Abstract
University student engagement is a construct resembling work engagement from a psychological perspective. Student engagement is positively related to personal resources, improved performance and on-time graduation. Its socio-economic impacts concern all the stakeholders of higher education. The structure of Utrecht Work Engagement Scale consisted of three dimensions, Vigor, Dedication and Absorption, is investigated. This is the first time that student engagement was measured in Greece. Hence, the purpose of this paper was to investigate the factorial structure of the Utrecht Work Engagement Scale-Student version for measuring student engagement in a sample of 462 students from all schools of University of Patras. The factorial structure which derived by a series of statistical analyses consisted of 9 items distributed in 2 dimensions (Vigor and Dedication-Absorption). This factorial structure presents measurement invariance across gender and order of choice of the department of attendance. The Utrecht Work Engagement Scale-Student version is a brief and eligible instrument with satisfactory psychometric properties thus proposed for measuring student engagement in the Greek university context.
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Astin, A.W. (1999). Student involvement: A developmental theory for higher education. https://pdfs.semanticscholar.org/80f5/d9fcc0a3bad638816893e75b0d2be42c53d5.pdf?_ga=2.80647191.105436436.1597240173-963604176.1595932061. Accessed 21 January 2020.
AUSSE. Australasian Survey of Student Engagement. (2019). https://www.acer.org/gb/ausse/reports/australasian-university. Accessed 15 February 2010.
Ayala, J. C., & Manzano, G. (2018). Academic performance of first-year university students: The influence of resilience and engagement. Higher Education Research and Development. https://doi.org/10.1080/07294360.2018.1502258https://www.tandfonline.com/doi/abs/10.1080/07294360.2018.1502258?journalCode=cher20. Accessed 2 March 2020.
Bokhove, C., & Muijs, D. (2019). Can we reliably compare student engagement between universities? Evidence from the United Kingdom engagement survey. Oxford Review of Education, 45(3), 417–434. https://doi.org/10.1080/03054985.2018.1554530https://www.tandfonline.com/doi/abs/10.1080/03054985.2018.1554530?af=R&journalCode=core20. Accessed 19 January 2020.
Bresó, E., Schaufeli, W. B., & Salanova, M. (2011). Can a self-efficacy-based intervention decrease burnout, increase engagement, and enhance performance? A quasi-experimental study. Higher Education, 61, 339–355. https://doi.org/10.1007/s10734-010-9334-6https://link.springer.com/article/10.1007/s10734-010-9334-6. Accessed 27 February 2020.
Cadime, I., Lima, S., Marques Pinto, A., & Ribeiro, I. (2016). Measurement invariance of the Utrecht work engagement scale for students: A study across secondary school pupils and university students measurement invariance of the Utrecht work engagement scale for students: A study across secondary school pupils and university students. European Journal of Developmental Psychology, 13(2), 254–263. https://doi.org/10.1080/17405629.2016.1148595.
Çapri, B., Gündüz, B., & Akbay, S. E. (2017). Utrecht work engagement scale-student forms’ (UWES-SF) adaptation to Turkish, validity and reliability studies, and the mediator role of work engagement between academic procrastination and academic responsibility. Kuram ve Uygulamada Eğitim Bilimleri/Educational Sciences: Theory and Practice, 17(2), 411–435. https://doi.org/10.12738/estp.2017.2.0518.
Carmona-Halty, M., Salanova, M., Llorens, S., & Schaufeli, W. B. (2019a). Linking positive emotions and academic performance: The mediated role of academic psychological capital and academic engagement. Current Psychology. https://doi.org/10.1007/s12144-019-00227-8.
Carmona-Halty, M., Schaufeli, W. B., & Salanova, M. (2019b). The Utrecht work engagement scale for students (UWES-9S): Factorial validity, reliability, and measurement invariance in a Chilean sample of undergraduate university students. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.01017.
Cazan, A. M. (2016). Learning motivation, engagement and burnout among university students. Procedia – Social and Behavioral Sciences, 187(May 2015), 413–417. https://doi.org/10.1016/j.sbspro.2015.03.077.
Chambel, M. J., & Curral, L. (2005). Stress in academic life: Work characteristics as predictors of student well-being and performance. Applied Psychology: An International Review, 54(1), 135–147. https://doi.org/10.1111/j.1464-0597.2005.00200.x.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of- fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902.
Demerouti, E., Bakker, A. B., Janssen, P. P. M., & Schaufeli, W. B. (2001). Burnout and engagement at work as a function of demands and control. Scandinavian Journal of Work, Environment and Health, 27, 279–286. https://doi.org/10.5271/sjweh.615
European Commission. (2015). Dropout and completion in higher education in Europe. http://supporthere.org/sites/default/files/dropout-completion-he_en.pdf. Accessed 18 January 2020.
