A conceptual model for students’ satisfaction with team-based learning using partial least squares structural equation modelling in a faculty of life sciences, in the United Kingdom

Manfrin, Andrea orcid iconORCID: 0000-0003-3457-9981, Apampa, Bugewa and Parthasarathy, Prabha (2019) A conceptual model for students’ satisfaction with team-based learning using partial least squares structural equation modelling in a faculty of life sciences, in the United Kingdom. Journal of Educational Evaluation for Health Professions, 16 (36).

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Official URL: https://doi.org/10.3352/jeehp.2019.16.36

Abstract

Purpose
Students’ satisfaction is an essential element in higher education. This study aimed to identify paths and predictive power of students’ satisfaction during team-based-learning activities in the faculty of life sciences using partial least squares structural equation modelling (PLS-SEM).
Methods
In 2018-19, at the University of Sussex (UK), 180 life science students exposed to team-based learning (TBL) were invited to participate in the study. Team-Based-Learning-Student-Assessment-Instrument was used. A conceptual model was developed for testing six hypotheses. H1: What was the effect of TBL on student satisfaction? H2: What was the effect of lectures on student satisfaction? H3: What was the effect of TBL on accountability? H4: What was the effect of lectures on accountability? H5: What was the effect of accountability on student satisfaction? H6: What were the in-sample and out-of-sample predictive power of the model? The analysis was conducted using the PLS-SEM approach.
Results
Ninety-nine students participated in the study giving a 55% response rate. Confirmatory tetrad analysis suggested a reflective model. Construct reliability, validity, average extracted variance and discriminant validity were confirmed. All path coefficients were positive, and five were statistically significant (H1:β=0.587, P<0:001; H2:β=0.262, P<0.001; H3:β=0.532, P<0.001; H4:β=0.063, P=0.546; H5:β=0.200, P=0.002). The in-sample predictive power was weak for Accountability, (R2=0.303, 95% CI 0.117-0.428, p<0.001) and substantial for Student Satisfaction (R2=0.678, 95% CI 0.498-0.777, P<0.001). The out-of-sample predictive power was moderate.
Conclusions
The results have demonstrated the possibility of developing and testing a TBL conceptual model using PLS-SEM for the evaluation of path coefficients and predictive power relative to students’ satisfaction.


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