Technology Acceptance of Navid Learning Management System in the Iranian Medical English Courses under the COVID-19 Pandemic

Document Type : Research Paper

Authors

1 Associate Professor of Applied Linguistics, Faculty of Humanities, Razi University, Kermanshah, Iran.

2 Assistant Professor of Applied Linguistics, Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

3 PhD candidate of Applied Linguistics, Faculty of Humanities, Razi University, Kermanshah, Iran

10.22034/elt.2021.42131.2296

Abstract

This mixed-method study endeavored to solicit the perspectives of Iranian collegiate students passing the obligatory course of medical English through Navid Learning Management System and its acceptance during COVID-19 pandemic. Utilizing Technology Acceptance Model, this study also sought to examine the possible effect gender, academic degree, instructional mode, and e-learning duration in LMS may have on the participants' attitudes. An online survey was employed to gather data from 78 Iranian students. Semi-structured interviews with ten participants were conducted as well to shed more light on the quantitative data regarding main advantages and disadvantages of medical English learning through Navid. The data were analyzed through descriptive and inferential statistics along with inductive thematic analysis, respectively. Findings revealed that Iranian collegiate medical students viewed Navid as a comprehensive e-learning platform to be favorable in terms of its system/service quality, student/educational service quality, and perceived satisfaction, but its perceived satisfaction was not aligned with their needs. Moreover, neither the individual variables, (viz., age and academic degree), nor the instructional variables (viz., instructional mode and e-learning duration) were predictors of the discrepancies among the participants in their perspectives and acceptance of Navid. Learning ubiquitously and lacking face-to-face communication were the main advantage and disadvantage of learning medical English through Navid, respectively. Results revealed that although under the Covid-19 pandemic the acceptance of Navid and students' satisfaction with its use might not be related to the individual and instructional variables in the medical English courses, it might not be the case in others.

Keywords


Article Title [فارسی]

میزان پذیرش سامانه مدیریت آموزشی نوید در کلاس‌های انگلیسی پزشکی ایران در زمان شیوع ویروس کوید 19

Authors [فارسی]

  • سامان عبادی 1
  • سعید خزائی 2
  • صبا بشیری 3
1 دانشیار زبانشناسی کاربردی، دانشکده علوم انسانی، دانشگاه رازی، کرمانشاه، ایران.
2 استادیار زبانشناسی کاربردی، مرکز تحقیقات فناوری اطلاعات سلامت، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران.
3 دانشجوی دکتری زبانشناسی کاربردی، دانشکده علوم انسانی، دانشگاه رازی، کرمانشاه، ایران.
Abstract [فارسی]

این پژوهش ترکیبی با هدف آگاهی از نگرش و برداشت دانشجویان ایرانی در پذیرش سامانه‌ی مدیریت آموزشی نوید در کلاس‌های زبان انگلیسی پزشکی، به‌عنوان دو واحد اجباری، در زمان شیوع ویروس کوید 19 انجام شد. با کاربرد مدل پذیرش فناوری، این پژوهش به بررسی اثر احتمالی سن، جنسیت، سابقه حضور در دانشگاه و نرم‌افزارهای متفاوت یادگیری بر تغییر نگرش شرکت‌کنندگان نیز می‌پردازد. یک پرسشنامه‌ی برخط طراحی و آماده‌سازی شد تا نگرش 78 دانشجوی پزشکی ایرانی را جویا شود. برای تکمیل وجه کمی، با کاربرد یک مصاحبه‌ی نیمه ساختار یافته با حضور 10 نفر از شرکت‌کنندگان، برداشت آن‌ها از کاربردپذیری نوید در آموزش انگلیسی پزشکی به شکل کیفی ارزیابی شد. یافته‌های حاصل از انجام پژوهش از نگرش مطلوب شرکت‌کنندگان به کیفیت سامانه‌ی نوید و رضایت از این سامانه در تسهیل یادگیری انگلیسی پزشکی خبر داد، اما، رضایت از سامانه با نیازهای آن‌ها تطابق نداشت. هیچ‌کدام از متغیرهای فردی و آموزشی بر تفاوت برداشت شرکت‌کنندگان تأثیرگذار نبود. نبود امکان تعامل چهره به چهره عمده‌ترین عیب و یاددهی-یادگیری انگلیسی پزشکی در هر زمان و در هر مکان عمده‌ترین مزیت سامانه‌ی مدیریت آموزشی نوید بود. نتایج این پژوهش نسان داد اگرچه متغیرهای فردی و آموزشی بر پذیرش سامانه‌ی مدیریت آموزشی نوید در دوره‌ی یاددهی-یادگیری انگلیسی پزشکی مؤثر بود، اما ممکن است در دیگر دوره‌های آموزش پزشکی این‌گونه نباشد.

