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
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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
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
참고문헌 (15)
- Jörg Henseler, "Using PLS path modeling in new technology research: updated guidelines", Industrial Management & Data Systems, 116(1), pp.2~20 (2016), Emerald[DOI]
- Joseph F. Hair, "Partial Least Squares: The Better Approach to Structural Equation Modeling?", Long Range Planning, 45(5-6), pp.312~319 (2012), Elsevier BV[DOI]
- Gvidas Urbonas, "Pharmacists‘ Job Satisfaction and Its Effect on Dispensing Precaution Taken at Community Pharmacies", Sveikatos mokslai, 25(3), pp.17~21 (2015), Association of Lithuanian Serials[DOI]
- Mohsen Ali Murshid, "Influence of the expertise, collaborative efforts and trustworthiness of pharmacists on the prescribing decisions of physicians", Journal of Pharmacy Practice and Research, 49(2), pp.150~161 (2019), Wiley[DOI]
- Leanne Marie Nation, "The applicability of a validated team-based learning student assessment instrument to assess United Kingdom pharmacy students’ attitude toward team-based learning", Journal of Educational Evaluation for Health Professions, 13, pp.30~ (2016), Korea Health Personnel Licensing Examination Institute[DOI]
- Prabha Parthasarathy, "Perceptions of team-based learning using the Team-Based Learning Student Assessment Instrument: an exploratory analysis amongst pharmacy and biomedical students in the United Kingdom", Journal of Educational Evaluation for Health Professions, 16, pp.1~10 (2019), 한국보건의료인국가시험원[DOI]
- Mennenga HA, "Development and psychometric testing of the Team-Based Learning Student Assessment Instrument", Nurse Educ, 37, pp.168~172 (2012)[DOI]
- Sarstedt M, "Handbook of Market Research", pp.1~40 (2017), Springer
- Franz Faul, "G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences", Behavior Research Methods, 39(2), pp.175~191 (2007), Springer Science and Business Media LLC[DOI]
- Marko Sarstedt, "Estimation issues with PLS and CBSEM: Where the bias lies!", Journal of Business Research, 69(10), pp.3998~4010 (2016), Elsevier BV[DOI]
- Joseph F. Hair, "When to use and how to report the results of PLS-SEM", European Business Review, 31(1), pp.2~24 (2019), Emerald[DOI]
- Cheong KC, "Assessment for learning within and beyond the classroom", pp.409~416 (2016), Springer
- Pelletier C, "Connecting student engagement to student satisfaction: a case study at East Carolina University", J Assess Inst Eff, 6, pp.123~141 (2017)
- Galit Shmueli, "The elephant in the room: Predictive performance of PLS models", Journal of Business Research, 69(10), pp.4552~4564 (2016), Elsevier BV[DOI]
- Joseph A. Rathner, "The use of team-based, guided inquiry learning to overcome educational disadvantages in learning human physiology: a structural equation model", Advances in Physiology Education, 38(3), pp.221~228 (2014), American Physiological Society[DOI]