received his BTech from Indraprastha University and his MTech and PhD from Jawaharlal Nehru University. He is an assistant professor at the Netaji Subhas University of Technology. His area of research includes systems software and educational software.

Manan Madan

Manan Madan is pursuing BTech Instrumentation and Control Engineering at the Netaji Subhas Institute of Technology. He is actively exploring the different areas of educational software, artificial intelligence, Natural Language Processing and Computer Vision.