Preparar a los instructores para la transición al aprendizaje a distancia en línea: ¿una solución para la pandemia?
DOI:
https://doi.org/10.24310/ijtei.101.2024.16820Palabras clave:
enseñanza en línea, aprendizaje a distancia en línea, COVID-19, preparación del instructorResumen
Este estudio examina la interrelación entre la preparación del instructor, la adopción de la enseñanza en línea, la actitud y la intención de comportamiento entre cuatro instructores de turismo y hotelería de la ASEAN. Este estudio amplió el modelo de la Teoría Unificada de Aceptación y Uso de la Tecnología (UTAUT) con atributos de preparación tecnológica. Se utilizaron muestreos intencionales y encuestas en línea para recopilar datos entre 248 instructores. Los instrumentos de la encuesta se adaptaron a partir de escalas establecidas, y se utilizó el modelo de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM) para probar el modelo de estudio y las hipótesis. El hallazgo mostró que la expectativa de esfuerzo (EE), la expectativa de rendimiento (PE) y la influencia social (SI) tenían un efecto directo en la actitud del instructor. Por otro lado, este estudio encontró que la preparación técnica, pedagógica y de estilo de vida es un fuerte indicador de mejorar la intención de comportamiento de un instructor para continuar impartiendo enseñanza en línea en el futuro. Además, la interacción entre la preparación técnica y de estilo de vida de los instructores sobre la intención de comportamiento difiere de la clase teórica y práctica. Los conocimientos prácticos del estudio facilitan la importancia de la enseñanza en línea de actitud y preparación tecnológica entre los instructores de hotelería y turismo. Los hallazgos del estudio también ayudan a los formuladores de políticas a diseñar un método de enseñanza de clase práctico y efectivo que sea flexible y se adapte bien al entorno dinámico de aprendizaje en línea.
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Referencias
Abou-Khalil, V., Helou, S., Khalifé, E., Chen, M. A., Majumdar, R., & Ogata, H. (2021). Emergency online learning in low-resource settings: Effective student engagement strategies. Education Sciences, 11(1), e24. https://doi.org/10.3390/educsci11010024 DOI: https://doi.org/10.3390/educsci11010024
Aditya, D. S. (2021). Embarking Digital Learning Due to COVID-19: Are Teachers Ready? Journal of Technology and Science Education, 11(1), 104-116. https://doi.org/10.3926/jotse.1109 DOI: https://doi.org/10.3926/jotse.1109
Afthanorhan, A., Nazim, A., & Ahmad, S. (2014). A parametric approach to partial least square structural equation modeling of multigroup analysis (PLS-MGA). International Journal of Economic, Commerce, and Management, 2(10), 15-24.
Akinnuwesi, B. A., Uzoka, F. M. E., Fashoto, S. G., Mbunge, E., Odumabo, A., Amusa, O. O., Okpeku, M., & Owolabi, O. (2022). A modified UTAUT model for the acceptance and use of digital technology for tackling Covid-19. Sustainable Operations and Computers, 3, 118–135. https://doi.org/10.1016/j.susoc.2021.12.001 DOI: https://doi.org/10.1016/j.susoc.2021.12.001
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004 DOI: https://doi.org/10.1016/j.chb.2019.08.004
Alea, L. A., Fabrea, M. F., Roldan, R. D. A., & Farooqi, A. Z. (2020). Teachers’ covid-19 awareness, distance learning education experiences and perceptions towards institutional readiness and challenges. International Journal of Learning, Teaching and Educational Research, 19(6), 127-144. https://doi.org/10.26803/ijlter.19.6.8 DOI: https://doi.org/10.26803/ijlter.19.6.8
Alfy, S., Gómez, J. M., & Ivanov, D. (2016). Exploring instructors’ technology readiness, attitudes and behavioral intentions towards e-learning technologies in Egypt and United Arab Emirates. Education and Information Technologies, 22(5), 2605–2627. https://doi.org/10.1007/s10639-016-9562-1 DOI: https://doi.org/10.1007/s10639-016-9562-1
Asghar, M. Z., Barberà, E., & Younas, I. (2021). Mobile Learning Technology Readiness and Acceptance among Pre-Service Teachers in Pakistan during the COVID-19 Pandemic. Knowledge Management & E-Learning, 13(1), 83-101. https://doi.org/10.34105/j.kmel.2021.13.005 DOI: https://doi.org/10.34105/j.kmel.2021.13.005
Ayodele, S., Endozo, A., & Ogbari, M. E. (2018, October). A study on factors hindering online learning acceptance in developing countries. In ICETC (Ed.), Proceedings of the 10th International Conference on Education Technology and Computers (pp. 254–258). Association for Computing Machinery. https://dl.acm.org/doi/abs/10.1145/3290511.3290533 DOI: https://doi.org/10.1145/3290511.3290533
Boettcher, J. V., & Conrad, R.-M. (2021). The online teaching survival guide: Simple and practical pedagogical tips. John Wiley & Sons.
