Main Article Content

Abstract

Distance learning has become the only solution for learning in the current Covid-19 pandemic outbreak. A more straightforward form of distance learning with the utilization of telepresence and cloud-based productivity tools was apparent in many institutions. The present study investigated this phenomenon and ask, “What factors affect students’ acceptance of distance learning during school closures due to COVID-19?”. An extended Unified Theory of Acceptance and Use of Technology was employed to answer the research question, with 156 students participating in the study. The result revealed that Effort Expectancy (EE) has the biggest effect on students’ acceptance of distance learning during school closures (β=0.372, p<0.001). Additionally, the extended variable of Socia l Presence (SP) was also showing great effects on students' acceptance (β=0.296, p<0.001). However, one of the UTAUT constructs, Facilitating Conditions, was found to have no effect on students' acceptance. Practical implications for schools and distance learning program managers were discussed to provide insight on improving a distance learning program. This study contributes to the body of knowledge on learning technologies as well as on how society, especially in the educational sector, should continue despite the current pandemic crisis.

Keywords

Distance Learning Covid-19 SEM Social Presence Zoom

Article Details

How to Cite
Ardiansyahmiraja, B., Nadlifatin, R., Persada, S. F., Prasetyo, Y. T., & Redi, A. P. (2021). Learning from a distance during a pandemic outbreak: Factors affecting students’ acceptance of distance learning during school closures due to COVID-19. Journal of E-Learning and Knowledge Society, 17(2), 21-31. https://doi.org/10.20368/1971-8829/1135412

