Understanding college students' e-loyalty to online practicum courses in hospitality programmes during COVID-19

  • Yoanita Alexandra Universitas Multimedia Nusantara
  • Septi Fahmi Choirisa Universitas Multimedia Nusantara

Abstract

This study aims to examine the students’ loyalty to an online practicum course for hospitality education during Covid-19 pandemic in Indonesia. Premised on the Technology Acceptance Model (TAM), we adopted a revised model consisting of Information System Success Model and Expectancy Confirmation Theory (ECT) to ascertain the students’ perceptions of the usefulness of the programme and their levels of satisfaction with, and e-loyalty to, the programme. This study utilized an online survey to obtain data from 309 participants. The partial least squares structural equation modelling method was employed in this study. The findings show that students’ perceptions of the usefulness of online learning were significantly influenced by information quality, system quality & system interaction which relate to satisfaction. Preliminary research provides the insight for stakeholders such as vocational institutions, teachers and practitioners of education to gain a better understanding the factors that contribute to hospitality students continued intentional use of online course.

Keywords: e-learning, practicum courses, hospitality students, pandemic Covid-19, student satisfaction, e-loyalty

References

Al-Busaidi, K. and Al-Shihi, H. (2010) ‘Instructors' acceptance of learning management systems: a theoretical framework’, Communications of The IbIMA, 1-10. https://doi.org/10.5171/2010.862128.

Alia, A. (2016) An investigation of the application of the Technology Acceptance Model (TAM) to evaluate instructors' perspectives on e-learning at Kuwait university. Unpublished PhD thesis. Dublin City University.

Amsal, A. A., Putri, S. L., Rahadi, F. and Fitri, M. E. (2020) ‘Perceived satisfaction and perceived usefulness of elearning: the role of interactive learning and social influence’, Proceedings of the 3rd International Conference on Educational Development and Quality Assurance. 506. Available at: https://www.atlantis-press.com/proceedings/iced-qa-20/125952030 (Accessed: 18 January 2021).

Anderson, J. C. and Gerbing, D. W. (1988) ‘Structural equation modelling in practice: a review’, Psychological Bulletin, 103, pp.411-423. https://doi.org/10.1037/0033-2909.103.3.411.

Bhattacherjee, A. (2001) ‘An empirical analysis of the antecedents of electronic commerce service continuance’, Decision Support Systems, 32, pp.201-214. https://doi.org/10.1016/S0167-9236(01)00111-7.

Carmines, E. G. and Zeller, R. A. (1979) Reliability and validity assessment. Beverly Hills: Sage University Paper Series on Quantitative Applications in the Social Sciences. https://dx.doi.org/10.4135/9781412985642.

Cheng, Y.-M. (2012) ‘Effects of quality antecedents on e-learning acceptance’, Internet Research, 22(3), pp. 361-390. https://doi.org/10.1108/10662241211235699.

Cheng, Y.-M. (2020) ‘Students’ satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors’, Education + Training, 62(9), pp.1037-1059. https://doi.org/10.1108/ET-10-2019-0245.

Chin, W. W. (1998) ‘Issues and opinion on structural equation modelling’, MIS Quarterly, 22(1), vii-xvi. Available at: http://www.jstor.org/stable/249674 (Accessed: 15 January 2021).

Chin, W. W. (2010) ‘How to write up and report pls analyses’, in Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds.) Handbook of Partial Least Squares. Berlin: Springer Handbooks of Computational Statistics. https://doi.org/10.1007/978-3-540-32827-8_29.

Chiu, C.-M., Hsu, M.-H., Sun, S.-Y., Lin, T.-C. and Sun, P.-C. (2005) ‘Usability, quality, value, and e-learning continuance decisions’, Computers & Education, 45, pp.399-416. https://doi.org/10.1016/j.compedu.2004.06.001.

Christou, E. and Chatzigeorgiou, C. (2019) ‘Experiential learning through industrial placement in hospitality education: the meat in the sandwich’, Journal of Contemporary Education Theory and Research, 3(2), pp.34-41. https://doi.org/10.5281/zenodo.3635961.