Felszeghy, S., Pasonen-seppänen, S., Koskela, A., Nieminen, P., Härkönen, K., Paldanius, K. M. A., et al. (2019). Using online game-based platforms to improve student performance and engagement in histology teaching. BMC Medical Education, 19(273), 1–11. https://doi.org/10.1186/s12909-019-1701-0
Fernández-Martínez, E., Andina-Díaz, E., Fernández-Peña, R., García-López, R., Fulgueiras-Carril, I., & Liébana-Presa, C. (2017). Social networks, engagement and resilience in university students. International Journal of Environmental Research and Public Health, 14, 1488. https://doi.org/10.3390/ijerph14121488.
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. (2004). School engagement: Potential of the concept: State of the evidence. Review of Educational Research, 74, 59–119. https://doi.org/10.3102/00346543074001059.
Grier-Reed, T., Appleton, J., Rodriguez, M., Ganuza, Z., & Reschly, A. L. (2012). Exploring the student engagement instrument and career perceptions with college students. Journal of Educational and Developmental Psychology, 2(2), 85–96. https://doi.org/10.5539/jedp.v2n2p85.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. https://doi.org/10.1080/10705519909540118
Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., Rosseel, Y., Miller, P., & Quick, C. (2018). semTools: Useful tools for structural equation modeling. R package version 0.5–1. https://CRAN.R-project.org/package=semTools. Accessed 17 January 2020.
Kedraka, K., & Rotidi, G. (2017). University pedagogy: A new culture is emerging in Greek higher education. International Journal of Higher Education, 6(3), 147–153. https://doi.org/10.5430/ijhe.v6n3p147
Kulikowski, K. (2017). Do we all agree on how to measure work engagement? Factorial validity of Utrecht work engagement scale as a standard measurement tool–a literature review. International Journal of Occupational Medicine and Environmental Health, 30(2), 161. https://doi.org/10.13075/ijomeh.1896.00947.
LAG-Lifelong Achievement Group. (2019). The motivation and engagement scale. https://www.lifelongachievement.com/the-motivation-and-engagement-scale-mes-i8/. Accessed 18 January 2020.
Lavidas, K., Komis, V., & Gialamas, V. (2013). Spreadsheets as cognitive tools: A study of the impact of spreadsheets on problem solving of math story problems. Education and Information Technologies, 18, 113–129. https://doi.org/10.1007/s10639-011-9174-8.
Lavidas, K., Dalapa, M., Dimitriadou, S., & Athanassopoulos, S. (2019). Four job satisfaction’s dimensions of secondary education teachers: An exploratory factor analysis based on a Greek sample. Preschool & Primary Education, 7(2), 102. https://doi.org/10.12681/ppej.20412.
Lavidas, K., Barkatsas, T., Manesis, D., & Gialamas, V. (2020). A structural equation model investigating the impact of tertiary students’ attitudes toward statistics, perceived competence at mathematics, and engagement on statistics performance. Statistics Education Research Journal, 19(2), 27–41 https://iase-web.org/documents/SERJ/SERJ19(2)_Lavidas.pdf?1593210287. Accessed 20 February 2020.
Li, C. H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior Research Methods, 48(3), 936–949. https://doi.org/10.3758/s13428-015-0619-7
Loscalzo, Y., & Giannini, M. (2018). Study engagement in Italian University students: A confirmatory factor analysis of the Utrecht work engagement scale – student version. Social Indicators Research, 142, 845–854. https://doi.org/10.1007/s11205-018-1943-y. Accessed 29 January 2020.
Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530.
Maroco, J., Maroco, A. L., Alvares, J., Bonini, D., & Fredricks, J. A. (2016). University student’s engagement: Development of the university student engagement inventory (USEI). Psicologia: Reflexão e Crítica. https://doi.org/10.1186/s41155-016-0042-8.
Medrano, L. A., Moretti, L., & Ortiz, A. (2014). Measure of academic engagement in university students Medición del engagement Académico en Estudiantes Universitarios [Measure of academic engagement in university students resumen]. Revista Iberoamericana de Diagnóstico y Evaluación – e Avaliação Psicológica., 40(1), 114–123.
Meli, K., Lavidas, K., & Koliopoulos, D. (2018). Factors that influence students in choosing physics Programmes at university level: The case of Greece. Research in Science Education, 1–17. https://doi.org/10.1007/s11165-018-9723-x.
NSSE. National Survey of Student Engagement. Customization Options. (2019). http://nsse.indiana.edu/html/customization_options.cfm. Accessed 10 February 2020.
Ouweneel, E., Le Blanc, P. M., & Schaufeli, W. B. (2011). Flourishing students: A longitudinal study on positive emotions, personal resources, and study engagement. The Journal of Positive Psychology, 6(2), 142–153. https://doi.org/10.1080/17439760.2011.558847.
Parissi, M., Komis, V., Lavidas, K., Dumouchel, G., & Karsenti, T. (2019). A pre-post study to assess the impact of an information-problem solving intervention on university students’ perceptions and self-efficacy towards search engines. International Journal of Technologies in Higher Education, 16(1), 68–87. https://doi.org/10.18162/ritpu-2019-v16n1-05.