Keywords [فارسی]

  • انگلیسی پزشکی
  • سامانه‌ی مدیریت آموزشی
  • مدل پذیرش فناوری
  • نوید
Adams, D., Sumintono, B., Mohamed, A., & Noor, N. S. M. (2018). E-learning readiness among students of diverse backgrounds in a leading Malaysian higher education institution. Malaysian Journal of Learning and Instruction15(2), 227-256.
Afacan Adanır, G., Muhametjanova, G., Çelikbağ, M. A., Omuraliev, A., & Ismailova, R. (2020). Learners' preferences for online resources, activities, and communication tools: A comparative study of turkey and kyrgyzstan. E-Learning and Digital Media17(2), 148-166. 
Al Lily, A. E., Ismail, A. F., Abunasser, F. M., & Alqahtani, R. H. A. (2020). distance education as a response to pandemics: Coronavirus and arab culture. Journal of Educational Technology, 49(1), 5-22.
Al-Araibi, A. A. M., Naz'ri Bin Mahrin, M., & Yusoff, R. C. M. (2019). Technological aspect factors of e-learning readiness in higher education institutions: Delphi technique. Education and Information Technologies24(1), 567-590.
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior102, 67-86.
Alhabeeb, A., & Rowley, J. (2018). E-learning critical success factors: Comparing perspectives from academic staff and students. Computers and Education127, 1-12.
Ali, S., Uppal, M. A., & Gulliver, S. R. (2018). A conceptual framework highlighting e-learning implementation barriers. Information Technology and People, 31(1),156-180.
Al-Samarraie, H., Teng, B. K., Alzahrani, A. I., & Alalwan, N. (2017). E-learning continuance satisfaction in higher education: A unified perspective from instructors and students. Studies in Higher Education43(11), 1-17.
Aubusson, P., Burke, P., Schuck, S., Kearney, M., & Frischknecht, B. (2014). Teachers choosing rich tasks: The moderating impact of technology on student learning, enjoyment, and preparation. Educational Researcher43(5), 219-229.
Bailey, D. R., & Lee, A. R. (2020). Learning from experience in the midst of COVID-19: Benefits, challenges, and strategies in online teaching. CALL-EJ 21(2), 178-198.
Bigirwa, J. P., Ndawula, S., & Naluwemba, E. F. (2020). E-learning adoption: Does the instructional design model matter? An explanatory sequential study on midwifery schools in Uganda. E-Learning and Digital Media, 1-22.
Crompton, H., Burke, D., & Gregory, K. H. (2017). The use of mobile learning in PK-12 education: A systematic review. Computers and Education110, 51-63.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
De Smet, C., Bourgonjon, J., De Wever, B., Schellens, T., & Valcke, M. (2012). Researching instructional use and the technology acceptation of learning management systems by secondary school teachers. Computers and Education58(2), 688-696.
Demuyakor, J. (2020). Coronavirus (COVID-19) and online learning in higher institutions of education: A survey of the perceptions of Ghanaian international students in China. Online Journal of Communication and Media Technologies10(3), e202018.
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5-22.
Dönmez-Turan, A., & Kır, M. (2019). User anxiety as an external variable of technology acceptance model: A meta-analytic study. Procedia Computer Science158, 715-724.
Farhan, W., Razmak, J., Demers, S., & Laflamme, S. (2019). E-Learning systems versus instructional communication tools: Developing and testing a new e-learning user interface from the perspectives of teachers and students. Technology in Society59, 101192.
Fishbein, M., & Ajzen, I. (1976). Misconceptions about the Fishbein model: Reflections on a study by Songer-Nocks. Journal of Experimental Social Psychology12(6), 579-584.
Fita, A., Monserrat, J. F., Moltó, G., Mestre, E. M., & Rodriguez‐Burruezo, A. (2016). Use of synchronous e‐learning at University Degrees. Computer Applications in Engineering Education24(6), 982-993.
Fonseca, D., Martí, N., Redondo, E., Navarro, I., & Sánchez, A. (2014). Relationship between student profile, tool use, participation, and academic performance with the use of augmented reality technology for visualized architecture models. Computers in Human Behavior31, 434-445.
Fryer, L. K., Bovee, H. N., & Nakao, K. (2014). E-learning: Reasons students in language learning courses don't want to. Computers and Education, 74, 26-36.