Davis, F. D. (1989) ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS Quarterly, 13(3), pp.319–340. https://doi.org/10.2307/249008.

Delone, W. H. and McLean, E. R. (2003). ‘The DeLone and McLean model of information systems success: a ten-year update’, Journal of Management Information Systems, 19(4), pp.9-30. https://doi.org/10.1080/07421222.2003.11045748.

Eggert, A. and Ulaga, W. (2002) ‘Customer perceived value: a substitute for satisfaction in business markets?’ Journal of Business and Industrial marketing, 17(2/3), pp.107-118. https://doi.org/10.1108/08858620210419754.

Fathema, N., Shannon, D. M. and Ross, M. (2015) ‘Expanding the Technology Acceptance Model (TAM) to examine faculty use of Learning Management Systems (LMSs) in higher education institutions’, Journal of Online Learning and Teaching, 11, pp.210-233.

Ferguson, R. (2012) ‘Learning analytics: drivers, developments and challenges’, International Journal of Technology Enhanced Learning, 4(5/6), pp.304–317. https://doi.org/10.1504/IJTEL.2012.051816.

Fornell, C. and Larcker, D. F. (1981) ‘Evaluating structural equation models with unobservable variables and measurement error’, Journal of Marketing Research, 18, pp.39-50. https://doi.org/10.1177/002224378101800104.

García-Aracil, A. (2009) ‘European graduates’ level of satisfaction with higher education’, Higher Education, 57(1), pp.1-21. Available at: http://www.jstor.org/stable/40269103 (Accessed: 20 January 2021).

Garg, S. and Sharma, S. (2020) ‘User satisfaction and continuance intention for using e-training: a structural equation model’, Vision: The Journal of Business Perspective 24(4), pp.441-451. https://doi.org/10.1177/0972262920926827.

Gefen, D. and Straub, D. (2005) ‘A practical guide to factorial validity using plsgraph: tutorial and annotated example’, Communications of the Association for Information Systems, 16, pp.91-109. https://doi.org/10.17705/1CAIS.01605.

Gefen, D., Straub, D. and Boudreau, M.-C. (2000) ‘Structural equation modeling and regression: guidelines for research practice’, Communications of the Association for Information Systems, 7(7), pp.1-78. https://doi.org/10.17705/1CAIS.00407.

Ghazal, S., AL-Samarraie, H. and Aldowah, H. (2018) ‘“I am Still learning”: modeling LMS critical success factors for promoting students’ experience and satisfaction in a blended learning environment’, IEEE Access, (6), pp.77179-77201. https://doi.org/10.1109/ACCESS.2018.2879677.

Giatman, M., Siswati, S. and Basri, I. Y. (2020) ‘Online learning quality control in the pandemic Covid-19 Era in Indonesia’, Journal of Nonformal Education, 6(2). https://doi.org/10.15294/jne.v6i2.25594.

Hair Jr, J. H., Hult, G. T., Ringle, C. M. and Sarstedt, M. (2016) A primer on partial least squares structural equation modeling (PLS-SEM). London: Sage Publications.

Hennig-Thurau, T., Langer, M. F. and Hansen, U. (2001) ‘Modeling and managing student loyalty: an approach based on the concept of relationship quality’, Journal of Service Research, 3(4), pp.331-344. https://doi.org/10.1177/109467050134006.

Huh, J. and Uysal, M. (2004) ‘Satisfaction with cultural/heritage sites’, Journal of Quality Assurance in Hospitality & Tourism, 4(3-4), pp.177-194. https://doi.org/10.1300/J162v04n03_12.

Jaber, O. A. (2016) An examination of variables influencing the acceptance and usage of e-learning systems in jordanian higher education institutions. Unpublished PhD thesis. Cardiff Metropolitan University.