Brinkley-Etzkorn, K.E. (2018). Learning to teach online: Measuring the influence of faculty development training on teaching effectiveness through a tpack lens. The Internet and Higher Education, 38, 28-35. https://doi.org/10.1016/j.iheduc.2018.04.004 DOI: https://doi.org/10.1016/j.iheduc.2018.04.004
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the utaut model. Frontiers in Psychology, 10, 1-14. https://doi.org/10.3389/fpsyg.2019.01652 DOI: https://doi.org/10.3389/fpsyg.2019.01652
Chin, W.W. (1998). The partial least squares approach to structural equation modelling. Advances in Hospitality and Leisure, 8(2), 295-336.
Coakes, S. J., Steed, L., & Ong, C. (2009). Analysis without anguish: SPSS version 16.0 for windows. John Wiley and Sons Ltd.
Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability, 12(24), e10367. https://doi.org/10.3390/su122410367 DOI: https://doi.org/10.3390/su122410367
Cutri, R. M., Mena, J., & Whiting, E. F. (2020). Faculty readiness for online crisis teaching: Transitioning to online teaching during the covid-19 pandemic. European Journal of Teacher Education, 43(4), 523-541. https://doi.org/10.1080/02619768.2020.1815702 DOI: https://doi.org/10.1080/02619768.2020.1815702
Davis, N. L., Gough, M., & Taylor, L. L. (2019). Online teaching: advantages, obstacles and tools for getting it right. Journal of Teaching in Travel & Tourism, 19(3), 256-263. https://doi.org/10.1080/15313220.2019.1612313 DOI: https://doi.org/10.1080/15313220.2019.1612313
Dragan, I.M., & Isaic-Maniu, A. (2013). Snowball sampling completion. Journal of Studies in Social Science, 5(2), 160-177.
Dumford, A. D., & Miller, A. L. (2018). Online learning in higher education: exploring advantages and disadvantages for engagement. Journal of Computing in Higher Education, 30(3), 452-465. https://doi.org/10.1007/s12528-018-9179-z DOI: https://doi.org/10.1007/s12528-018-9179-z
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719-734. https://doi.org/10.1007/s10796-017-9774-y DOI: https://doi.org/10.1007/s10796-017-9774-y
Dwivedi, Y.K., Rana, N.P., Janssen, M., Lal, B., Williams, M.D., &Clement, M. (2017). An empirical validation of a unified model of electronic government adoption (UMEGA). Government Information Quarterly, 34(2), 211-230. https://doi.org/10.1016/j.giq.2017.03.001 DOI: https://doi.org/10.1016/j.giq.2017.03.001
Ersin, P., Atay, D., & Mede, E. (2020). Boosting preservice teachers’ competence and online teaching readiness through e-practicum during the COVID-19 outbreak. International Journal of TESOL Studies, 2(2), 112-124.
