فصلنامه پژوهش و برنامه ریزی در آموزش عالی

مدل آمادگی یادگیری الکترونیکی دانشگاه‌ها در مواجه بیماری کووید 19 (مورد: دانشگاه تهران)

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه تهران

10.61838/irphe.29.1.3

چکیده

پژوهش پیش رو با هدف طراحی مدلی برای آمادگی یادگیری الکترونیکی دانشگاه تهران در مواجهه با بیماری کووید 19 انجام شده است. نوع آن کاربردی است و با روش پدیدارشناسی و توزیع پرسشنامه بازپاسخ در میان 603 نفر از اعضای هیئت‌علمی شاغل در 36 دانشکدۀ دانشگاه تهران به‌صورتِ ارسال ایمیل و نیز گرفتن تماس‌های صوتی و تصویری صورت گرفته است. اعتبار و روایی آن با سه اقدام و از طریق بازبینی توسط مشارکت‌کنندگان احصاءشد. مدلی متشکل از 8 عنصر فرعی با تحلیل محتوای استقرایی و کدگذاری باز و مقوله‌بندی اصلی معرفی گردید: توسعۀ فرآیندهای یاددهی-یادگیری، مدیریت زمان، غنی‌سازی محتوای آموزشی، استمرار در آموزش، برقراری عدالت آموزشی، ارتقای مسئولیت‌پذیری اجتماعی دانشگاه، تداوم و توسعه آموزش و یادگیری الکترونیکی، بهبود نظارت و ارزیابی کلاس. به عبارت دیگر، گسترش یادگیری الکترونیکی به عنوان رویکردی نو در آموزش عالی مستلزم ایجاد چهار آمادگی اجتماعی-فرهنگی، آمادگی پداگوژیکی، آمادگی سازمانی و آمادگی فناوری در پیوند با مدل اصلاح شده بلوم است. هم‌افزایی این عناصر در شرایط کنونی دانشگاه ها را می‌توان به منزلۀ راهبردی برای یادگیری در نظر گرفت که برای بهبود مستمر یادگیری الکترونیکی در دوران شیوع بیماری کووید 19 لازم و ضروری است. لذا، پیشنهادهای این پژوهش را می‌توان برای دانشگاه‌ها به‌کار برد.

کلیدواژه‌ها

عنوان مقاله [English]

A Model of E-learning readiness of universities in the face of Corvid 19 disease (Case: University of Tehran)

نویسندگان [English]

  • Javad Pourkarimi
  • Fatemeh Ordoo

University of Tehran

چکیده [English]

The present study aimed at designing a model for E-learning readiness of the University of Tehran in the face of Covid 19 disease. This study is applied and has been done by phenomenological method and answering an Open Answer Questionnaire from 603 faculty members among 36 faculties of the University of Tehran by sending e-mails and also by voice and video calls. Its validity was assessed by the participants through three measures and through review. A model consisting of 8 sub-elements with inductive content analysis and open coding and main categorization was introduced; Development of teaching-learning processes, time management, enrichment of educational content, continuity of education, establishment of educational justice, promotion of social responsibility of the university, continuation and development of e-learning and teaching, improving classroom supervision and evaluation. In other words, the development of e-learning as a new approach in higher education requires the creation of four socio-cultural readiness, pedagogical readiness, organizational readiness and technological readiness in conjunction with the revised Bloom model; The combination of these elements in the current situation of universities can be considered as a strategy for learning that is necessary for the continuous improvement of e-learning during the outbreak of Covid 19 pandemic. Therefore, the suggestions of this research can be applied to universities.

کلیدواژه‌ها [English]