Jimenez, I. C., García, L. C., Violante, M. G. and Vezzetti, E. (2020) ‘Commonly used external TAM variables in virtual reality, e-learning and agriculture applications: a literature review using QFD as organizing framework’, Preprints 2020. https://doi.org/10.20944/preprints202010.0023.v1.

Junjie, Z. (2017). ‘Exploring the factors affecting learners' continuance intention of MOOCs for online collaborative learning: an extended ECM perspective’, Australasian Journal of Educational Technology, 33(5), pp.123-135. https://doi.org/10.14742/ajet.2914.

Kamis, A., Saibon, R. A., Yunus, F. N., Rahim, M. B., Herrera, L. M. and Montenegro, P. Y. (2021) ‘The SmartPLS analyzes approach in validity and reliability of graduate marketability instrument’, Turkish Journal of Computer and Mathematics Education, 12(3), pp.829-841. https://doi.org/10.17762/turcomat.v12i3.791.

Keaveney, S. and Young, C. (1997) ‘The student satisfaction and retention model (SSRM)’, Working Paper, University of Colorado at Denver.

Khalifa, M. and Liu, V. (2002) ‘Satisfaction with internet-based services: the role of expectations and desires’, International Journal of Electronic Commerce, 7(2), pp.31-49. https://doi.org/10.1080/10864415.2002.11044267.

Lee, B.-C., Yoon, J.-O., and Lee, I. (2009) ‘Learners’ acceptance of e-learning in South Korea: theories and results’, Computers & Education, 53(4), pp.1320-1329. https://doi.org/10.1016/j.compedu.2009.06.014.

Mahmodi, M. (2017) ‘The analysis of the factors affecting the acceptance of e-learning in higher education’, Interdisciplinary Journal of Virtual Learning in Medical Sciences, 8(1). https://doi.org/10.5812/IJVLMS.11158.

Miyazoe, T. and Anderson, T. (2010) ‘Empirical research on learners' perceptions: interaction equivalency theorem in blended learning’, The European Journal of Open Distance and E-Learning. Available at: https://files.eric.ed.gov/fulltext/EJ911753.pdf (Accessed: 8 January 2021).

Mtebe, J. S. and Raisamo, R. (2014) ‘A model for assessing Learning Management System success in higher education in Sub‐Saharan countries’, The Electronic Journal of Information Systems in Developing Countries, 61(7), pp.1-17. https://doi.org/10.1002/j.1681-4835.2014.tb00436.x.

Nunnally, J. and Bernstein, I. (1994) Psychometric Theory. 3rd edn. New York: McGraw-Hill.

Oliver, R. L. (1980) ‘A cognitive model of the antecedents and consequences of satisfaction decisions’, Journal of Marketing Research, 17(4), pp.460-469. https://doi.org/10.1177/002224378001700405.

Orr, D., Weller, M., and Farrow, R. (2018) ‘Models for online, open, flexible and technology enhanced higher education across the globe – a comparative analysis’. Oslo, Norway: International Council for Open and Distance Education (ICDE). Available at: https://oofat.oerhub.net/OOFAT/. (Accessed: 5 January 2021)

Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T. and Pham, H. T. (2019) ‘Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam’, International Journal of Educational Technology in Higher Education, 16. https://doi.org/10.1186/s41239-019-0136-3.

Rajabalee, Y. B. and Santally, M. I. (2020) ‘Learner satisfaction, engagement and performances in an online module: implications for institutional e-learning policy’, Education and Information Technologies, 26, pp.2623-2656. https://doi.org/10.1007/s10639-020-10375-1.

Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L. and Koole, M. (2020) ‘Online university teaching during and after the Covid-19 crisis: refocusing teacher presence and learning activity’, Postdigital Science and Education, 2, pp.923-945. https://doi.org/10.1007/s42438-020-00155-y.