References

  1. ADNAN, M. & ANWAR, K. 2020. Online Learning amid the COVID-19 Pandemic: Students' Perspectives. Online Submission, 2, 45-51. doi: 10.33902/JPSP.2020261309
  2. ALLEN, M., MABRY, E., MATTREY, M., BOURHIS, J., TITSWORTH, S. & BURRELL, N. 2004. Evaluating the effectiveness of distance learning: A comparison using meta‐analysis. Journal of communication, 54, 402-420. doi: 10.1111/j.1460-2466.2004.tb02636.x
  3. ALSHEHRI, A., RUTTER, M. J., & SMITH, S. (2019). An implementation of the UTAUT model for understanding students' perceptions of learning management systems: A study within tertiary institutions in Saudi Arabia. International Journal of Distance Education Technologies (IJDET), 17(3), 1-24. doi: 10.4018/IJDET.2019070101
  4. AMENDOLA, D., & MICELI, C. (2016). Online Physics laboratory for University courses. Journal of E-Learning and Knowledge Society, 12(3). doi: 10.20368/1971-8829/1165
  5. AMIR, L., TANTI, I., MAHARANI, D. A., WIMARDHANI, Y., JULIA, V., SULIJAYA, B. & PUSPITAWATI, R. 2020. Student Perspective Of Classroom And Distance Learning Method During Covid-19 Pandemic In The Undergraduate Dental Study Program. doi: 10.21203/rs.3.rs-42334/v1
  6. ANASTASIADES, P. S., FILIPPOUSIS, G., KARVUNIS, L., SIAKAS, S., TOMAZINAKIS, A., GIZA, P. & MASTORAKI, H. 2010. Interactive Videoconferencing for collaborative learning at a distance in the school of 21st century: A case study in elementary schools in Greece. Computers & Education, 54, 321-339. doi: 10.1016/j.compedu.2009.08.016
  7. ANDREWS, T. & TYNAN, B. 2012. Distance learners: Connected, mobile and resourceful individuals. Australasian Journal of Educational Technology, 28. doi: 10.14742/ajet.828
  8. BASILAIA, G., DGEBUADZE, M., KANTARIA, M. & CHOKHONELIDZE, G. 2020. Replacing the Classic Learning Form at Universities as an Immediate Response to the COVID-19 Virus Infection in Georgia. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 8, 101-8. doi: 10.22214/ijraset.2020.3021
  9. BEYTH-MAROM, R., CHAJUT, E., ROCCAS, S. & SAGIV, L. 2003. Internet-assisted versus traditional distance learning environments: factors affecting students' preferences. Computers & Education, 41, 65-76. doi: 10.1016/S0360-1315(03)00026-5
  10. BIRCH, A. & IRVINE, V. 2009. Preservice teachers' acceptance of ICT integration in the classroom: applying the UTAUT model. Educational media international, 46, 295-315. doi: 10.1080/09523980903387506
  11. BOS, B., WILDER, L., COOK, M. & O'DONNELL, R. 2014. Learning mathematics through Minecraft. Teaching Children Mathematics, 21, 56-59. doi: 10.5951/teacchilmath.21.1.0056
  12. BUI, T.-H., LUONG, D.-H., NGUYEN, X.-A., NGUYEN, H.-L. & NGO, T.-T. 2020. Impact of female students' perceptions on behavioral intention to use video conferencing tools in COVID-19: Data of Vietnam. Data in Brief, 106142. doi: 10.1016/j.dib.2020.106142
  13. CAI, J., YANG, H. H. & GONG, D. Understanding Undergraduates' Adoption of Flipped Learning: Integrating UTAUT and Social Presence. International Conference on Blended Learning, 2019. Springer, 9-21. doi: 10.1007/978-3-030-21562-0_2
  14. CHAU, M. 2008. The effects of electronic books designed for children in education.
  15. CHAWLA, A. 2020. Coronavirus (COVID-19)-'Zoom'Application Boon or Bane. Available at SSRN 3606716. doi: 10.2139/ssrn.3606716
  16. CHICK, R. C., CLIFTON, G. T., PEACE, K. M., PROPPER, B. W., HALE, D. F., ALSEIDI, A. A. & VREELAND, T. J. 2020. Using technology to maintain the education of residents during the COVID-19 pandemic. Journal of Surgical Education. doi: 10.1016/j.jsurg.2020.03.018
  17. CHURIYAH, M., SHOLIKHAN, S., FILIANTI, F. & SAKDIYYAH, D. A. 2020. Indonesia Education Readiness Conducting Distance Learning in Covid-19 Pandemic Situation. International Journal of Multicultural and Multireligious Understanding, 7, 491-507. doi: 10.18415/ijmmu.v7i6.1833
  18. CINQUE, M., & PENSIERI, C. (2009). Campus We-Com. University students attitude towards didactical innovation. Journal of e-learning and knowledge society, 5(1), 181-189. Doi: 10.20368/1971-8829/305
  19. COOPER, D. R., SCHINDLER, P. S., & SUN, J. (2006). Business research methods (Vol. 9, pp. 1-744). New York: Mcgraw-hill.
  20. CUSHMAN & WAKEFIELD 2020. GLOBAL ECONOMY REOPENING TRACKER 11 August, 2020.
  21. DIETRICH, N., KENTHESWARAN, K., AHMADI, A., TEYCHENÉ, J., BESSIÈRE, Y., ALFENORE, S., LABORIE, S. P., BASTOUL, D., LOUBIÈRE, K. & GUIGUI, C. 2020. Attempts, Successes, and Failures of Distance Learning in the Time of COVID-19. Journal of Chemical Education. doi: 10.1021/acs.jchemed.0c00717
  22. FORNELL, C. & LARCKER, D. F. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18, 39-50. doi: 10.1177/002224378101800104