Eseadi, C. (2023). Online Learning Attitude and Readiness of Students in Nigeria during the Covid-19 pandemic: A Case of Undergraduate Accounting Students. Innoeduca. International Journal of Technology and Educational Innovation, 9(1), 27-38. https://doi.org/10.24310/innoeduca.2023.v9i1.15503 DOI: https://doi.org/10.24310/innoeduca.2023.v9i1.15503
Estriegana, R., Medina-Merodio, J. A., & Barchino, R. (2019). Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Computers & Education, 135, 1-14. https://doi.org/10.1016/j.compedu.2019.02.010 DOI: https://doi.org/10.1016/j.compedu.2019.02.010
Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 57(2), 112-127. https://doi.org/10.1080/09523987.2020.1786772 DOI: https://doi.org/10.1080/09523987.2020.1786772
Gamage, K. A., Wijesuriya, D. I., Ekanayake, S. Y., Rennie, A. E., Lambert, C. G., & Gunawardhana, N. (2020). Online delivery of teaching and laboratory practices: Continuity of university programmes during COVID-19 pandemic. Education Sciences, 10(10), e291. https://doi.org/10.3390/educsci10100291 DOI: https://doi.org/10.3390/educsci10100291
Gay, G. H. (2016). An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education, 28(2), 199-220. https://doi.org/ 10.1007/s12528-016-9115-z DOI: https://doi.org/10.1007/s12528-016-9115-z
Geldsetzer, P. (2020). Use of rapid online surveys to assess people's perceptions during infectious disease outbreaks: a cross-sectional survey on COVID-19. Journal of Medical Internet Research, 22(4), e18790. https://doi.org/10.2196/18790 DOI: https://doi.org/10.2196/18790
Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16, e17. https://doi.org/10.1186/s41239-019-0147-0 DOI: https://doi.org/10.1186/s41239-019-0147-0
Goh, E., & King, B. (2020). Four decades (1980–2020) of hospitality and tourism higher education in Australia: Developments and future prospects. Journal of Hospitality and Tourism Education, 32(4), 266-272. https://doi.org/10.1080/10963758.2019.1685892 DOI: https://doi.org/10.1080/10963758.2019.1685892
Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923-6947. https://doi.org/10.1007/s10639-021-10523-1 DOI: https://doi.org/10.1007/s10639-021-10523-1
Guðmundsdóttir, G., & Hathaway, D. (2020). “We always make it work”: Teachers’ agency in the time of crisis. Journal of Technology and Teacher Education, 28(2), 239-250.
Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2020). When to use and how to report the results of pls-sem. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203 DOI: https://doi.org/10.1108/EBR-11-2018-0203
Hair. F. Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/ebr-10-2013-0128 DOI: https://doi.org/10.1108/EBR-10-2013-0128
Hanafiah, M. (2020). Formative vs reflective measurement model: Guidelines for structural equation modelling research. International Journal of Analysis and Applications, 18(5), 876-889. https://doi.org/10.28924/2291-8639-18-2020-876 DOI: https://doi.org/10.28924/2291-8639-18-2020-876
Henseler, J. (2012, July 21-23). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In W. A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme, & J. Kunze (Eds.), Challenges at the Interface of Data Analysis, Computer Science, and Optimization (pp. 495-501). Springer Berlin Heidelberg. DOI: https://doi.org/10.1007/978-3-642-24466-7_50
Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of Academy of Marketing Science, 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8 DOI: https://doi.org/10.1007/s11747-014-0403-8
Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers & Education, 94 , 120-133. https://doi.org/10.1016/j.compedu.2015.11.012 DOI: https://doi.org/10.1016/j.compedu.2015.11.012
Iyer, D. G., & Chapman, T. A. (2021). Overcoming technological inequity in synchronous online learning. Communications of the Association for Information Systems, 48(1), 205-212. https://doi.org/ 10.17705/1CAIS.04826 DOI: https://doi.org/10.17705/1CAIS.04826
Jung, I., & Lee, J. (2020). A cross‐cultural approach to the adoption of open educational resources in higher education. British Journal of Educational Technology, 51(1), 263-280. https://doi.org/10.1111/bjet.12820 DOI: https://doi.org/10.1111/bjet.12820
