Vol. 9 Núm. 3 (2020): Número extraordinario: Consecuencias del Cierre de Escuelas por el Covid-19 en las Desigualdades Educativas

Impact of Faculty and Student Readiness on Virtual Learning Adoption amid Covid-19

Mohammad Rokibul Kabir
Publicado diciembre 21, 2020

Palabras clave:

Covid-19; Higher education; Social imbalance; Technology adoption; Virtual learning.
Cómo citar
Rokibul Kabir, M. (2020). Impact of Faculty and Student Readiness on Virtual Learning Adoption amid Covid-19. Revista Internacional De Educación Para La Justicia Social, 9(3), 387-414. https://doi.org/10.15366/riejs2020.9.3.021


The deadly effect of Covid-19 has changed the world dramatically. The education sector is one of the worst sufferers due to the official closures of educational institutions worldwide. The government of Bangladesh has declared all the on-campus activities shut in March 2020. This paper explains the effect of faculty and student readiness in adopting virtual classes considering the mediating effect of technology adoption intention. Teachers and students from private and public universities in Bangladesh are surveyed for this research. The findings revealed that the private universities are well ahead of providing online education as their faculty and students are ready with logistics and mindset to adopt technology-based virtual learning while the public university stakeholders are yet to initiate it. It is concluded that the lack of readiness of public universities will create a massive gap between public and private university education and rural and urban students as well. The proposed model of this research can help the policymakers and the government in formulating policy guidelines for bringing all the students and teachers on virtual education platforms irrespective of their university affiliations.


Los datos de descargas todavía no están disponibles.


Adnan, M. (2018). Professional development in the transition to online teaching: The voice of entrant online instructors. ReCALL, 30(1), 88-111. https://doi.org/10.1017/S0958344017000106

Agarwal, R. & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391 . https://doi.org/10.1111/j.1540-5915.1999.tb01614.x

Ajzen, I., Nichols, A. J., & Driver, B. L. (1995). Identifying salient beliefs about leisure activities: Frequency of elicitation versus response latency 1. Journal of Applied Social Psychology, 25(16), 1391-1410. https://doi.org/10.1111/j.1559-1816.1995.tb02623.x

Allen, I. E. & Seaman, J. (2016). Online report card: Tracking online education in the United States. Babson Survey Research Group.

Al-Rabiaah, A., Temsah, M. H., Al-Eyadhy, A. A., Hasan, G. M., Al-Zamil, F., Al-Subaie, S., ... & Somily, A. M. (2020). Middle east respiratory syndrome-corona virus (MERS-CoV) associated stress among medical students at a university teaching hospital in Saudi Arabia. Journal of Infection and Public Health, 13(5), 687-691. https://doi.org/10.1016/j.jiph.2020.01.005

Askari, R. (may, 8, 2020). The impact of Covid-19 on higher education in Bangladesh. Dhaka courier. https://dhakacourier.com.bd/news/Column/the-impact-of-covid-19-on-higher-education-in-bangladesh/2397.html

Balkin, R. S., Buckner, D., Swartz, J., & Rao, S. (2005). Issues in classroom management in an interactive distance education course. International Journal of Instructional Media, 32(4), 363-372.

Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. https://doi.org/10.1037/0022-3514.51.6.1173

Bedford, J., Enria, D., Giesecke, J., Heymann, D. L., Ihekweazu, C., Kobinger, G., ... & Ungchusak, K. (2020). Covid-19: Towards controlling of a pandemic. The Lancet, 395(10229), 1015-1018. https://doi.org/10.1016/S0140-6736(20)30673-5

Bickel, R. (2012). Multilevel analysis for applied research: It's just regression! Guilford Press.

Bower, M., Dalgarno, B., Kennedy, G. E., Lee, M. J., & Kenney, J. (2015). Design and implementation factors in blended synchronous learning environments: Outcomes from a cross-case analysis. Computers & Education, 86, 1-17. https://doi.org/10.1016/j.compedu.2015.03.006

Bozkurt, A. & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), 1-6.