  • Covid 19 disease
  • E-learning model
  • University of Tehran
  1. Abdellahi M, Zamani B E, 1Ebrahim Zadeh I, Zaree H, Zandi B.(2011) “Barriers to Participation in Electronic Technology Courses Encountered by University Teachers”. IRPHE,16 (2):19-40 [in Persian].
  2. Al-Hamad, N. Q., AlHamad, A. Q., & Al-Omari, F. A. (2020). “Smart devices employment in teaching and learning: reality and challenges in Jordan universities”. Smart Learning Environments, 7(1), 1-15.
  3. Anderson, L. W., & Bloom, B. S. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. Longman.
  4. Ausubel, D. P. (1968). The psychology of meaningful learning; An introduction to school learning. Grune and Stratton.
  5. Ayebi-Arthur, K. (2017). “E-learning, resilience and change in higher education: Helping a university cope after a natural disaster”. E-Learning and Digital Media, 14(5), 259-274.
  6. Bloom, B. S. (1956). Engelhart, MD, Furst, EJ, Hill, WH, & Krathwohl, DR. Taxonomy of educational objectives: Handbook I: Cognitive domain.
  7. Castleberry, D., & Brandt, S. R. (2016). The Effect of Question Ordering Using Bloom's Taxonomy in an e-Learning Environment. In International Conference on Computer Science Education Innovation & Technology (CSEIT). Proceedings(p. 22). Global Science and Technology Forum.
  8. Creswell, J. W. (2012). Educational research: planning. Conducting, and Evaluating [No.?].
  9. Dewan, M. A. A., Murshed, M., & Lin, F. (2019). “Engagement detection in online learning: a review”. Smart Learning Environments, 6(1), 1.
  10. Dhawan, S. (2020). “Online learning: A panacea in the time of COVID-19 crisis”. Journal of Educational Technology Systems, 49(1), 5-22.
  11. Dickinson, K. J., & Gronseth, S. L. (2020). Application of Universal Design for Learning (UDL) Principles to Surgical Education during the COVID-19 Pandemic: UDL for surgical education during COVID-19. Journal of Surgical Education [No.?].
  12. Dron, J. (2018). “Smart learning environments, and not so smart learning environments: a system view”. Smart Learning Environments, 5(1), 1-20.
  13. Elahi S, Kanaani F, Shayan A.(2011) Designing a Framework for Effective Factors on Virtual Students’ Tendency to the Electronic Learning and its Assessment. IRPHE, 17 (2) :59-80 [in Persian].
  14. Franchi, T. (2020). “The Impact of the Covid‐19 Pandemic on Current Anatomy Education and Future Careers: A Student’s Perspective”. Anatomical Sciences Education, 13(3), 312-315.
  15. Freigang, S., Schlenker, L., & Köhler, T. (2018). “A conceptual framework for designing smart learning environments”. Smart Learning Environments, 5(1), 27.
  16. Hsieh, H. F., & Shannon, S. E. (2005). “Three approaches to qualitative content analysis”. Qualitative health research, 15(9), 1277-1288.
  17. Hubalovsky, S., Hubalovska, M., & Musilek, M. (2019). “Assessment of the influence of adaptive E-learning on learning effectiveness of primary school pupils”. Computers in Human Behavior, 92, 691-705.
  18. Köğce, D., Aydın, M., & Yıldız, C. (2009). Krathwohl, DR (2002). “A revision of bloom's taxonomy: An overview”. Theory into Practice, 41 (4), 212-218. Elementary Education Online, 8(3).
  19. Krathwohl, D. R. (2002). “A revision of Bloom's taxonomy: An overview”. Theory into practice, 41(4), 212-218.
  20. Lau, K. H., Lam, T. K., Kam, B. H., Nkhoma, M., & Richardson, J. (2018). “Benchmarking higher education programs through alignment analysis based on the revised Bloom’s taxonomy”. Benchmarking: An International Journal.[No.?]
  21. Martens, A., Sandkuhl, K., Lantow, B., Lehmann, H., Lettau, W. D., & Radisch, F. (2019). “An evaluation approach for smart support of teaching and learning processes”. Smart Learning Environments, 6(1), 2.
  22. Mirabi, M., Amini, Z., Jaafari, D., Jebeli, I., Fazli, H., Ezami, F., Maniee, R. (2019). Higher Education Statistics of Iran Academic Year 2017-2018. Tehran: Institute of Research and Planning in Higher Education [in Persian].
  23. Mousavi M., Mohammadzadeh Nasrabadi M., Pezeshki-Rad G.R. “Identifying and Analyzing Barrier and Inhibitor Factors for Implementation and Development of E-learning in Payame Noor University”. IRPHE. 2011; 17 (1) :137-154 [in Persian].
  24. Nili Ahmadabadi, M. (2020). Ministry of Science, Research and Technology. Retrieved from https://b2n.ir/705730 [in Persian].
  25. Paskevicius, M., & Irvine, V. (2019). “Practicalities of implementing open pedagogy in higher education”. Smart Learning Environments, 6(1), 23.
  26. Patton, M. Q. (2002). “Two decades of developments in qualitative inquiry: A personal, experiential perspective”. Qualitative social work, 1(3), 261-283.
  27. Radha, R., Mahalakshmi, K., Sathis Kumar, V., & Saravanakumar, A. R. (2020). “E-learning during lockdown of Covid-19 pandemic: a global perspective”. International journal of control and automation, 13(4), 1088-1099.
  28. Rohani, S., Mir Hosseini, S.V.(2014). “Designing an Agent-based Intelligent Teaching Assistant and Evaluating its Efficiency in e-Learning Portals”. IJVLMS, 5(3), 29-36 [in Persian].
  29. Selim, H. M. (2007). “Critical success factors for e-learning acceptance: Confirmatory factor models”. Computers & education, 49(2), 396-413.
  30. Sheth, S., Ganesh, A., Nagendra, S., Kumar, K., Tejdeepika, R., Likhitha, C., & Murthy, P. (2020). “Development of a mobile responsive online learning module on psychosocial and mental health issues related to COVID 19”. Asian Journal of Psychiatry [NO.?].
  31. Taghiyareh F. (2007). “Key Selection Criteria of E-learning Authoring Tools”. IRPHE. 2007; 13 (1) :75-89 [in Persian].
  32. Tatnall, A. (Ed.). (2020). Encyclopedia of Education and Information Technologies. Springer [in Persian].
  33. Tavangarian, D., Leypold, M. E., Nölting, K., Röser, M., & Voigt, D. (2004). “Is e-Learning the Solution for Individual Learning?” . Electronic Journal of E-learning, 2(2), 273-280.
  34. Torrau, S. (2020). Exploring Teaching and Learning about the Corona Crisis in Social Studies Webinars: A Case Study. Journal of Social Science Education, 19, 15-29.
  35. Wang, S. L., & Wu, P. Y. (2008). “The role of feedback and self-efficacy on web-based learning: The social cognitive perspective”. Computers & Education, 51(4), 1589-1598.
  36. Wang, Y., Li, T., Geng, C., & Wang, Y. (2019). “Recognizing patterns of student’s modeling behaviour patterns via process mining”. Smart Learning Environments, 6(1), 1-16.

 

فصلنامه پژوهش و برنامه ریزی در آموزش عالی
دوره 29، شماره 1 - شماره پیاپی 107
خرداد 1402
صفحه 53-77