Rizkalla, N. and Setiadi, D. D. (2020) ‘Appraising the influence of theory of consumption values on environmentally-friendly product purchase intention in Indonesia’. Management & Marketing, XVII, pp.7-25. Available at: https://www.mnmk.ro/documents/2020_1/1-7-1-20.pdf (Accessed: 18 January 2021)

Rizun, M. and Strzelecki, A. (2020) ‘Students’ acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland’, Environmental Research and Public Health, 17(18), p.6468. https://doi.org/10.3390/ijerph17186468.

Robinson, R. N., Breakey, N. and Ruhanen, L. (2015) ‘Tourism and Hospitality internships: influences on student career aspirations’, Current Issues in Tourism, 19(6), pp.513-527. https://doi.org/10.1080/13683500.2015.1020772.

Roca, J. C., Chiu, C.-M. and Martínez, F. J. (2006) ‘Understanding e-learning continuance intention: an extension of the technology acceptance model’, International Journal of Human-Computer Studies, 64(8), pp.683-696. https://doi.org/10.1016/j.ijhcs.2006.01.003.

Rodríguez-Ardura, I. and Meseguer-Artola, A. (2016) ‘E-learning continuance: the impact of interactivity and the mediating role of imagery, presence and flow, Information and Management, 53(4), pp.504-516. https://doi.org/10.1016/j.im.2015.11.005.

Roldán, J. and Sánchez-Franco, M. (2012) ‘Variance-based structural equation modeling: guidelines for using partial least squares in information systems research’, in M. Mora, O. Gelman, A, Steenkamp, and M. Raisinghani (eds.), Research Methodologies, Innovations and Philosophies, in Software Systems Engineering and Information Systems, pp.193-221. https://doi.org/10.4018/978-1-4666-0179-6.ch010.

Salloum, S. A., Alhamad, A. M., Al-emran, M., Monem, A. A. and Shaalan, K. (2019). ‘Exploring students’ acceptance of e-learning through the development of a comprehensive Technology Acceptance Model’. IEEE Access, 7, pp.128445-128462. https://doi.org/10.1109/ACCESS.2019.2939467.

Song, S. M. (2010) E-learning: Investigating students' acceptance of online learning in hospitality programs. Graduate Theses and Dissertations, Iowa State University.

Song, Y. and Kong, S.-C. (2017) ‘Investigating students’ acceptance of a statistical learning platform using Technology Acceptance Model’, Journal of Educational Computing Research, 55(6). https://doi.org/10.1177/0735633116688320.

Su, B., Bonk, C. J., Magjuka, R. J., Liu, X. and Lee, S.-h. (2005) ‘The importance of interaction in web-based education: a program-level case study of online MBA courses’, Journal of Interactive Online Learning, 4 pp.1-19. Available at: https://www.ncolr.org/jiol/issues/pdf/4.1.1.pdf (Accessed: 4 January 2021).

Urbach, N. and Ahlemann, F. (2010) ‘Structural equation modelling in information systems research using partial least squares’, Journal of Information Technology Theory and Application, 11(2), pp.5-40. Available at: https://aisel.aisnet.org/jitta/vol11/iss2/2 (Accessed: 4 January 2021).

Vinzi, V. E., Trinchera, L., and Amato, S. (2010) PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. Berlin: Springer Handbooks of Computational Statistics.

Wang, Y.-S., Wang, H.-Y. and Shee, D. Y. (2007) ‘Measuring e-learning systems success in an organizational context: scale development and validation’, Computers in Human Behavior, 23, pp.1792-1808. https://doi.org/10.1016/j.chb.2005.10.006.

Williams, L. J., Vandenberg, R. J. and Edwards, J. R. (2009) ‘Structural equation modeling in management research: a guide for improved analysis’, The Academy of Management Annals, 3(1), pp.543–604. https://doi.org/10.1080/19416520903065683.

Published
2021-09-28
How to Cite
Alexandra, Y. and Choirisa, S. F. (2021) “Understanding college students’ e-loyalty to online practicum courses in hospitality programmes during COVID-19 ”, Journal of Learning Development in Higher Education. Plymouth, UK, (21). doi: 10.47408/jldhe.vi21.627.
Section
Papers