Junus, K., Santoso, H. B., Putra, P. O. H., Gandhi, A., & Siswantining, T. (2021). Lecturer readiness for online classes during the pandemic: A survey research. Education Sciences, 11(3), e139. https://doi.org/10.3390/educsci11030139 DOI: https://doi.org/10.3390/educsci11030139
Kaplan, K. J. (1972). On the ambivalence-indifference problem in attitude theory and measurement: A suggested modification of the semantic differential technique. Psychological Bulletin, 77(5), 361-372. https://doi.org/10.1037/h0032590 DOI: https://doi.org/10.1037/h0032590
Karen, E., & Etzkorn, B. (2020). The effects of training on instructor beliefs about and attitudes toward online teaching. American Journal of Distance Education, 34(1), 19-35. https://doi.org/10.1080/08923647.2020.1692553 DOI: https://doi.org/10.1080/08923647.2020.1692553
Kaushik, M. K., & Agrawal, D. (2021). Influence of technology readiness in adoption of e-learning. International Journal of Educational Management, 35(2), 483-495. https://doi.org/10.1108/IJEM-04-2020-0216 DOI: https://doi.org/10.1108/IJEM-04-2020-0216
Kemp, N., & Grieve, R. (2014). Face-to-face or face-to-screen? Undergraduates’ opinions and test performance in classroom vs. online learning. Frontiers in Psychology, 5, 1-11. https://doi.org/10.3389/fpsyg.2014.01278 DOI: https://doi.org/10.3389/fpsyg.2014.01278
Keong, Y. C., Albadry, O., & Raad, W. (2014). Behavioral intention of efl teachers to apply e-learning. Journal of Applied Sciences, 14(20), 2561-2569. https://doi.org/10.3923/jas.2014.2561.2569 DOI: https://doi.org/10.3923/jas.2014.2561.2569
Khalil, R., Mansour, A. E., Fadda, W. A., Almisnid, K., Aldamegh, M., Al-Nafeesah, A., Alkhalifah, A., & Al-Wutayd, O. (2020). The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: A qualitative study exploring medical students’ perspectives. BMC Medical Education, 20, e285. https://doi.org/10.1186/s12909-020-02208-z DOI: https://doi.org/10.1186/s12909-020-02208-z
Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the utaut model. British Journal of Educational Technology, 51(6), 2306–2325. https://doi.org/10.1111/bjet.12905 DOI: https://doi.org/10.1111/bjet.12905
Kim, D., Lee, Y., Leite, W. L., & Huggins-Manley, A. C. (2020). Exploring student and teacher usage patterns associated with student attrition in an open educational resource-supported online learning platform. Computers & Education, 156, 103961. https://doi.org/10.1016/j.compedu.2020.103961 DOI: https://doi.org/10.1016/j.compedu.2020.103961
Koet, T. W., & Abdul Aziz, A. (2021). Teachers’ and students’ perceptions towards distance learning during the covid-19 pandemic: A systematic review. International Journal of Academic Research in Progressive Education and Development, 10(3), 531-562. https://doi.org/10.6007/ijarped/v10-i3/11005 DOI: https://doi.org/10.6007/IJARPED/v10-i3/11005
König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during covid-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608-622. https://doi.org/10.1080/02619768.2020.1809650 DOI: https://doi.org/10.1080/02619768.2020.1809650
Lassoued, Z., Alhendawi, M., & Bashitialshaaer, R. (2020). An exploratory study of the obstacles for achieving quality in distance learning during the COVID-19 pandemic. Education Sciences, 10(9), e232. https://doi.org/10.3390/educsci10090232 DOI: https://doi.org/10.3390/educsci10090232
Loomis, K.D. (2000). Learning styles and asynchronous learning: Comparing the lassi model to class performance. Online Learning, 4(1), 23-32. https://doi.org/ 10.24059/olj.v4i1.1908 DOI: https://doi.org/10.24059/olj.v4i1.1908
MacKinnon, D. P. (2011). Integrating mediators and moderators in research design. Research on Social Work Practice, 21(6), 675-681. https://doi.org/ 10.1177/1049731511414148 DOI: https://doi.org/10.1177/1049731511414148
Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies, 26(6), 6629–6649. https://doi.org/10.1007/s10639-021-10465-8 DOI: https://doi.org/10.1007/s10639-021-10465-8
Mailizar, M., Almanthari, A., & Maulina, S. (2021). Examining teachers’ behavioral intention to use e-learning in teaching of mathematics: An extended tam model. Contemporary Educational Technology, 13(2), e298. https://doi.org/10.30935/cedtech/9709 DOI: https://doi.org/10.30935/cedtech/9709
