Factors Affecting a Medical Faculty’s Engagement in Virtual Learning Environments

Document Type: Original Article

Authors

1 Department of Educational Management, School of Economy and Management, Islamic Azad University, Shiraz, Iran

2 Department of e-Learning in medical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

10.5812/ijvlms.2020.88894.1065

Abstract

Background: This study aimed to investigate the intrinsic and extrinsic factors affecting faculty engagement in virtual learning environments at Shiraz University of Medical Sciences (SUMS) in Shiraz, Iran. Methods: In this comparative study, 112 eligible faculty members at SUMS were enrolled in 2018-2019 academic year. The sample was surveyed by a researcher-made questionnaire consisting of 28 items, including 17 questions on intrinsic factors (familiarity with e-learning, faculty attitudes and human resources) and 11 on extrinsic factors (financial resources, inherent barriers, infrastructural factors and institutional support). The reliability of the research instrument, as measured by internal consistency and Cronbach’s alpha, stood at 0.92. It was measured at 0.87 and 0.92 for extrinsic and intrinsic factors respectively. The CVR and CVI values were found to be 0.6 and 0.8 respectively. One-sample t-test was applied to compare the mean scores of the intrinsic and extrinsic factors with the hypothetical mean, and to determine the ranking of the factors. Results: In order of their impact, the intrinsic and extrinsic factors included inadequate financial resources (P=0.566) lack of familiarity with electronic learning (p <0.001), inherent barriers such as institutional disbelief in the complementary role of e-learning (P=0.001), infrastructural factors (p <0.001), faculty attitudes (p <0.001), inadequate human resources (p <0.001), and lack of institutional support (p <0.001). Conclusion: University administrators should provide educators with adequate resources for handling new educational environments, remove administrative and structural obstacles, and create motivation among faculty members to use e-learning systems.

Keywords


Sim TY, Lau SL, Zipf P, Kimm K. Design and development of a supported tiered software for teaching and learning using a connected mobile learning application. World Applied Sciences Journal. 2014;30(1):247-55. DOI: 10.5829/idosi.wasj.2015.30.icmrp.32
Khasawneh R, Simonsen K, Snowden J, Higgins J, Beck G. The effectiveness of e-learning in pediatric medical student education. Medical education online. 2016 Jan 1;21(1):29516. doi: 10.3402/meo.v21.29516.
Ertmer, P.A., Richardson, J.C., Belland, B., Camin, D., Connolly, P., Coulthard, G., Lei, K. and Mong, C., 2007. Using peer feedback to enhance the quality of student online postings: An exploratory study. Journal of Computer-Mediated Communication, 12(2), pp.412-433. https://doi.org/10.1111/j.1083-6101.2007.00331.x
Coopasami M, Knight S, ́ Pete M. e-Learning readiness amongst nursing students at the Durban University of Technology. health sa gesondheid. 2017;22(1):300-6. https://doi.org/10.1016/j.hsag.2017.04.003
Drent M, Meelissen M. Which factors obstruct or stimulate teacher educators to use ICT innovatively?. Computers & Education. 2008 Aug 1;51(1):187-99. DOI: 10.1016/j.compedu.2007.05.001
Valdez G. Technology: A catalyst for teaching and learning in the classroom. Retrieved, Feb. 2005;9:2014.
Wang Q. A generic model for guiding the integration of ICT into teaching and learning. Innovations in education and teaching international. 2008 Nov 1;45(4):411-9. DOI: 10.1080/14703290802377307
Nazeri N, Dorri S, Atashi A. The Effective Factors on Success of E-learning in Medical Sciences Fields. Journal of Health and Biomedical Informatics. 2017; 4 (2) :98-107 URL: http://jhbmi.ir/article-1-218-fa.html
Roodsaz H., Kamalian AR, Amiri M, Ghaemmagami Tabrizi A. Identifying the Factors Affecting the Pattern of Virtual Vocational Education in Iran, Research in Educational Systems, 2017; 11(36): 121-144. DOI: 10.22034/jiera.2017.51088
Kumar N, Rose RC, D’Silva JL. Teachers’ readiness to use technology in the classroom: An empirical study. European Journal of Scientific Research. 2008;21(4):603-16.
Anthoine E, Moret L, Regnault A, Sébille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health and quality of life outcomes. 2014 Dec;12(1):1-0. doi:10.1186/s12955-014-0176-2
Hope J, Hope T. Competing in the third wave: the ten key management issues of the information age. Harvard Business Press; 1997.
Sife A, Lwoga E, Sanga C. New technologies for teaching and learning: Challenges for higher learning institutions in developing countries. International journal of education and development using ICT. 2007 Jun 13;3(2):57-67.
Panda S, Mishra S. E‐Learning in a Mega Open University: Faculty attitude, barriers and motivators. Educational Media International. 2007 Dec 1;44(4):323-38. https://doi.org/10.1080/09523980701680854
Oomen-Early J, Murphy L. Self-actualization and e-learning: A qualitative investigation of university faculty’s perceived barriers to effective online instruction. International Journal on E-Learning. 2009 Apr;8(2):223-40.
Tedre M, Ngumbuke F, Kemppainen J. Infrastructure, human capacity, and high hopes: A decade of development of e-Learning in a Tanzanian HEI. RUSC. Universities and Knowledge Society Journal. 2010;7(1):7-20.
Alsabawy AY, Cater-Steel A, Soar J. IT infrastructure services as a requirement for e-learning system success. Computers & Education. 2013 Nov 1;69:431-51. https://doi.org/10.1016/j.compedu.2013.07.035
Muñoz Carril PC, González Sanmamed M, Hernández Sellés N. Pedagogical roles and competencies of university teachers practicing in the e-learning environment. International Review of Research in Open and Distributed Learning. 2013;14(3):462-87. https://doi.org/10.19173/irrodl.v14i3.1477