Gamble, C. (2018). Exploring EFL university students' acceptance of e-learning using TAM. Kwansei Gakuin University Humanities Review22, 23-37.
Ghapanchi, A. H., & Aurum, A. (2011). The impact of project license and operating system on the effectiveness of the defect-fixing process in open-source software projects. International Journal of Business Information Systems, 8(4), 413–424.
González-Gómez, F., Guardiola, J., Rodríguez, Ó. M., & Alonso, M. Á. M. (2012). Gender differences in e-learning satisfaction. Computers and Education58(1), 283-290.
Guri-Rosenblit, S., & Gros, B. (2011). E-learning: Confusing terminology, research gaps and inherent challenges. International Journal of E-Learning and Distance Education, 25(1). 1-17.
Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. Educause Review27.
Houshmandi, S., Rezaei, E., Hatami, J., & Molaei, B. (2019). E-learning readiness among faculty members of medical sciences universities and provide strategies to improve it. Research and Development in Medical Education8(2), 105-112.
Islam, M. A., Abdul Rahim, N. A., Liang, T. C., & Momtaz, H. (2011). Effect of demographic factors on e-learning effectiveness in a higher learning institution in Malaysia. International Education Studies, 4(1), 112-121.
Jiang, D., & Zhang, L. J. (2020). Collaborating with familiar strangers in mobile-assisted environments: The effect of socializing activities on learning EFL writing. Computers and Education150, 103841.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model. Technology in Society60, 101212.
Kanwal, F., & Rehman, M. (2017). Factors affecting e-learning adoption in developing countries–empirical evidence from Pakistan's higher education sector. IEEE Access5, 10968-10978.
Karkar, A. J., Fatlawi, H. K., & Al-Jobouri, A. A. (2020). Highlighting e-learning adoption challenges using data analysis techniques: University of Kufa as a case study. Electronic Journal of e-Learning18(2), 136-149.
Kerimbayev, N., Kultan, J., Abdykarimova, S., & Akramova, A. (2017). LMS Moodle: Distance international education in cooperation of higher education institutions of different countries. Education and Information Technologies22(5), 2125-2139.
Kerimbayev, N., Nurym, N., Akramova, А., & Abdykarimova, S. (2020). Virtual educational environment: Interactive communication using LMS Moodle. Education and Information Technologies25(3), 1965-1982.
Khazaie, S., Torabi, R., & Saghaee, A. (2020).  Exploring the viability of augmented reality-based cognitive therapy of low working memory in English for medical purposes comprehension and performance. In Proceedings of the 5th International Conference on Computer Games; Challenges and Opportunities 2020 February 19. University of Isfahan. http://cgco2020.ui.ac.ir/fa/
Kite, J., Schlub, T. E., Zhang, Y., Choi, S., Craske, S., & Dickson, M. (2020). Exploring lecturer and student perceptions and use of a learning management system in a postgraduate public health environment. E-Learning and Digital Media17(3), 183-198.
Koh, J. H. L., & Kan, R. Y. P. (2020). Perceptions of learning management
system quality, satisfaction, and usage: Differences among students of the arts. Australasian Journal of Educational Technology, 26-40.
Kumar Basak, S., Wotto, M., & Belanger, P. (2018). E-learning, m-learning and d-learning: Conceptual definition and comparative analysis. E-Learning and Digital Media15(4), 191-216.
Kurt, Ö. E. (2019). Examining an e-learning system through the lens of the information systems success model: Empirical evidence from Italy. Education and Information Technologies24(2), 1173-1184.
Lai, C., Zhu, W., & Gong, G. (2015). Understanding the quality of out‐of‐class English learning. TESOL Quarterly49(2), 278-308.
Lau, C. Y., & Shaikh, J. M. (2012). The impacts of personal qualities on online learning readiness at Curtin Sarawak Malaysia (CSM). Educational Research and Reviews, 7(20), 430-444.
Levy, M., & Stockwell, G. (2013). CALL dimensions: Options and issues in computer-assisted language learning. London: Routledge.
Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers and Education58(1), 88-99.
Luo, H., & Yang, C. (2018). Twenty years of telecollaborative practice: Implications for teaching Chinese as a foreign language. Computer Assisted Language Learning31(5-6), 546-571.
Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. San Francisco: Jossey-Bass.
Moghavvemi, S., & Salarzadeh Janatabadi, H. (2018). Incremental impact of time on students' use of e‐learning via facebook. British Journal of Educational Technology49(3), 560-573.
Murphy, M. P. (2020). COVID-19 and emergency e-learning: Consequences of the securitization of higher education for post-pandemic pedagogy. Contemporary Security Policy, 41(3), 1-14.
Naresh, B., Reddy, B. S., & Pricilda, U. (2016). A study on the relationship between demographic factor and e-learning readiness among students in higher education. Sona Global Management Review, 10(4), 1-11.
Patricia, A. (2020). College students' use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1-33.
Rashid, T., & Asghar, H. M. (2016). Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior63, 604-612.
Rentler, B. R., & Apple, D. (2020). Understanding the acceptance of e-learning in a Japanese university English program using the technology acceptance model. APU Journal of Language Research5, 22-37.
Rizun, M., & Strzelecki, A. (2020). Students' acceptance of the COVID-19 impact on shifting higher education to distance learning in Poland. International Journal of Environmental Research and Public Health17(18), 1-19.
Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies64(8), 683-696.
Rodrigues, H., Almeida, F., Figueiredo, V., & Lopes, S. L. (2019). Tracking e-learning through published papers: A systematic review. Computers and Education136, 87-98.
Saba, T. (2012). Implications of e-learning systems and self-efficiency on students' outcomes: A model approach. Human-Centric Computing and Information Sciences2(1), 1-11.
Salloum, S. A., & Shaalan, K. (2018, September). Factors affecting students' acceptance of e-learning system in higher education using UTAUT and structural equation modeling approaches. In International Conference on Advanced Intelligent Systems and Informatics (pp. 469-480). London: Springer.
Sangrà, A., Vlachopoulos, D., & Cabrera, N. (2012). Building an inclusive definition of e-learning: An approach to the conceptual framework. International Review of Research in Open and Distance Learning, 13(2), 145–159.
Sarker, M. F. H., Al Mahmud, R., Islam, M. S., & Islam, M. K. (2019). Use of e-learning at higher educational institutions in Bangladesh. Journal of Applied Research in Higher Education11(2), 210-223.
Sethi, A., Wajid, A., & Khan, A. (2019). eLEARNING. The Professional Medical Journal26(4), 632-638.
Smith, E., Lye, P., Greatrex, B., Taylor, M., & Stupans, I. (2013). Enriching learning for first year chemistry students: introduction of Adobe Connect. European Journal of Open, Distance and E-learning16(1), 94-101.
Sun, P. P., & Mei, B. (2020). Modeling pre-service Chinese-as-a-second/foreign-language teachers' adoption of educational technology: A technology acceptance perspective. Computer Assisted Language Learning, 1-24.
Tang, C. M., & Bradshaw, A. (2020). Instant messaging or face-to-face? How choice of communication medium affects team collaboration environments. E-Learning and Digital Media17(2), 111-130.
Teo, T. (2011). Factors influencing teachers' intention to use technology: Model development and test. Computers and Education, 57(4), 2432–2440.
UNESCO. (2020, Match 13). COVID19 educational disruption and response. Retrieved from https://en.unesco.org/covid19/educationresponse
Wang, C., & Zhao, H. (2020). The impact of COVID-19 on anxiety in Chinese university students. Frontiers in Psychology11, 1168, 1-18.
Weeden, K. A., & Cornwell, B. (2020). The small-world network of college classes: Implications for epidemic spread on a university campus. Sociological Science7, 222-241.
Win, N. L., & Wynn, S. D. (2015). Introducing blended learning practices in our classrooms. Journal of Institutional Research in South East Asia, 12(2), 17-27.
Yanga, J. Y., & Yenb, Y. C. (2016). College students' perspectives of e-learning system use in high education. Asian Journal of Education and Training2(2), 53-62.
Zaneldin, E., Ahmed, W., & El-Ariss, B. (2019). Video-based e-learning for an undergraduate engineering course. E-Learning and Digital Media16(6), 475-496.
Zourou, K., & Potolia, A. (2021). Openness in a crowd-sourced massive online language community. Open Education and Second, 87.