  23. GARRISON, D. R., CLEVELAND-INNES, M. & FUNG, T. S. 2010. Exploring causal relationships among teaching, cognitive and social presence: Student perceptions of the community of inquiry framework. The Internet and higher education, 13, 31-36. doi: 10.1016/j.iheduc.2009.10.002
  24. GON, S. & RAWEKAR, A. 2017. Effectivity of E-learning through Whatsapp as a teaching learning tool. MVP Journal of Medical Science, 4, 19-25. doi: 10.18311/mvpjms/0/v0/i0/8454
  25. Google. (2020). Zoom School - Explore - Google Trends. https://trends.google.com/trends/explore?q=zoom%20school
  26. GUNAWARDENA, C. N. & ZITTLE, F. J. 1997. Social presence as a predictor of satisfaction within a computer‐mediated conferencing environment. American journal of distance education, 11, 8-26. doi: 10.1080/08923649709526970
  27. HANNAY, M. & NEWVINE, T. 2006. Perceptions of distance learning: A comparison of online and traditional learning. Journal of Online Learning and Teaching, 2, 1-11.
  28. HEAD, M. & ZIOLKOWSKI, N. 2012. Understanding student attitudes of mobile phone features: Rethinking adoption through conjoint, cluster and SEM analyses. Computers in Human Behavior, 28, 2331-2339. doi: 10.1016/j.chb.2012.07.003
  29. HEERINK, M., KRÖSE, B., EVERS, V. & WIELINGA, B. 2008. The influence of social presence on acceptance of a companion robot by older people. doi: 10.14198/JoPha.2008.2.2.05
  30. HOOPER, D., COUGHLAN, J. & MULLEN, M. R. 2008. Structural equation modelling: Guidelines for determining model fit. Electronic journal of business research methods, 6, 53-60.
  31. HORNBÆK, K. & HERTZUM, M. 2017. Technology acceptance and user experience: A review of the experiential component in HCI. ACM Transactions on Computer-Human Interaction (TOCHI), 24, 1-30. doi: 10.1145/3127358
  32. HOX, J. J. & BECHGER, T. M. 1998. An introduction to structural equation modeling.
  33. HSU, C.-L. & LIN, J. C.-C. 2008. Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & management, 45, 65-74. doi: 10.1016/j.im.2007.11.001
  34. HUANG, R., TLILI, A., CHANG, T.-W., ZHANG, X., NASCIMBENI, F. & BURGOS, D. 2020. Disrupted classes, undisrupted learning during COVID-19 outbreak in China: application of open educational practices and resources. Smart Learning Environments, 7, 1-15. doi: 10.1186/s40561-020-00125-8
  35. KETTLES, N. & VAN BELLE, J.-P. Investigation into the antecedents of autonomous car acceptance using an enhanced UTAUT model. 2019 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD), 2019. IEEE, 1-6. doi: 10.1109/ICABCD.2019.8851011
  36. KHECHINE, H., LAKHAL, S., PASCOT, D. & BYTHA, A. 2014. UTAUT model for blended learning: The role of gender and age in the intention to use webinars. Interdisciplinary Journal of E-Learning and Learning Objects, 10, 33-52. doi: 10.28945/1994
  37. KONDRATOVA, L. 2020. The organization of distance learning of music teachers in the conditions of postgraduate education reforming. ScienceRise: Pedagogical Education, 45-49. doi: 10.15587/2519-4984.2020.207401
  38. LAKHAL, S., KHECHINE, H. & PASCOT, D. 2013. Student behavioural intentions to use desktop video conferencing in a distance course: integration of autonomy to the UTAUT model. Journal of Computing in Higher Education, 25, 93-121. doi: 10.1007/s12528-013-9069-3
  39. LEWIS, E. E., TAYLOR, L. J., HERMSEN, J. L., MCCARTHY, D. P. & FIEDLER, A. G. 2020. Cardiothoracic education in the time of COVID-19: how I teach it. The Annals of thoracic surgery, 110, 362-363. doi: 10.1016/j.athoracsur.2020.04.002
  40. MARCHEWKA, J. T. & KOSTIWA, K. 2007. An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7, 10.
  41. MAVROIDIS, I., KARATRANTOU, A., KOUTSOUBA, M., GIOSSOS, Y. & PAPADAKIS, S. 2013. Technology Acceptance and Social Presence in Distance Education--A Case Study on the Use of Teleconference at a Postgraduate Course of the Hellenic Open University. European Journal of Open, Distance and E-learning, 16, 76-96.
  42. MEMON, M. A., TING, H., RAMAYAH, T., CHUAH, F., & CHEAH, J. H. (2017). A review of the methodological misconceptions and guidelines related to the application of structural equation modeling: A Malaysian scenario. Journal of applied structural equation modeling, 1(1), 1-13.
  43. MUN, Y. Y. & HWANG, Y. 2003. Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International journal of human-computer studies, 59, 431-449. doi: 10.1016/S1071-5819(03)00114-9
  44. NOWAK, K. L. & BIOCCA, F. 2003. The effect of the agency and anthropomorphism on users' sense of telepresence, copresence, and social presence in virtual environments. Presence: Teleoperators & Virtual Environments, 12, 481-494. doi: 10.1162/105474603322761289
  45. OH, S., LEHTO, X. Y. & PARK, J. 2009. Travelers' intent to use mobile technologies as a function of effort and performance expectancy. Journal of Hospitality Marketing & Management, 18, 765-781. doi: 10.1080/19368620903235795
