Assessment and Feedback Practices in MOOCs: A Systematic Literature Review of 2023–2025 Studies
Keywords:
Massive Open Online Courses, assessment and feedback, automated assessment, learning analytics
Abstract
This study aims to synthesize the latest empirical evidence regarding assessment and feedback practices in Massive Open Online Courses (MOOCs) through the Systematic Literature Review (SLR) approach that follows the PRISMA guidelines. The identification process was carried out using the Scopus database with keywords related to MOOCs, assessments, and feedback, resulting in 514 initial articles. After going through the stages of screening, feasibility assessment, and selection based on the 2023–2025 publication year range, document type, language, access status, and file availability, as many as 29 articles met all inclusion criteria. Analysis of these articles shows that assessment in MOOCs is evolving towards an automated, adaptive, and data-driven approach, with the use of automated quizzes, adaptive assessments, peer assessments, and learning analytics. On the other hand, feedback mechanisms show significant transformation through the integration of generative artificial intelligence technology and learning analytics that provide fast, relevant, and personalized feedback at massive scale. The results of the synthesis also revealed that good evaluation design consistently increases the motivation, engagement, and learning outcomes of MOOC participants, while a number of challenges such as peer assessment bias, evaluation design complexity, and technological barriers still need to be considered. Overall, this study confirms that assessment and feedback are key components that determine the quality of learning in MOOCs and contribute greatly to the effectiveness of learning processes and outcomes when designed in a systematic, adaptive, and participant-oriented manner.
References
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Qi, X., Sun, G., & Yue, L. (2023). Applying Self-Optimised Feedback to a Learning Management System for Facilitating Personalised Learning Activities on Massive Open Online Courses. Sustainability (Switzerland), 15(16), 0–21. https://doi.org/10.3390/su151612562
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Sarilita, E., Rafisa, A., Desai, P., & Mossey, P. A. (2024). Utilising massive open online courses to enhance global learning dissemination in cleft lip and palate: a case report of penta helix collaboration. BMC Medical Education, 24(1), 1–8. https://doi.org/10.1186/s12909-024-05225-4
Selvaraj, R., Kuthadi, V., Baskar, S., & Acevedo, R. (2025). Exploring Motivation and Learning Factors in Digital Media Through the Lens of Activity Theory and Behavioural Influences. Indian Journal of Information Sources and Services, 15(3), 37–47. https://doi.org/10.51983/ijiss-2025.IJISS.15.3.05
Sriwisathiyakun, K. (2024). A MOOC-Integrated Design Thinking Model For Hearing-Impaired Learners. Journal of Information Technology Education: Research, 23, 6–14.
Ulfa, S., Surahman, E., Wedi, A., Fatawi, I., & Bringula, R. (2025). An adaptive assessment: Online summary with automated feedback as a self-assessment tool in MOOCs environments. Knowledge Management and E-Learning, 17(1), 88–113. https://doi.org/10.34105/j.kmel.2025.17.004
Wang, Y., Nie, L., & Jian, H. (2023). Valuation and Analysis of Online Teaching Platforms in Post-pandemic Era. International Journal of Information and Education Technology, 13(2), 257–265. https://doi.org/10.18178/ijiet.2023.13.2.1803
Wei, W., Liu, J., Xu, X., Kolletar-Zhu, K., & Zhang, Y. (2023). Effective interactive engagement strategies for MOOC forum discussion: A self-efficacy perspective. PLoS ONE, 18(11 November), 1–15. https://doi.org/10.1371/journal.pone.0293668
Wiese-Posselt, M., Saydan, S., Lâm, T. T., Rörig, A., Bergmann, C., Becker, F., Kurzai, O., Feufel, M. A., Gastmeier, P., & Schneider, S. (2025). Development and evaluation of a massive open online course (MOOC) to teach medical students the prudent use of antibiotics. Antimicrobial Resistance and Infection Control, 14(1). https://doi.org/10.1186/s13756-025-01640-4