Brooks, C. & Grajek, S. L. (april, 9, 2020). Institutional readiness to adopt fully remote learning. EDUCAUSE. https://er.educause.edu/blogs/2020/4/institutional-readiness-to-adopt-fully-remote-learning.

Bussmann, S., Johnson, S. R., Oliver, R., Forsythe, K., Grandjean, M., Lebsock, M., & Luster, T. (2017). On the recognition of quality online course design in promotion and tenure: A survey of higher ed institutions in the western United States. Online Journal of Distance Learning Administration, 20(1), art 1.

Callaghan, W., Wilson, B., Ringle, C. M., & Henseler, J. (2007). Exploring causal path directionality for a marketing model using cohen’s path method. MATFORSK.

Carrión, G. C., Nitzl, C., & Roldán, J. L. (2017). Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples. In H. Latan and R. D. Noonan (Eds.), Partial least squares path modeling (pp. 173-195). Springer. https://doi.org/10.1007/978-3-319-64069-3_8

Celik, V. & Yesilyurt, E. (2013). Attitudes to technology, perceived computer self-efficacy and computer anxiety as predictors of computer supported education. Computers & Education, 60(1), 148-158. https://doi.org/10.1016/j.compedu.2012.06.008

Chang, I. & Chen, R. (2020). The impact of perceived usefulness on satisfaction with online parenting resources: The mediating effects of liking and online interaction. Asia-Pacific Education Researcher, 29, 307-317. https://doi.org/10.1007/s40299-019-00484-y.

Child, D. (2006). The essentials of factor analysis. A&C Black.

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.

Chin, W. W. (1998a). Commentary: Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7-16. 259.

Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217. https://doi.org/10.1287/isre.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, Inc.

Compeau, D. R. & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 5(1), 189-211. https://doi.org/10.2307/249688

Coopasami, M., Knight, S., & Pete M. (2017). E-Learning readiness amongst nursing students at the Durban University of Technology. Health Sa Gesondheid, 22(1), 300-306. https://doi.org/10.1016/j.hsag.2017.04.003

Cox, D. R. & Hinkley, D. V. (1979). Theoretical statistics. CRC Press. https://doi.org/10.1201/b14832

Cutri, R. M. & Mena, J. (2020). A critical reconceptualization of faculty readiness for online teaching. Distance Education, 41(3), 361-380. https://doi.org/10.1080/01587919.2020.1763167

Cutri, R. M. & Whiting, E. F. (2018). Opening spaces for teacher educator knowledge in a faculty development program on blended learning course development. Studying Teacher Education, 14(2), 125-140. https://doi.org/10.1080/17425964.2018.1447920

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 3(2), 319-340. https://doi.org/10.2307/249008

Deci, E. L. & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer. https://doi.org/10.1007/978-1-4899-2271-7

Denis, B., Watland, P., Pirotte, S., & Verday, N. (2004). Roles and competencies of the e-tutor. In AAVV (Coord.), Proceedings of the fourth international conference (pp. 150-157). Networked learning.

Eble, K. (1994). Craft of teaching: A guide to mastering the professor's art. Jossey-Bass.

Falk, R. F. & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.

Field, A. (2009). Discovering statistics using SPSS. Sage publications.

Fishbein, M., Jaccard, J., Davidson, A. R., Ajzen, I., & Loken, B. (1980). Predicting and understanding family planning behaviors. Prentice Hall.

Flores, M. & Gago, M. (2020). Teacher education in times of Covid-19 pandemic in Portugal: National, institutional and pedagogical responses. Journal of Education for Teaching, 46(4), 1-10. https://doi.org/10.1080/02607476.2020.1799709

Fornell, C. & Cha, J. (1994). Partial least squares. Advanced Methods of Marketing Research, 407, 52-78. https://doi.org/10.1002/0471667196.ess1914.pub2

Fornell, C. & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.1177/002224378101800313

Frydenberg, J. (2007). Persistence in university continuing education online classes. The International Review of Research in Open and Distributed Learning, 8(3), 375-389. https://doi.org/10.19173/irrodl.v8i3.375.

Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. Taylor & Francis. https://doi.org/10.4324/9780203838761

Garrison, D. R., Anderson, T., & Archer, W. (2003). A theory of critical inquiry in online distance education. Handbook of Distance Education, 1, 113-127.

Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107. https://doi.org/10.1093/biomet/61.1.101.

Godoe, P. & Johansen, T. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students, 3(1), art 2. https://doi.org/10.5334/jeps.aq

Gülbahar, Y. & Adnan, M. (2020). Faculty professional development in creating significant teaching and learning experiences online. In M. Adan (Ed.), Handbook of research on creating meaningful experiences in online courses (pp. 37-58). IGI Global. https://doi.org/10.4018/978-1-7998-0115-3.ch004

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed, a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202. https://doi.org/10.15358/9783800653614

Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling. Sage. https://doi.org/10.15358/9783800653614

Hair J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis. Prentice.

Hardy, J. V. (1998). Teacher attitudes toward and knowledge of computer technology. Computers in the Schools, 14(4), 119-136. https://doi.org/10.1300/J025v14n03_11

Hashim, H. & Tasir, Z. (2014). E-learning readiness: A literature review. International Conference on Teaching and Learning in Computing and Engineering, 7, 267-271. https://doi.org/10.1109/LaTiCE.2014.58

Henseler, J. & Fassott, G. (2010). Testing moderating effects in PLS path models: An illustration of available procedures. In J. Henseler (Ed.), Handbook of partial least squares (pp. 713-735). Springer. https://doi.org/10.1007/978-3-540-32827-8_31

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Academy of Marketing Science Journal, 43(1), 115-129. https://doi.org/10.1007/s11747-014-0403-8

Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277-320. https://doi.org/10.1108/S1474-7979(2009)0000020014.

Islam, M. Z. (April, 14, 2020). Mobile internet slowest in Bangladesh among 42 countries. The Daily Stars. https://www.thedailystar.net/business/news/mobile-internet-slowest-bangladesh-among-42-countries-1892761

Islam, M. K., Islam, Y. M., Hossain, M. E., & Hoque, M. S. (2016). Articulation of group dynamics of undergraduate students in social media. http://oasis.col.org/handle/11599/2508.

Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on motivation in collaborative learning: Moving beyond the cognitive-situative divide and combining individual and social processes. Educational Psychologist, 45(1), 15-27. https://doi.org/10.1080/00461520903433539

Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers & Education, 95, 114-122. https://doi.org/10.1016/j.compedu.2015.12.004

Kafka, A. C. (2020). Shock, fear, and fatalism: As coronavirus prompts colleges to close, students grapple with uncertainty. The Cronicle of Higher Education.

Khalifeh, G., Noroozi, O., Farrokhnia, M., & Talaee, E. (2020). Higher education students’ perceived readiness for computer-supported collaborative learning. Multimodal Technologies and Interaction, 4(2), 11. https://doi.org/10.3390/mti4020011

Khan, M., Hossain, S., Hasan, M., & Clement, C. K. (2012). Barriers to the introduction of ICT into education in developing countries: The example of Bangladesh. Online Submission, 5(2), 61-80.

Khan, S. & Hancioglu, A. (2019). Multiple indicator cluster surveys: Delivering robust data on children and women across the globe. Studies in Family Planning, 50(3), 279-286. https://doi.org/10.1111/sifp.12103

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) 1-15. https://doi.org/10.1080/02619768.2020.1809650

Krejcie, R. V. & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308

Kyei-Blankson, L., Ntuli, E., & Blankson, J. (Eds.). (2019). Handbook of research on creating meaningful experiences in online courses. IGI Global. https://doi.org/10.4018/978-1-7998-0115-3

Li, K., Li, Y., & Franklin, T. (2016). Preservice teachers’ intention to adopt technology in their future classrooms. Journal of Educational Computing Research, 54(7), 946-966. https://doi.org/10.1177/0735633116641694

Li, Q. & Ma, X. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review, 22(3), 215-243. https://doi.org/10.1007/s10648-010-9125-8

Li, W., Lee, A. M., & Solmon, M. A. (2005). Relationships among dispositional ability conceptions, intrinsic motivation, perceived competence, experience, and performance. Journal of Teaching in Physical Education, 24(1), 51-65. https://doi.org/10.1123/jtpe.24.1.51

Liouville, J. & Bayad, M. (1998). Human resource management and performances: Proposition and test of a causal model. Human Systems Management, 17(3), 183-192. https://doi.org/10.1177/239700229801200304

Liu, X., Liu, S., Lee, S., & Magjuka, R. J. (2010). Cultural differences in online learning: International student perceptions. Educational Technology and Society, 13(3), 177-188.