  46. PERSADA, S. F., MIRAJA, B. A., & NADLIFATIN, R. (2019). Understanding the Generation Z Behavior on D-Learning: A Unified Theory of Acceptance and Use of Technology (UTAUT) Approach. International Journal of Emerging Technologies in Learning, 14(5).
  47. RAMAN, A., DON, Y., KHALID, R. & RIZUAN, M. 2014. Usage of learning management system (Moodle) among postgraduate students: UTAUT model. Asian Social Science, 10, 186-192. doi: 10.5539/ass.v10n14p186
  48. SALLOUM, S. A. & SHAALAN, K. Factors affecting students' acceptance of e-learning system in higher education using UTAUT and structural equation modeling approaches. International Conference on Advanced Intelligent Systems and Informatics, 2018. Springer, 469-480. doi: 10.1007/978-3-319-99010-1_43
  49. SANDARS, J., CORREIA, R., DANKBAAR, M., DE JONG, P., GOH, P. S., HEGE, I., MASTERS, K., OH, S.-Y., PATEL, R. & PREMKUMAR, K. 2020. Twelve tips for rapidly migrating to online learning during the COVID-19 pandemic. MedEdPublish, 9. doi: 10.15694/mep.2020.000082.1
  50. SEXTON, J., HOLZMUELLER, C., PRONOVOST, P., THOMAS, E., MCFERRAN, S., NUNES, J., THOMPSON, D., KNIGHT, A., PENNING, D. & FOX, H. 2006. Variation in caregiver perceptions of teamwork climate in labor and delivery units. Journal of perinatology, 26, 463-470. doi: 10.1038/sj.jp.7211556
  51. SEYAL, A. H., RAHMAN, M. N. A. & RAHIM, M. M. 2002. Determinants of academic use of the Internet: a structural equation model. Behaviour & Information Technology, 21, 71-86. doi: 10.1080/01449290210123354
  52. SHEN, J. 2012. Social comparison, social presence, and enjoyment in the acceptance of social shopping websites. Journal of Electronic Commerce Research, 13, 198.
  53. SHI, W. An empirical research on users' acceptance of smart phone online application software. 2009 International Conference on Electronic Commerce and Business Intelligence, 2009. IEEE, 106-110. doi: 10.1109/ECBI.2009.102
  54. SMITH, J. 2006. The effect of social presence on teacher technology acceptance, continuance intention, and performance in an online teacher professional development course.
  55. STONE, R. W., GOOD, D. J. & BAKER-EVELETH, L. 2007. The impact of information technology on individual and firm marketing performance. Behaviour & Information Technology, 26, 465-482. doi: 10.1080/01449290600571610
  56. Stonebraker, P. W., & Hazeltine, J. E. (2004). Virtual learning effectiveness. The Learning Organization.
  57. TABER, K. S. 2018. The use of Cronbach's alpha when developing and reporting research instruments in science education. Research in Science Education, 48, 1273-1296. doi: 10.1007/s11165-016-9602-2
  58. TAN, P. J. B. 2013a. Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. Sage Open, 3, 2158244013503837. doi: 10.1177/2158244013503837
  59. TAN, P. J. B. 2013b. Students' adoptions and attitudes towards electronic placement tests: A UTAUT analysis. American Journal of Computer Technology and Application, 1, 14-23.
  60. TEO, T. 2014. Unpacking teachers' acceptance of technology: Tests of measurement invariance and latent mean differences. Computers & Education, 75, 127-135. doi: 10.1016/j.compedu.2014.01.014
  61. TERÄS, M., SUORANTA, J., TERÄS, H. & CURCHER, M. 2020. Post-Covid-19 Education and Education Technology 'Solutionism': a Seller's Market. Postdigital Science and Education, 1-16. doi: 10.1007/s42438-020-00164-x
  62. THOMAS, T., SINGH, L. & GAFFAR, K. 2013. The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana. International Journal of Education and Development using ICT, 9.
  63. TSAI, S. & MACHADO, P. 2002. E-Learning Basics: Essay: E-learning, online learning, web-based learning, or distance learning: unveiling the ambiguity in current terminology. eLearn, 2002, 3. doi: 10.1145/566778.568597
  64. TURK, V. 2020. Zoom took over the world. This is what will happen next. Wired UK.
  65. UNESCO. 2020. COVID-19 Impact on Education [Online]. Available: https://en.unesco.org/covid19/educationresponse [Accessed 13 August 2020].
  66. VARALAKSHMI, R. & ARUNACHALAM, K. 2020. COVID 2019-ROLE OF FACULTY MEMBERS TO KEEP MENTAL ACTIVENESS OF STUDENTS. Asian Journal of Psychiatry, 51, 102091. doi: 10.1016/j.ajp.2020.102091
  67. VENKATESH, V., MORRIS, M. G., DAVIS, G. B. & DAVIS, F. D. 2003. User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. doi: 10.2307/30036540
  68. WANG, C.-H., LIU, W.-L., TSENG, M.-C. & TSAI, H.-S. 2010. A Study of Taiwanese College Teachers' Acceptance of Distance Learning. International Journal of Organizational Innovation, 3.
  69. WONG, K.-T., TEO, T. & RUSSO, S. 2013. Interactive whiteboard acceptance: Applicability of the UTAUT model to student teachers. The Asia-Pacific Education Researcher, 22, 1-10. doi: 10.1007/s40299-012-0001-9
  70. WORLD HEALTH ORGANIZATION 2020. Coronavirus disease 2019 (COVID-19): situation report, 204.