ISSN: 2222-6990
Open access
Online distance learning is becoming a standard delivery method in educational institutions since the spread of the Covid-19 pandemic in 2019. Public and private universities in Malaysia are no exception to facing various problems in online teaching and learning using the Open Distance learning (ODL) method. After nearly one and half years of performing an ODL teaching and learning method, students in public and private institutions of higher learning are beginning to show a trend of emotional decline. According to a scientific brief released by the WHO, the global prevalence of anxiety and depression increased by a massive 25% in the first year of the COVID-19 pandemic. Thus, this study is significant to identify the students' emotions along the ODL to surpass the issues. In addition, the measurement of emotional stability on the quality of online student learning ability is still growing. Therefore, the instrument to evaluate the research variables is crucial to ensure the quality of the output. Thus, this paper aims to assess the validity and reliability of the instrument for emotional stability on the quality of online student learning ability. This study applied a quantitative approach by using a random distribution of Google Forms questionnaires. The questionnaire was distributed among academicians in universities to re-redistribute among their students to participate in this research. The survey involved 41 Students as respondents with various backgrounds in public universities. The data was analyzed by using SmartPLS 3 for the measurement model to achieve the aim of the research. The findings show the three variables to measure the emotional condition of online student learning ability, namely learning aids, learning environment, and lecturer, are valid and confirmed to measure student emotional stability. This study found that a latent variable emotional condition should have its items to measure the relationship between variables effectively. Thus, the restructuring of items for each latent variable will be reviewed and rearranged to ensure that the number of items measuring each construct is satisfactory in future research.
Alshurideh, M., Salloum, S. A., Al Kurdi, B., Monem, A. A., & Shaalan, K. (2019). Understanding the quality determinants that influence the intention to use the mobile learning platforms: A practical study. International Journal of Interactive Mobile Technologies, 13(11), 157–183. https://doi.org/10.3991/ijim.v13i11.10300
Alphonse, A., Orellana, A., & Kanzki-Veloso, E. (2019). How online students describe their physical learning environment. Quarterly Review of Distance Education, 20(2), 29-54.
Armstrong-Mensah, E., Ramsey-White, K., Yankey, B., & Self-Brown, S. (2020). COVID-19 and Distance Learning: Effects on Georgia State University School of Public Health Students. Frontiers in Public Health, 8. doi:10.3389/fpubh.2020.576227
Botros, S. (2020). Online learning distractions at home.
Crossman, Ashley. (2020). Pilot Study in Research. ThoughtCo.,
https://www.thoughtco.com/pilot-study-3026449
Gefen, D., and Straub, D. W. (2000) "The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption," J. Assoc. Inf. Syst.1(1) p. 8.
Fakinlede, C. O., Yusuf, M. O., Adegbija, V. M., and Oputa, G. O. (2014). Online learning in higher education: Faculty readiness in Nigerian universities. Malaysian Journal of Distance Education, 16(2), pp.109-123.
Fornell, C., & Larcker, D. F. (1981). Fornell, C. and Larcker, D.F. (1981), "Evaluating structural equation models with unobservable variables and.pdf. Journal of Marketing Research, XVIII(February), 39–50.
Guijosa, C. (2019). Distractions: an obstacle to online education. Institute for the Future Education. International Bureau of Education (IBE). (2022). General Education System Quality Analysis/Diagnosis Framework (GEQAF). Switzerland: IBE-UNESCO.
Hertzog, M. A. (2008). Considerations in determining sample size for pilot studies. Research in Nursing & Health, 31(2), 180–191.
Hosny, S., Ghaly, M., AlSheikh, M. H., Shehata, M. H., Salem, A. H., and Atwa, H. (2021). Developing, Validating, and Implementing a Tool for Measuring the Readiness of Medical Teachers for Online Teaching Post-COVID-19: A Multicenter Study. Advances in Medical Education and Practice, 12, p.755.
ILO. (2020) ILO Sectorial Brief: Covid 19 and Education Sctor, June 2020. https://www.ilo.org/wcmsp5/groups/public/---ed_dialogue/---sector/documents/briefingnote/wcms_742025.pdf
Junus, K., Santoso, H. B., Putra, P. O. H., Gandhi, A., and Siswantining, T. (2021). Lecturer readiness for online classes during the pandemic: A survey research. Education sciences, 11(3), p.139.
Kabirikopaei, A., Lau, J., Nord, J., & Bovaird, J. (2021). Identifying the K-12 classrooms' indoor air quality factors that affect student academic performance. Science of the Total Environment, 786. doi:org/10.1016/j.scitotenv.2021.147498
Kyei-Blankson, L., Blankson, J., & Ntuli, E. (2021). Supporting Students Through Online Learning. In K. Carlson (Ed.), Handbook of Research on Inequities in Online Education During Global Crises: IGI Global.
Lasi, M. bin A. (2021). Online Distance Learning Perception and Readiness During Covid-19 Outbreak: A Research Review. International Journal of Academic Research in Progressive Education and Development, 10(1), pp.63–73.