Mathew, V. N., & Chung, E. (2020). University students’ perspectives on open and distance learning (odl) implementation amidst covid-19. Asian Journal of University Education, 16(4), 152-160. https://doi.org/10.24191/ajue.v16i4.11964 DOI: https://doi.org/10.24191/ajue.v16i4.11964
Mazman Akar, S. G. (2019). Does it matter being innovative: Teachers’ technology acceptance. Education and Information Technologies, 24(6), 3415-3432. https://doi.org/10.1007/s10639-019-09933-z DOI: https://doi.org/10.1007/s10639-019-09933-z
McGee, P., Windes, D., & Torres, M. (2017). Experienced online instructors: beliefs and preferred supports regarding online teaching. Journal of Computing in Higher Education, 29(2), 331-352. https://doi.org/10.1007/s12528-017-9140-6 DOI: https://doi.org/10.1007/s12528-017-9140-6
Md Yunus, M., Ang, W. S., & Hashim, H. (2021). Factors affecting teaching English as a Second Language (TESL) postgraduate students’ behavioural intention for online learning during the COVID-19 pandemic. Sustainability, 13(6), 3524. https://doi.org/10.3390/su13063524 DOI: https://doi.org/10.3390/su13063524
Mei, B., Brown, G. T., & Teo, T. (2018). Toward an understanding of preservice English as a Foreign language teachers’ acceptance of computer-assisted language learning 2.0 in the people’s Republic of China. Journal of Educational Computing Research, 56(1), 74–104. https://doi.org/10.1177/0735633117700144 DOI: https://doi.org/10.1177/0735633117700144
Mokhtar, S., Katan, H., & Rehman, H., (2018). Instructors’ behavioural intention to use learning management system: An integrated tam perspective. Technology, Education and Management Journal, 7(3), 513-525. https://doi.org/10.18421/TEM73-07
Mosunmola, A., Mayowa, A., Okuboyejo, S., & Adeniji, C. (2018, January). Adoption and use of mobile learning in higher education: The utaut model. In IC4E '18 (Ed.), Proceedings of the 9th International Conference on E-Education, E-Business, E-Management and E-Learning (pp. 20-25). Association for Computing Machinery. https://doi.org/10.1145/3183586.3183595 DOI: https://doi.org/10.1145/3183586.3183595
Munoz, K. E., Wang, M.-J., & Tham, A. (2021). Enhancing online learning environments using social presence: evidence from hospitality online courses during covid-19. Journal of Teaching in Travel & Tourism, 21(4), 339-357. https://doi.org/10.1080/15313220.2021.1908871 DOI: https://doi.org/10.1080/15313220.2021.1908871
Nikolopoulou, K., Gialamas, V., & Lavidas, K. (2021). Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet. Computers and Education Open, 2, 100041. https://doi.org/10.1016/j.caeo.2021.100041 DOI: https://doi.org/10.1016/j.caeo.2021.100041
Nikou, S. A., & Economides, A. A. (2018). Factors that influence behavioral intention to use mobile-based assessment: A stem teachers’ perspective. British Journal of Educational Technology, 50(2), 587–600. https://doi.org/10.1111/bjet.12609 DOI: https://doi.org/10.1111/bjet.12609
Oguguo, B., Ezechukwu, R., Nannim, F., & Offor, K. (2023). Analysis of teachers in the use of digital resources in online teaching and assessment in COVID times. Innoeduca. International Journal of Technology and Educational Innovation, 9(1), 81-96. https://doi.org/10.24310/innoeduca.2022.v8i1.11144 DOI: https://doi.org/10.24310/innoeduca.2023.v9i1.15419
Omotayo, F.O. & Adekunle, O.A. (2021). Adoption and use of electronic voting system as an option towards credible elections in Nigeria. International Journal of Development Issues, 20(1), 38 - 61. https://doi.org/10.1108/IJDI-03-2020-0035 DOI: https://doi.org/10.1108/IJDI-03-2020-0035
Owen, S. M., White, G., Palekahelu, D. T., Sumakul, D. T., & Sediyono, E. (2020). Integrating online learning in schools: Issues and ways forward for developing countries. Journal of Information Technology Education: Research, 19, 571-614. https://doi.org/10.28945/4625 DOI: https://doi.org/10.28945/4625
Peattie, K. (2001). Golden goose or wild goose? The hunt for the green consumer. Business Strategy and the Environment, 10(4), 187–199. https://doi.org/10.1002/bse.292 DOI: https://doi.org/10.1002/bse.292
Phan, T. T. N., & Dang, L. T. T. (2017). Teacher readiness for online teaching: A critical review. International Journal on Open and Distance E-Learning, 3(1), 1-16.
Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. Higher Education Research and Development, 26(2), 217-234. https://doi.org/10.1080/07294360701310821 DOI: https://doi.org/10.1080/07294360701310821
Prause, M. (2019). Challenges of industry 4.0 technology adoption for smes: the case of Japan. Sustainability, 11(20), e5807. https://doi.org/10.3390/su11205807 DOI: https://doi.org/10.3390/su11205807
Rafique, G. M., Mahmood, K., Warraich, N. F., & Rehman, S. U. (2021). Readiness for online learning during covid-19 pandemic: A survey of Pakistanis students. The Journal of Academic Librarianship, 47(3), 1-10. https://doi.org/10.1016/j.acalib.2021.102346 DOI: https://doi.org/10.1016/j.acalib.2021.102346
Ramos-Morcillo, A. J., Leal-Costa, C., Moral-García, J. E., & Ruzafa-Martínez, M. (2020). Experiences of nursing students during the abrupt change from face-to-face to e-learning education during the first month of confinement due to COVID-19 in Spain. International Journal of Environmental Research and Public Health, 17(15), 5519. https://doi.org/10.3390/ijerph17155519 DOI: https://doi.org/10.3390/ijerph17155519
Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Towards a unified view. Information Systems Frontiers, 19(3), 549–568. https://doi.org/10.1007/s10796-015-9613-y DOI: https://doi.org/10.1007/s10796-015-9613-y
Sabet, S. A., Moradi, F., & Soufi, S. (2022). Predicting students’ satisfaction with virtual education based on health-oriented lifestyle behaviors. Innoeduca: International Journal of Technology and Educational Innovation, 8(2), 43-57. https://doi.org/10.24310/innoeduca.2022.v8i2.13079 DOI: https://doi.org/10.24310/innoeduca.2022.v8i2.13079
Sangeeta & Tandon, U. (2021). Factors influencing adoption of online teaching by school teachers: A study during COVID‐19 pandemic. Journal of Public Affairs, 21(4), e2503. Htpps://doi.org/10.1002/pa.2503 DOI: https://doi.org/10.1002/pa.2503
Schlenz, M. A., Schmidt, A., Wöstmann, B., Krämer, N., & Schulz-Weidner, N. (2020). Students’ and lecturers’ perspective on the implementation of online learning in dental education due to SARS-CoV-2 (COVID-19): A cross-sectional study. BMC Medical Education, 20, e354. https://doi.org/10.1186/s12909-020-02266-3 DOI: https://doi.org/10.1186/s12909-020-02266-3
Selvaraj, A., Radhin, V., Nithin, K. A., Benson, N., & Mathew, A. J. (2021). Effect of pandemic based online education on teaching and learning system. International Journal of Educational Development, 85, e102444. https://doi.org/10.1016/j.ijedudev.2021.102444 DOI: https://doi.org/10.1016/j.ijedudev.2021.102444
Semerci, A., & Aydın, M. K. (2018). Examining high school teachers’ attitudes towards ICT use in education. International Journal of Progressive Education, 14(2), 93–105. https://doi.org/10.29329/ijpe.2018.139.7 DOI: https://doi.org/10.29329/ijpe.2018.139.7
Sewandono, R. E., Thoyib, A., Hadiwidjojo, D., & Rofiq, A. (2023). Performance expectancy of E-learning on higher institutions of education under uncertain conditions: Indonesia context. Education and Information Technologies, 28(4), 4041-4068. https://doi.org/10.1007/s10639-022-11074-9 DOI: https://doi.org/10.1007/s10639-022-11074-9
Sidpra, J., Gaier, C., Reddy, N., Kumar, N., Mirsky, D., & Mankad, K. (2020). Sustaining education in the age of covid-19: A survey of synchronous web-based platforms. Quantitative Imaging in Medicine and Surgery, 10(7), 1422–1427. https://doi.org/10.21037/qims-20-714 DOI: https://doi.org/10.21037/qims-20-714
Simamora, R. M. (2020). The Challenges of online learning during the COVID-19 pandemic: An essay analysis of performing arts education students. Studies in Learning and Teaching, 1(2), 86-103. https://doi.org/10.46627/silet.v1i2.38 DOI: https://doi.org/10.46627/silet.v1i2.38
Stangor, C., Tarry, H., & Jhangiani, R. (2014). Principles of Social Psychology – 1st International Edition. Pressbooks by BCcampus.
