J Educ Eval Health Prof.  2019;16:36. 10.3352/jeehp.2019.16.36.

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 A
• Apampa B
• Parthasarathy P

• KMID: 2502163
• DOI: http://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 (TBL) activities in the faculty of life sciences using partial least squares structural equation modelling (PLS-SEM).
Methods
In 2018–2019, at the University of Sussex (Falmer, UK), 180 life science students exposed to 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 5 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% confidence interval [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.
Conclusion
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.

Keyword

Least-squares analysis; Personal satisfaction; Problem-based learning, Students; United Kingdom

Figure

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  Fig. 1. Conceptual model. The arrows are connecting the circles, and the direction of the arrows represent the hypothesis that we were going to test. TBL, team-based learning.

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  Fig. 2. Path model (reflective). The values inside the circles represent the coefficient of determination (R2). The values overlapping the arrows pointing towards the rectangles represent the outer loading coefficients. The values overlapping the arrows between the circles (constructs) represent the path coefficients (standardised beta=beta coefficients).

Reference

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