Li, C., & Lalani, F. (2020). The COVID-19 pandemic has changed education forever. This is how. Future of Media, Entertainment and Sport.
Majlis Keselamatan Negara. (2020). KENYATAAN MEDIA MAJLIS KESELAMATAN NEGARA, JABATAN PERDANA MENTERI 18 MAC 2020. MKN https://www.mkn.gov.my/web/wp-content/uploads/sites/3/2020/03/PERGERAKAN-KAWALAN-COVID19-amended-18032020-UPDATED-12.12AM.pdf
Martin, F., Budhrani, K., and Wang, C. (2019). Examining faculty perception of their readiness to teach online. Online Learning, 23(3), pp.97-119.
Mil, I. W. V., Briere, B., Jeong, C.-H., Larsen, O. P., Iversen, A., & Pind, F. (2018). Noise measurements during focus-based classroom activities as an indication of student's learning with ambient and focused artificial light distribution. Paper presented at the Euronoise 2018, Convention Center Creta Maris, Crete.
Mpungose, C. B. (2020). Emergent transition from face-to-face to online learning in a South African University in the context of the Coronavirus pandemic. Humanities and Social Sciences Communications, 7(113), 1-9.
National Center on Safe Supportive Learning Environment. (2021). Physical Environment. Arlington, VA: American Institutes for Research (AIR).
Ng, C. F. (2021). The Physical Learning Environment of Online Distance Learners in Higher Education – A Conceptual Model. Frontiers in Psychology, 12. doi:10.3389/fpsyg.2021.635117
Pulimeno, M., Piscitelli, P., Colazzo, S., Colao, A., & Miani, A. (2020). Indoor air quality at school and students’ performance: Recommendations of the UNESCO Chair on Health Education and Sustainable Development & the Italian Society of Environmental Medicine (SIMA). Health Promotion Perspectives, 10(3), 169-174.
Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Ali, M. (2018). Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS 3.0 (Second Edi). Kuala Lumpur: Pearson Malaysia Sdn Bhd.
Roddy, C., Amiet, D. L., Chung, J., Holt, C., Shaw, L., McKenzie, S., Garivaldis, F., Lodge, J.M. and Mundy, M.E., 2017, November. Applying best practice online learning, teaching, and support to intensive online environments: An integrative review. In Frontiers in Education (Vol. 2, p. 59). Frontiers.
Riggs, S. (2020). Student-centered remote teaching: Lessons learned from online education. EDUCAUSE.
Saidi, R. M., Sharip, A. A., Abd Rahim, N. Z., Zulkifli, Z. A., and Zain, S. M. M. (2021). Evaluating Students' Preferences of Open and Distance Learning (ODL) Tools. Procedia Computer Science, 179, pp.955-961.
Stauffer, B. (2020). What's the difference between online learning and distance learning? Digital Curriculum.
Stephan, M., Markus, S., & Gläser-Zikuda, M. (2019). Students' Achievement Emotions and Online Learning in Teacher Education. Frontiers in Education, 4. doi:10.3389/feduc.2019.00109
Simonson, M., and Berg, G. A. (2016). "Distance learning". Encyclopedia Britannica. https://www.britannica.com/topic/distance-learning. Accessed 8 September 2021.
Shackman, J. D. (2013). The Use of Partial Least Squares Path Modeling and Generalized Structured Component Analysis in International Business Research: A Literature Review. International Journal of Management. 30(3), 78-85.
Tajuddin, A. J. A., Romly, R., Hamzah, Y., Hussin, W. R. W., & Muda, W. M. W. (2021). Lecturers’ Readiness and Emotional Presence on Online Teaching Data in a Malaysian University During COVID-19. In First International Conference on Science, Technology, Engineering and Industrial Revolution (ICSTEIR 2020) (pp. 548-556). Atlantis Press.
Chin, W. W. (1998). "The partial least squares approach to structural equation modeling," Mod. methods Bus. Res., 295(2), 295–336.
World Health Organization (2021, January 21) Listings of WHO’s response to COVID-19, 29 June 2020. https://www.who.int/news/item/29-06-2020-covidtimeline
World Health Organization. (2021). Preventing and mitigating COVID-19 at work: policy brief. https://apps.who.int/iris/handle/10665/341328. License: CC BY-NC-SA 3.0 IGO
World Health Organization. (2022). COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide (Press Release).
https://www.who.int/news/item/02-03-2022-covid-19-pandemic-triggers-25-increase-in-prevalence-of-anxiety-and-depression-worldwide
Yao, S., Li, D., Yohannes, A., and Song, H. (2021). Exploration for network distance teaching and resource sharing system for higher education in epidemic situation of COVID-19. Procedia Computer Science, 183, pp.807-813.
In-Text Citation: (Sakip et al., 2022)
To Cite this Article: Sakip, S. R. M., Mahayuddin, S. A., Nayan, N. M., Ismail, A., & Ahmad, A. C. (2022). Open and Distance Learning Ability Scale for Higher Education Students: Measurement Model Analysis. International Journal of Academic Research in Business and Social Sciences, 12(4), 518–532.
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