Tang, Y. M., Chen, P. C., Law, K. M., Wu, C. H., Lau, Y.-y., Guan, J., & Ho, G. T. (2021). Comparative analysis of student’s live online learning readiness during the coronavirus (Covid-19) pandemic in the higher education sector. Computers & Education, 168, e104211. https://doi.org/10.1016/j.compedu.2021.104211 DOI: https://doi.org/10.1016/j.compedu.2021.104211
Tiwari, P., Séraphin, H., & Chowdhary, N. R. (2020). Impacts of Covid-19 on tourism education: Analysis and perspectives. Journal of Teaching in Travel & Tourism, 21(4), 313-338. https://doi.org/10.1080/15313220.2020.1850392 DOI: https://doi.org/10.1080/15313220.2020.1850392
Triandis, H. C. (1971). Attitude and attitude change (foundations of social psychology). John Wileys & Sons Inc.
Tsourela, M., & Roumeliotis, M. (2015). The moderating role of technology readiness, gender, and sex in consumer acceptance and actual use of Technology-based services. The Journal of High Technology Management, 26(2), 124-136. https://doi.org/10.1016/j.hitech.2015.09.003 DOI: https://doi.org/10.1016/j.hitech.2015.09.003
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540
Wang, Y., Gu, J., Wang, S., & Wang, J. (2019). Understanding consumers’ willingness to use ride-sharing services: The roles of perceived value and perceived risk. Transportation Research Part C: Emerging Technologies, 105, 504-519. https://doi.org/10.1016/j.trc.2019.05.044 DOI: https://doi.org/10.1016/j.trc.2019.05.044
Weerakkody, V., Irani, Z., Kapoor, K., Sivarajah, U., & Dwivedi, Y. K. (2017). Open data and its usability: An empirical view from the citizen’s perspective. Information Systems Frontiers, 19(2), 285–300. https://doi.org/10.1007/s10796-016-9679-1 DOI: https://doi.org/10.1007/s10796-016-9679-1
Wei, H.-C., & Chou, C. (2020). Online learning performance and satisfaction: Do perceptions and readiness matter? Distance Education, 41(1), 48-69. https://doi.org/10.1080/01587919.2020.1724768 DOI: https://doi.org/10.1080/01587919.2020.1724768
Wilson, B. J., Deckert, A., Shah, R., Kyei, N., Copeland Dahn, L., Doe-Rogers, R., Hinneh, A. B., Johnson, L. W., Natt, G. D., Verdier, J. A., Vosper, A., Louis, V. R., Dambach, P., & Thomas-Connor, I. (2021). Covid-19-related knowledge, attitudes and practices: a mixed-mode cross-sectional survey in Liberia. BMJ Open, 11(7), 1-14. https://doi.org/10.1136/bmjopen-2021-049494 DOI: https://doi.org/10.1136/bmjopen-2021-049494
Wong, G. K. (2016). The behavioral intentions of Hong Kong primary teachers in adopting educational technology. Educational Technology Research and Development, 64(2), 313–338. https://doi.org/10.1007/s11423-016-9426-9 DOI: https://doi.org/10.1007/s11423-016-9426-9
Zikmund, W.G., Carr, B.J., Griffin, M., & Babin, B.J. (2013). Business Research Method. Dryden Press.
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