Portalanza Chavarria, C. A., Grueso Hinestroza, M. P., & Duque Oliva, E. J. (2017). Propiedades de la Utrecht Work Engagement Scale (UWES-S 9): análisis exploratorio con estudiantes en Ecuador. INNOVAR. Revista de Ciencias Administrativas y Sociales, 27(64), 145–156. https://doi.org/10.12681/ppej.20412.
R Core Team. (2018). R: A language and environment for statistical computing. Austria, Vienna: R Foundation for Statistical Computing https://www.R-project.org/. Accessed 10 February 2019.
Raykov, T. (2001). Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints. The British Journal of Mathematical and Statistical Psychology, 54, 315–323. https://doi.org/10.1348/000711001159582.
Römer, J. (2016). The Korean Utrecht work engagement scale-student (UWES-S): A factor validation study. TPM, 23(1), 65–81. https://doi.org/10.4473/TPM23.1.5https://www.tpmap.org/the-korean-utrecht-work-engagement-scale-student-uwes-s-a-factor-validation-study/. Accessed 22 January 2020.
Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36 http://www.jstatsoft.org/v48/i02/. Accessed 21 January 2020.
Salanova, M., Llorens, S., Cifre, E., Martínez, I., & Schaufeli, W. B. (2003). Perceived collective efficacy, subjective well-being and task performance among electronic work groups: An experimental study. Small Group Research, 34, 43–73 https://journals.sagepub.com/doi/10.1177/1046496402239577. Accessed 28 February 2020.
Salanova, M., Bresó, E., & Schaufeli, W. B. (2005). Hacia un modelo espiral de las creencias de eficacia en el estudio del burnout y del engagement [Towards a spiral model of the efficacy beliefs in the study of burnout and engagement]. Ansiedady Estrés, 11(2–3), 215–231 http://www.want.uji.es/download/hacia-un-modelo-espiral-de-las-creencias-de-eficacia-en-el-estudio-del-burnout-y-del-engagement/. Accessed 2 February 2020.
Salanova, M., Schaufeli, W., Martínez, I., & Bresó, E. (2009). How obstacles and facilitators predict academic performance: The mediating role of study burnout and engagement. Anxiety, Stress & Coping, 23(1), 53–70 https://www.tandfonline.com/doi/abs/10.1080/10615800802609965. Accessed 28 February 2020.
Schaufeli, W. & Bakker, A. (2004). UWES. UTRECHT work engagement scale. Preliminary manual (version 1.1). Occupational Health Psychology Unit, Utrecht University. https://www.wilmarschaufeli.nl/publications/Schaufeli/Test%20Manuals/Test_manual_UWES_English.pdf. Accessed 10 February 2020.
Schaufeli, W. B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: Burnout and work engagement, and their relationships with efficacy beliefs. Anxiety, Stress, and Coping, 20(June), 177–196. https://doi.org/10.1080/10615800701217878.
Schaufeli, W. B., Martínez, I. M., Marques-Pinto, A., Salanova, M., & Bakker, A. B. (2002). Burnout and engagement in university students. A cross-national study. Journal of Cross-Cultural Psychology, 33(5), 464–481. https://doi.org/10.1177/0022022102033005003.
Sinval, J., Casanova, J. R., Marôco, J., & Almeida, L. S. (2018). University student engagement inventory (USEI): Psychometric properties. Current Psychology, 2, 1–3. https://doi.org/10.1007/s12144-018-0082-6.
Tayama, J., Schaufeli, W., Shimazu, A., Tanaka, M., & Takahama, A. (2018). Validation of a Japanese version of the work engagement scale for students. Japanese Psychological Research, 61(4), 262–272 https://onlinelibrary.wiley.com/doi/abs/10.1111/jpr.12229. Accessed 26 February 2020.
UKES. UK Engagement Survey. (2018). https://www.heacademy.ac.uk/institutions/surveys/uk-engagement-survey. Accessed 20 February 2020.
University of Patras. (2020). Data of quality assurance system for the academic year 2018–2019. Patras: University of Patras.
Xanthopoulou, D., Bakker, A. B., Kantas, A., & Demerouti, E. (2012). Measuring burnout and work engagement: factor structure, invariance, and latent mean differences across Greece and the Netherlands. International Journal of Business Science and Applied Management, 7(2), 41–52 https://business-and-management.org/library/2012/7_2--40-52-Xanthopoulou,Bakker,Kantas,Demerouti.pdf. Accessed 25 February 2020.
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Dimitriadou, S., Lavidas, K., Karalis, T. et al. Study Engagement in University Students: a Confirmatory Factor Analysis of the Utrecht Work Engagement Scale with Greek Students. J well-being assess 4, 291–307 (2020). https://doi.org/10.1007/s41543-021-00035-7
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DOI: https://doi.org/10.1007/s41543-021-00035-7