Systematic Reviews and Meta Analysis
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Kitlesel Açık Çevrimiçi Ders Ortamlarında öğrenci katılımı nasıl geliştirilebilir?

Year 2022, , 176 - 206, 31.12.2022
https://doi.org/10.52911/itall.1194260

Abstract

Günümüzde artan nüfus, günlük, sosyal, eğitim ve iş yaşamındaki beklenen yeterliklerin değişmesiyle birlikte sürekli eğitim ihtiyacı ve bunun bir sonucu olarak hayat boyu öğrenmenin önemin artması gibi faktörler eğitim ortamlarının çeşitlenmesini beraberinde getirmiştir. Bu artan ihtiyacı karşılamaya dönük özellikle zaman ve mekan konusunda sınırlılıkları bireyler için kitlesel açık çevrimiçi dersler ve uzaktan eğitim ortamları büyük kolaylık sağlamaktadır. Ancak literatürde kitlesel açık çevrimiçi ortamlarda sıklıkla kursu tamamlayamama ve düşük katılım gibi olumsuz durumlar belirtilmiştir. Kitlesel açık çevrimiçi derslerde öğrenci katılımı ile ilgili çok sayıda çalışma vardır. Bu konuyla ilgili sistematik çalışmaların odak noktası bu gibi ortamlarda öğrenci katılımı önündeki engeller ve karşılaşılan zorluklardır. Bu çalışmada ise odak noktamız öğrenci katılımını etkileyen faktörleri (içsel, dışsal) sistematik bir bakış açısı ile almaktır. Buradan yola çıkarak Web of Science veri tabanında yer alan kitlesel açık çevrimiçi dersler ve öğrenci katılımı başlıklarını içeren 100 çalışma incelenmiştir. Kitlesel açık çevrimiçi ortamlarda öğrenci katılımını etkileyen içsel faktörlerde öne çıkan faktörler motivasyon, öz yeterlik, işbirliği ve sadakattir. Öne çıkan dışsal faktörler ise etkileşim, oyunlaştırma, geribildirim, kurs yapısı ve tasarımıdır.

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How can student engagement be improved in Massive Open Online Courses?

Year 2022, , 176 - 206, 31.12.2022
https://doi.org/10.52911/itall.1194260

Abstract

Today, factors such as the increasing population, the change in expected competencies in daily, social, education, and business life, the need for continuous education, and the increase in the importance of lifelong learning have brought about the diversification of educational environments. Massive open online courses and distance education environments provide great convenience, especially for individuals with limited time and space to meet this increasing need. However, in the literature, negative situations such as the inability to complete the course and low attendance are frequently reported in massive open online settings. There are numerous studies of student engagement in massive open online courses. The focus of systematic studies on this topic is the barriers and challenges to student engagement in such settings. In this study, we focus on the factors (internal and external) affecting student engagement from a systematic perspective. Starting from this, we reviewed 100 studies concentrated on massive open online courses and student engagement in the Web of Science database. The prominent internal factors affecting student engagement in massive open online environments are motivation, self-efficacy, cooperation, and loyalty. The principal external factors are interaction, gamification, feedback, course structure, and design.

References

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  • Alamri, M. M. (2022). Investigating Students’ Adoption of MOOCs during COVID-19 Pandemic: Students’ Academic Self-Efficacy, Learning Engagement, and Learning Persistence. Sustainability, 14(2), 714.
  • Alemayehu, L., & Chen, H.-L. (2021). Learner and instructor-related challenges for learners’ engagement in MOOCs: A review of 2014–2020 publications in selected SSCI indexed journals. Interactive Learning Environments, 1-23.
  • Alexandron, G., Wiltrout, M. E., Berg, A., Gershon, S. a. K., & Ruipérez‐Valiente, J. A. (2022). The effects of assessment design on academic dishonesty, learner engagement, and certification rates in MOOCs. Journal of Computer Assisted Learning.
  • Alharbi, K., Alrajhi, L., Cristea, A.I., Bittencourt, I.I., Isotani, S., James, A. (2020). Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs. In: Kumar, V., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science(), vol 12149. Springer, Cham.
  • Amado-Salvatierra, H.R., Rizzardini, R.H. (2018). An Experience Using Educational Data Mining and Machine Learning Towards a Full Engagement Educational Framework. In: Uden, L., Liberona, D., Ristvej, J. (eds) Learning Technology for Education Challenges. LTEC 2018. Communications in Computer and Information Science, vol 870. Springer, Cham.
  • Anderson, A., Huttenlocher, D., Kleinberg, J., & Leskovec, J. (2014). Engaging with massive online courses. Proceedings of the 23rd international conference on World wide web. Seoul, Korea.
  • Antonaci, A., Klemke, R., Lataster, J., Kreijns, K., Specht, M. (2019). Gamification of MOOCs Adopting Social Presence and Sense of Community to Increase User’s Engagement: An Experimental Study. In: Scheffel, M., Broisin, J., Pammer-Schindler, V., Ioannou, A., Schneider, J. (eds) Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science(), vol 11722. Springer, Cham.
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  • Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., & Seaton, D. T. (2013). Studying learning in the worldwide classroom research into edX's first MOOC. Research & Practice in Assessment, 8, 13-25.
  • Bote Lorenzo, M. L., & Gómez Sánchez, E. (2018). An approach to build in situ models for the prediction of the decrease of academic engagement indicators in Massive Open Online Courses.
  • Buchem, I., Carlino, C., Amenduni, F., & Poce, A. (2020). Meaningful gamification in MOOCs. Designing and examining learner engagement in the Open Virtual Mobility Learning Hub. Proceedings of the 14th International Technology, Education and Development Conference. Valencia, Spain.
  • Calik, M., & Sözbilir, M. (2014). Parameters of content analysis. Egitim Ve Bilim-Education and Science, 39(174).
  • Casson, F., Salter, M., & Hejmadi, M. (2017). What factors influence learner engagement with futurelearn moocs? A case study from bath. 9th International Conference on Education and New Learning Technologies. Barcelona, Spain.
  • Cheng, Y.-M. (2022). Which quality determinants cause MOOCs continuance intention? A hybrid extending the expectation-confirmation model with learning engagement and information systems success. Library Hi Tech(ahead-of-print).
  • Crosslin, M., Dellinger, J. T., Joksimovic, S., Kovanovic, V., & Gaševic, D. (2018). Customizable Modalities for Individualized Learning: Examining Patterns of Engagement in Dual-Layer MOOCs. Online Learning, 22(1), 19-38.
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Details

Primary Language English
Subjects Other Fields of Education
Journal Section Research Articles
Authors

Ahmet Uçar 0000-0002-9401-3034

Mustafa Sarıtepeci 0000-0002-6984-0652

Publication Date December 31, 2022
Submission Date October 25, 2022
Acceptance Date December 11, 2022
Published in Issue Year 2022

Cite

APA Uçar, A., & Sarıtepeci, M. (2022). How can student engagement be improved in Massive Open Online Courses?. Instructional Technology and Lifelong Learning, 3(2), 176-206. https://doi.org/10.52911/itall.1194260

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