Students e-learning readiness towards education 4.0: Instrument development and validation

Didik Hariyanto, Universitas Negeri Yogyakarta, Indonesia
Sigit Yatmono, Universitas Negeri Yogyakarta, Indonesia
Moh Khairudin, Universitas Negeri Yogyakarta, Indonesia
Thomas Köhler, Technische Universität Dresden, Germany

Abstract


One of the characteristics of Education 4.0, which is a response to the demands of Industry 4.0, is the use of adaptive and artificial intelligence technologies in online education. In relation to e-learning preparedness, many researchers have conducted studies. But in Education 4.0, the teaching and learning processes' peculiarities were not considered. Therefore, this study aims to develop and validate an instrument for assessing the e-learning readiness of students toward Education 4.0. There were 126 undergraduate students participated in this study. The respondents were asked to fill out the online-based questionnaire voluntarily. The data obtained were then statistically analyzed using the Pearson product-moment correlation test to measure the instrument's validity. The validity test showed that all items on the questionnaire are considerably valid at a significance level of 0.01. Meanwhile, the instrument reliability was measured through Cronbach's alpha score. The reliability test confirmed that six aspects out of seven of the instrument are categorized as high reliability (flexibility, learning preferences, project-based learning, data interpretation, improving curriculum, and self-directedness). One aspect (field experience) showed a moderate level of reliability. The study's findings confirmed that the questionnaire developed is valid and reliable for collecting data concerning the students' e-learning readiness toward Education 4.0.

Keywords


Education 4.0; instrument development; instrument validation; student readiness

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References


Alem, F., Plaisent, M., Zuccaro, C., & Bernard, P. (2016). Measuring e-Learning readiness concept: Scale development and validation using structural equation modeling. International Journal of E-Education, e-Business, e-Management and e-Learning, 6(4), 193–207. https://doi.org/10.17706/ijeeee.2016.6.4.193-207

Alshaher, A. A.-F. (2013). The McKinsey 7S model framework for e-learning system readiness assessment. International Journal of Advances in Engineering & Technology, 6(5), 1948. https://www.proquest.com/docview/1468932560

Aydin, C. H., & Tasci, D. (2005). Measuring readiness for e-learning: Reflections from an emerging country. Journal of Educational Technology & Society, 8(4), 244–257. https://www.jstor.org/stable/pdf/jeductechsoci.8.4.244.pdf

Brusilovsky, P. (2000). Adaptive hypermedia: From intelligent tutoring systems to web-based education. In G. Gauthier, C. Frasson, & K. VanLehn (Eds.), International Conference on Intelligent Tutoring Systems (pp. 1–7). Springer. https://doi.org/10.1007/3-540-45108-0_1

Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning (4th ed.). John Wiley & Sons.

Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Harcourt Brace Jovanovich College.

Diwan, P. (2017). Is Education 4.0 an imperative for success of 4th industrial revolution. Medium. https://pdiwan.medium.com/is-education-4-0-an-imperative-for-success-of-4th-industrial-revolution-50c31451e8a4

Durrheim, K., & Tredoux, C. (2004). Numbers, hypotheses & conclusions: A course in statistics for the social sciences. Juta and Company Ltd.

Fisk, P. (2017). Education 4.0 ... the future of learning will be dramatically different, in school and throughout life. Peterfisk. https://www.peterfisk.com/2017/01/future-education-young-everyone-taught-together/

Franta, D. (2012). SOF as a Learning Organization [Naval Postgraduate School]. https://core.ac.uk/download/pdf/36700908.pdf

Hariyanto, D., & Köhler, T. (2020). A web-based adaptive e-learning application for engineering students: An expert-based evaluation. International Journal of Engineering Pedagogy (IJEP), 10(2), 60–71. https://doi.org/10.3991/ijep.v10i2.11834

Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004

Landauer, T. K. (1997). Behavioral research methods in human-computer interaction. In M. G. Helander, T. K. Landauer, & P. V. Prabhu (Eds.), Handbook of Human-Computer Interaction (pp. 203–227). Elsevier. https://doi.org/10.1016/B978-044481862-1/50075-3

Liutu, R. (2010). Subway market research [Saimaa University Applied Sciences]. https://www.theseus.fi/bitstream/handle/10024/23519/Liutu_Riina.pdf?sequence=1&isAllowed=y

Lou, Y., & MacGregor, S. K. (2004). Enhancing project-based learning through online between-group collaboration. Educational Research and Evaluation, 10(4–6), 419–440. https://doi.org/10.1080/13803610512331383509

Nunnally, J. C. (1978). Psychometric theory. McGraw-Hill.

Odunaike, S. A., Olugbara, O. O., & Ojo, S. O. (2013). E-learning implementation critical success factors. Proceedings of the International MultiConference of Engineers and Computer Scientists, 1. https://www.iaeng.org/publication/IMECS2013/IMECS2013_pp560-565.pdf

Peters, T. J., Waterman, R. H., & Jones, I. (1983). In search of excellence: Lessons from America’s best-run companies. Administrative Science Quarterly, 28(4), 621–624. https://doi.org/10.2307/2393015

Robinson, J. P., Shaver, P. R., & Wrightsman, L. S. (1991). Criteria for scale selection and evaluation. In Measures of Personality and Social Psychological Attitudes (Vol. 1, Issue 3, pp. 1–16). Elsevier. https://doi.org/10.1016/B978-0-12-590241-0.50005-8

Rosenberg, M. J., & Foshay, R. (2002). E-learning: Strategies for delivering knowledge in the digital age. Performance Improvement, 41(5), 50–51. https://doi.org/10.1002/pfi.4140410512

Smith, P. J., Murphy, K. L., & Mahoney, S. E. (2003). Towards identifying factors underlying readiness for online learning: An exploratory study. Distance Education, 24(1), 57–67. https://doi.org/10.1080/01587910303043

Srichanyachon, N. (2010). Key components of e-learning readiness. Bangkok University Academic Review, 9(1), 55–61. https://www.bu.ac.th/knowledgecenter/epaper/jan_june2010/pdf/Page_56.pdf

Ünal, Y., Alır, G., & Soydal, İ. (2014). Students readiness for e-learning: An assessment on Hacettepe University Department of Information Management. In J. N. Gathegi, Y. Tonta, S. Kurbanoğlu, U. Al, & Z. Taşkın (Eds.), International Symposium on Information Management in a Changing World (pp. 137–147). Springer. https://doi.org/10.1007/978-3-662-44412-2_13

Williams, V., & Pennsylvania State University. (n.d.). Online readiness assessment. Pennstate.Qualtrics. Retrieved June 6, 2022, from https://pennstate.qualtrics.com/jfe/form/SV_7QCNUPsyH9f012B




DOI: https://doi.org/10.21831/jpv.v12i3.51798

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