Martin, F., Wang, C., Jokiaho, A., May, B., & Grübmeyer, S. (2019). Examining faculty readiness to teach online: A comparison of US and German educators. European Journal of Open, Distance and E-Learning, 22(1), 53-69. https://doi.org/10.2478/eurodl-2019-0004.

McIntyre, M. (2020). How coronavirus is affecting the mental health of millions of Americans. https://www.psycom.net/coronavirus-mental-health.html

Mitra, A., Hazen, M. D., LaFrance, B., & Rogan, R. G. (1999). Faculty use and non-use of electronic mail: Attitudes, expectations and profiles. Journal of Computer-Mediated Communication, 4(3), 297-318. https://doi.org/10.1111/j.1083-6101.1999.tb00097.x

Mtebe, J. & Raisamo, R. (2014). Investigating students’ behavioural intention to adopt and use mobile learning in higher education in East Africa. International Journal of Education and Development Using ICT, 10(3), 148476.

Nami, F. & Vaezi, S. (2018). How ready are our students for technology-enhanced learning? Students at a university of technology respond. Journal of Computing in Higher Education, 30(3), 510-529. https://doi.org/10.1007/s12528-018-9181-5

Noroozi, O. & Hatami, J. (2019). The effects of online peer feedback and epistemic beliefs on students’ argumentation-based learning. Innovations in Education and Teaching International, 56(5), 548-557. https://doi.org/10.1080/14703297.2018.1431143

Notari, M., Baumgartner, A., & Herzog, W. (2014). Social skills as predictors of communication, performance and quality of collaboration in project?based learning. Journal of Computer Assisted Learning, 30(2), 132-147. https://doi.org/10.1111/jcal.12026

Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill

Osborne, J. W., Costello, A. B., & Kellow, J. T. (2008). Exploratory factor analysis (EFA) is rightly described as both an art and a science. Best Practices in Quantitative Methods, 86, e6243. https://doi.org/10.4135/9781412995627

Osman, M. E. (2005). Students’ reaction to WebCT: Implications for designing online learning environments. International Journal of Instructional Media, 32(4), 353-362.

Parasuraman, A. & Colby, C. L. (2007). Techno-ready marketing: How and why your customers adopt technology. The Free Press.

Phielix, C., Prins, F. J., & Kirschner, P. A. (2010). Awareness of group performance in a CSCL-environment: Effects of peer feedback and reflection. Computers in Human Behavior, 26(2), 151-161. https://doi.org/10.1016/j.chb.2009.10.011

Preacher, K. J. & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36, 717-731. https://doi.org/10.3758/BF03206553

Raffo, D. M., Fisher, L. S., & Raffo, D. M. (2015). Balancing online teaching activities: Strategies for optimizing efficiency and effectiveness. The Free Press.

Rennie, F. & Morrison, T. (2013). E-learning and social networking handbook: Resources for higher education. Routledge. https://doi.org/10.4324/9780203120279

Renninger, K. A., Cai, M., Lewis, M. C., Adams, M. M., & Ernst, K. L. (2011). Motivation and learning in an online, unmoderated, mathematics workshop for teachers. Educational Technology Research and Development, 59(2), 229-247. https://doi.org/10.1007/s11423-011-9195-4

Ryan, R. M. & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. https://doi.org/10.1006/ceps.1999.1020

Ryan, R. M., Connell, J. P., & Grolnick, W. S. (1992). When achievement is not intrinsically motivated: A theory of internalization and self-regulation in school. Achievement and Motivation: A Social-Developmental Perspective, 167(88), 167-188.

