Main Article Content
Abstract
Online and blended learning have increased drastically during the pandemic, and their popularity has persisted as we emerge from this global crisis. This study aims to adapt and validate the Online Learning Readiness Scale (OLRS) to assess high school students. Secondary school students were recruited (n = 296) for the study. The OLRS scale included five components: Technology Readiness, Learner Control, Online Communication Self-efficacy, Self-directed Learning and Motivation for Learning. Results supported the OLRS scale in terms of reliability and internal construct validity in context of the study by confirmatory factor analysis and Rasch measurement with partial credit analysis. The differential item functioning analysis revealed no bias issues regarding gender, confirming the measurement invariance statistics achieved. The study also found that the majority of students (73.7%) engaged in online learning solely through their mobile phone. ICT familiarity, i.e., interacting with friends regularly, browsing online learning materials, and watching educational videos on YouTube, had a positive association with students’ readiness for online learning. Students’ access to social networks, online forums and online music did not have a significant effect on their readiness for online learning. The scale demonstrated the capacity to function as an assessment instrument for evaluating readiness for online learning in the context of secondary education. Educational implications were considered, including key requirements of supporting technology and pedagogical practice in online and blended learning environments.
Keywords
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The author declares that the submitted to Journal of e-Learning and Knowledge Society (Je-LKS) is original and that is has neither been published previously nor is currently being considered for publication elsewhere.
The author agrees that SIe-L (Italian Society of e-Learning) has the right to publish the material sent for inclusion in the journal Je-LKS.
The author agree that articles may be published in digital format (on the Internet or on any digital support and media) and in printed format, including future re-editions, in any language and in any license including proprietary licenses, creative commons license or open access license. SIe-L may also use parts of the work to advertise and promote the publication.
The author declares s/he has all the necessary rights to authorize the editor and SIe-L to publish the work.
The author assures that the publication of the work in no way infringes the rights of third parties, nor violates any penal norms and absolves SIe-L from all damages and costs which may result from publication.
The author declares further s/he has received written permission without limits of time, territory, or language from the rights holders for the free use of all images and parts of works still covered by copyright, without any cost or expenses to SIe-L.
For all the information please check the Ethical Code of Je-LKS, available at http://www.je-lks.org/index.php/ethical-code
References
- Adams, R., & Wu, M. (2010). Modelling a polytomously scored items with the rating scale and partial credit models. ConQuest
- Adedoyin, O. B., & Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, No Pagination Specified-No Pagination Specified. https://doi.org/10.1080/10494820.2020.1813180
- Al-araibi, A. A. M., Naz’ri bin Mahrin, M., Yusoff, R. C. M., & Chuprat, S. B. (2019). A model for technological aspect of e-learning readiness in higher education. Educ Inf Technol, 24(2), 1395-1431. https://doi.org/10.1007/s10639-018-9837-9
- Alqabbani, S., Almuwais, A., Benajiba, N., & Almoayad, F. (2020). Readiness towards emergency shifting to remote learning during COVID-19 pandemic among university instructors. E-Learning and Digital Media, 18, 460 - 479.
- Alqurashi, E. (2016). Self-Efficacy In Online Learning Environments: A Literature Review. Contemporary Issues in Education Research, 9, 45-52. https://doi.org/10.19030/cier.v9i1.9549
- Angeles, L. P. (2002). Evaluating Cutoff Criteria of Model Fit Indices for Latent Variable Models with Binary and Continuous Outcomes.
- Arthur-Nyarko, E., Agyei, D. D., & Armah, J. K. (2020). Digitizing distance learning materials: Measuring students’ readiness and intended challenges. Educ Inf Technol, 25(4), 2987-3002. https://doi.org/10.1007/s10639-019-10060-y
- Code, J. (2020). Agency for Learning: Intention, Motivation, Self-Efficacy and Self-Regulation. Frontiers in Education, 5. https://doi.org/10.3389/feduc.2020.00019
- Creighton, T. B. (2018). Digital Natives, Digital Immigrants, Digital Learners: An International Empirical Integrative Review of the Literature.
- Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz‐Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29-47. https://doi.org/10.1080/01587919.2011.565496
- Eom, S. (2022). The effects of the use of mobile devices on the E-learning process and perceived learning outcomes in university online education. E-Learning and Digital Media, 20(1), 80-101. https://doi.org/10.1177/20427530221107775
- Farid, A. (2014). Student online readiness assessment tools: A systematic review approach. Electronic Journal of e-Learning, 12, 375-382.
- Geng, S., Law, K., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International journal of educational technology in higher education, 16. https://doi.org/10.1186/s41239-019-0147-0
- Gliner, J., Morgan, G., & Leech, N. (2016). Research Methods in Applied Settings: An Integrated Approach to Design and Analysis. Routledge.
- Hu, L.-t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. https://doi.org/10.1080/10705519909540118
- 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
- Hunt, I., Power, J., Young, K., & Ryan, A. (2022). Optimising industry learners’ online experiences – lessons for a post-pandemic world. European Journal of Engineering Education, 48(2), 358–373. https://doi.org/10.1080/03043797.2022.2112553
- Joosten, T., & Cusatis, R. (2020). Online Learning Readiness. American Journal of Distance Education, 34(3), 180-193. https://doi.org/10.1080/08923647.2020.1726167
- Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23, 1-13.
