Quantitative analysis of the effectiveness of team-based learning on mathematics undergraduates

• Main Author: Amrita, Sridhar Narayanan
• Other Authors: Fedor Duzhin
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Science::Mathematics
• Online Access: http://hdl.handle.net/10356/77166
• Institution: Nanyang Technological University

Collaborative Learning is an emerging teaching strategy that uses group work as a tool for understanding and processing knowledge. Team-Based Learning, a type of Collaborative Learning strategy, achieves this goal through a structured process conceived by Larry Michaelson in the 1970s (Michaelson, Sweet & Parmalee, 2009). With TBL’s popularity increasing in the past decade, many educational researchers evaluate its effectiveness through basic statistical analysis or apply qualitative methodologies to gain an in-depth perspective on its structural merits and demerits. However, there is a lack of extensive quantitative analyses of the TBL approach as the researchers might not be familiar with other data analysis methods. Hence, this thesis aims to develop data analysis techniques to extract value from non-experimental data collected throughout TBL teaching and learning process that can also be applied by other researchers. The data used in this study is of 400 mathematics undergraduates collected as part of the teaching process of TBL of an Ordinary Differential Equations course in NTU. Probability distributions, numerical simulations and regression modelling were the diverse mathematical approaches adopted in analyzing the data. It was observed that the team scores generally ranged higher than individual scores, in line with the philosophy behind the impact of collaboration on learning. Students were proven to have improved their communication throughout the course, with communication playing a factor in the higher group. A correlation between the difficulty level of the content and high individual scores was also found, highlighting potential flaws in applying TBL at a higher-order level. From these findings, it is evident that the benefits of TBL to mathematics undergraduates can be quantitatively justified. Therefore, this study is significant for education researchers as they could apply the techniques explained to their studies as well.