Sahu, P. (2020). Closure of universities due to Coronavirus Disease 2019 (COVID-19): impact on education and mental health of students and academic staff. Cureus, 12(4), e7541. https://doi.org/10.7759/cureus.7541

Sarker, M., Mahmud, R., Islam, M. S., & Islam, M. K. (2019). Use of e-learning at higher educational institutions in Bangladesh: Opportunities and challenges. Journal of Applied Research in Higher Education, 11(2), 210-223. https://doi.org/10.1108/JARHE-06-2018-0099.

Shenoy, M. V, Mahendra.M. S. & Vijay, M. N. (2020). Covid-19. Lockdown: Technology adaption, teaching, learning, student’s engagement and faculty experience. Mukt Shabd Journal, 9(4), 698-702.

Slof, B., Nijdam, D., & Janssen, J. (2016). Do interpersonal skills and interpersonal perceptions predict student learning in CSCL-environments? Computers & Education, 97, 49-60. https://doi.org/10.1016/j.compedu.2016.02.012

Smith, P. J. (2005). Learning preferences and readiness for online learning. Educational Psychology, 25(1), 3-12. https://doi.org/10.1080/0144341042000294868

Stansfield, M., McLellan, E., & Connolly, T. M. (2004). Enhancing student performance in online learning and traditional face-to-face class delivery. Journal of Information Technology Education, 3, 173-188. https://doi.org/10.28945/296

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111-147. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x

Sureshchandar, G. S., Rajendran, C., & Anantharaman, R. N. (2002). The relationship between service quality and customer satisfaction–a factor specific approach. Journal of Services Marketing, 16(4), 363-379. https://doi.org/10.1108/08876040210433248

Swanson, E. B. (1988). Management information system: Appreciation and involvement. Management Science, 21(2), 178-188. https://doi.org/10.1287/mnsc.21.2.178

Tacq, J. J. & Tacq, J. (1997). Multivariate analysis techniques in social science research: From problem to analysis. Sage.

Teo, T. (2010). A path analysis of pre-service teachers' attitudes to computer use: Applying and extending the technology acceptance model in an educational context. Interactive Learning Environments, 18(1), 65-79. https://doi.org/10.1080/10494820802231327

Teo, T., Lee, C. B., & Chai, C. S. (2008). Understanding pre?service teachers' computer attitudes: Applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128-143. https://doi.org/10.1111/j.1365-2729.2007.00247.x

Toquero, C. M. (2020). Challenges and opportunities for higher education amid the covid-19 pandemic: The Philippine context. Pedagogical Research, 5(4), em0063. https://doi.org/10.29333/pr/7947

Uddin, M. (june, 13, 2020). Effects of the pandemic on the education sector in Bangladesh. The Financial Express. https://thefinancialexpress.com.bd/views/effects-of-the-pandemic-on-the-education-sector-in-bangladesh-1592061447

Ünal, Y., Al?r, G., & Soydal, I. (2014). Students readiness for e-learning: An assessment on hacettepe university department of information management. Communications in Computer and Information Science, 137-147. https://doi.org/10.1007/978-3-662-44412-2_13.

UNESCO. (2020). Covid-19 educational disruption and response. UNESCO.

UNESCO. (2020). Dealing with obstacles to distance learning. UNESCO.

Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.

Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: From foundations to recent developments and open issues for model assessment and improvement. In V. E. Vinzi, W. W. Chin, J. R. Henseler (Eds.), Handbook of partial least squares (pp. 47-82). Springer. https://doi.org/10.1007/978-3-540-32827-8_3

Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92-118. https://doi.org/10.1111/j.1467-8535.2007.00809.x

Wilson, J. (2010). Essentials of business research: A guide to doing your research project. Sage.

Xiong, Y., So, H. J., & Toh, Y. (2015). Assessing learners’ perceived readiness for computer-supported collaborative learning (CSCL): A study on initial development and validation. Journal of Computing in Higher Education, 27(3), 215-239. https://doi.org/10.1007/s12528-015-9102-9

Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91. https://doi.org/10.1006/ceps.1999.1016