- Kim, B., & Park, M. J. (2018). Effect of personal factors to use ICTs on e-learning adoption: comparison between learner and instructor in developing countries. Information Technology for Development, 24(4), 706-732. https://doi.org/10.1080/02681102.2017.1312244
- Lin, J.-S. C., & Chang, H.-C. (2011). The role of technology readiness in self‐service technology acceptance. Managing Service Quality, 21, 424-444.
- Madadi, Y., Iravani, H., & Nooghabi, S. N. (2011). Factors effective on Familiarity and Usage of Information and Communication Technology (ICT) University College of Agriculture and Natural Resources, University of Tehran, Iran. Procedia - Social and Behavioral Sciences, 15, 3625-3632. https://doi.org/10.1016/j.sbspro.2011.04.346
- Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Educ Inf Technol (Dordr), 26(6), 6629-6649. https://doi.org/10.1007/s10639-021-10465-8
- McCrum-Gardner, E. (2010). Sample size and power calculations made simple. International Journal of Therapy and Rehabilitation, 17, 10-14. https://doi.org/10.12968/ijtr.2010.17.1.45988
- Muthén, B., & Muthén, L. (2017). Mplus. In Handbook of item response theory (pp. 507-518). Chapman and Hall.
- Nasir Ansari, J., & Khan, N. (2020). Exploring the role of social media in collaborative learning the new domain of learning. Smart Learning Environments, 7. https://doi.org/10.1186/s40561-020-00118-7
- OECD. (2014). PISA 2015 ICT Familiarity Questionnaire. OECD Publishing. http://www.oecd.org/pisa/data/CY6_QST_MS_ICQ_Final.pdf
- Peechapol, C., Na-Songkhla, J., Sujiva, S., & Luangsodsai, A. (2018). Paper— An Exploration of Factors Influencing Self-Efficacy in Online Learning : A Systematic Review An Exploration of Factors Influencing Self-Efficacy in Online Learning : A Systematic Review.
- Perifanou, M. A., Economides, A. A., & Tzafilkou, K. (2022). Greek teachers’ difficulties & opportunities in emergency distance teaching. E-Learning and Digital Media, 19, 361 - 379.
- Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. Higher Education Research & Development, 26(2), 217–234. https://doi.org/10.1080/07294360701310821
- Power, J. R. (2021). Enhancing engineering education through the integration of Open Science principles: A strategic approach to systematic reviews. Journal of Engineering Education, 110(3), 509–514. https://doi.org/10.1002/jee.20413
- Power, J., Conway, P., Gallchóir, C. Ó., Young, A.-M., & Hayes, M. (2022). Illusions of online readiness: the counter-intuitive impact of rapid immersion in digital learning due to COVID-19. Irish Educational Studies, 1-18. https://doi.org/10.1080/03323315.2022.2061565
- Ramazanoglu, M., GÜRel, S., & Çetin, A. (2022). The development of an online learning readiness scale for high school students. International Journal of Assessment Tools in Education, 9, 126-145. https://doi.org/10.21449/ijate.1125823
- Redmond, P., Heffernan, A., Abawi, L., Brown, A. V., & Henderson, R. (2018). An Online Engagement Framework for Higher Education.
- Revelle, W. (2019). psych: Procedures for Psychological, Psychometric, and Personality Research. R Package Version 1.0–95. Northwestern University.
- Reychav, I., Ndicu, M., & Wu, D. (2016). Leveraging social networks in the adoption of mobile technologies for collaboration. Computers in Human Behavior, 58, 443-453. https://doi.org/10.1016/j.chb.2016.01.011
- Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066X.55.1.68
- Scheiter, K., & Gerjets, P. (2007). Learner Control in Hypermedia Environments. Educational Psychology Review, 19, 285-307. https://doi.org/10.1007/s10648-007-9046-3
- Sharadgah, T. A., & Sa’di, R. A. (2021). Priorities for reorienting traditional institutions of higher education toward online teaching and learning: Thinking beyond the COVID-19 experience. E-Learning and Digital Media, 19(2), 209-224. https://doi.org/10.1177/20427530211038834
- Shirahada, K., Ho, B., & Alan, W. (2019). Online public services usage and the elderly: Assessing determinants of technology readiness in Japan and the UK. Technology in Society, 58. https://doi.org/10.1016/j.techsoc.2019.02.001
- Singh, V., & Thurman, A. (2019). How Many Ways Can We Define Online Learning? A Systematic Literature Review of Definitions of Online Learning (1988-2018). American Journal of Distance Education, 33(4), 289-306. https://doi.org/10.1080/08923647.2019.1663082
- 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
- Taber, K. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48, 1-24. https://doi.org/10.1007/s11165-016-9602-2
- Tang, Y. M., Chen, P. C., Law, K. M. Y., Wu, C. H., Lau, Y.-y., Guan, J., . . . Ho, G. T. S. (2021). Comparative analysis of Student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector. Computers & Education, 168, 104211. https://doi.org/10.1016/j.compedu.2021.104211
- Turgut, Y. E., & Aslan, A. (2021). Factors affecting ICT integration in TURKISH education: a systematic review. Educ Inf Technol, 26(4), 4069-4092. https://doi.org/10.1007/s10639-021-10441-2
- Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag New York.
- Wright, S., Park, Y. S., & Saadé, A. (2022). Insights from a Catholic school’s transition to distance learning during Covid-19. Open Learning: The Journal of Open, Distance and e-Learning, 1-15. https://doi.org/10.1080/02680513.2022.2152667
- Yalley, A. A. (2022). Student readiness for e-learning co-production in developing countries higher education institutions. Educ Inf Technol. https://doi.org/10.1007/s10639-022-11134-0