Zhilmagambetova, R., Kopeyev, Z., Mubarakov, A., & Alimagambetova, A. (2023). The Role of Adaptive Personalized Technologies in the Learning Process: Stepik as a Tool for Teaching Mathematics. International Journal of Virtual and Personal Learning Environments, 13(1), 1–15. https://doi.org/10.4018/IJVPLE.324079
Anitha, D., Jeyamala, C., Thiruvengadam, S. J., & Saravana Perumaal, S. (2023). An Experimental Journey with Self-Made Online Courses: How does it differ? Journal of Engineering Education Transformations, 36(Special Issue 2), 166–172. https://doi.org/10.16920/jeet/2023/v36is2/23023
Aung, K. T., Abdul Razak, R., & Zulkafley, M. F. (2024). Effectiveness of Massive Open Online Course on Risk Communication Knowledge in Global Health Emergencies Among Nurses. Jurnal Keperawatan Indonesia, 27(3), 165–174. https://doi.org/10.7454/jki.v27i3.1233
Boufaida, S. O., Benmachiche, A., Derdour, M., Maatallah, M., Kahil, M. S., & Ghanem, M. C. (2025). TSA-GRU: A Novel Hybrid Deep Learning Module for Learner Behavior Analytics in MOOCs. Future Internet, 17(8), 1–31. https://doi.org/10.3390/fi17080355
Chen, X., Xie, H., Tao, X., Wang, F. L., & Cao, J. (2024). Leveraging text mining and analytic hierarchy process for the automatic evaluation of online courses. International Journal of Machine Learning and Cybernetics, 15(11), 4973–4998. https://doi.org/10.1007/s13042-024-02203-6
Coad, B., Joekes, K., Rudnicka, A., Frost, A., Openshaw, M. R., Tatton-Brown, K., & Snape, K. (2023). Evaluation of two Massive Open Online Courses (MOOCs) in genomic variant interpretation for the NHS workforce. BMC Medical Education, 23(1), 1–12. https://doi.org/10.1186/s12909-023-04406-x
Coccoli, M., Torre, I., & Galluccio, I. (2024). User experience evaluation of Edurell interface for video augmentation. Multimedia Tools and Applications, 83(12), 36695–36717. https://doi.org/10.1007/s11042-023-15912-x
Glinsky, J. V., Ilha, J., Xiong, Y., Gomez, G., Rostagnor, S., Martín-Manjarrés, S., Tranter, K., Muldoon, S., Weerts, E., & Harvey, L. A. (2023). The 2022 Massive Open Online Course (MOOC) to train physiotherapists in the management of people with spinal cord injuries: a qualitative and quantitative analysis of learners’ experiences and its impact. Spinal Cord, 61(11), 615–623. https://doi.org/10.1038/s41393-023-00922-1
Hot, A., Dagenais, C., Kielende, M., Villemin, R., & Ridde, V. (2025). Evaluation of remote learning in knowledge translation through massive open online courses in the DRC. African Evaluation Journal, 13(1), 1–9. https://doi.org/10.4102/aej.v13i1.791
Iniesto, F., Rodrigo, C., & Hillaire, G. (2023). A Case Study to Explore a UDL Evaluation Framework Based on MOOCs. Applied Sciences (Switzerland), 13(1). https://doi.org/10.3390/app13010476
Jarial, P., Aggarwal, H., & Singla, B. S. (2025). The effectiveness of MOOCs in Technical Education: an Indian perspective. Scientific Reports, 15(1), 1–16. https://doi.org/10.1038/s41598-025-09405-0
Jiao, J., & Chen, B. (2023). A GCN- and Deep Biaffine Attention-Based Classification Model for Course Review Sentiment. International Journal of Information Technologies and Systems Approach, 16(2), 1–18. https://doi.org/10.4018/IJITSA.323568
Jitpaisarnwattana, N. (2025). The effects of a personalized learning plan in a language MOOC on learners’ oral presentation skills. JALT CALL Journal, 21(2), 1–23. https://doi.org/10.29140/jaltcall.v21n2.102601
Mercado, J., Mendoza-Cardenas, C., Fletscher, L., & Gaviria-Gomez, N. (2025). Learning Analytics in a Non-Linear Virtual Course. Algorithms, 18(5), 1–29. https://doi.org/10.3390/a18050284
Mi, A., Hashim, H., & Hussin, S. (2025). Small Private Online Courses Integrated with Blended Learning: Effect on English Speaking Skills in Chinese Higher Education. Forum for Linguistic Studies, 7(5), 340–357. https://doi.org/10.30564/fls.v7i5.9572
Mignemi, G., Chen, Y., & Moustaki, I. (2025). Unfolding the Network of Peer Grades: A Latent Variable Approach. Psychometrika, 90(3), 1153–1174. https://doi.org/10.1017/psy.2025.10021
Morales-Chan, M., Amado-Salvatierra, H. R., Medina, J. A., Barchino, R., Hernández-Rizzardini, R., & Teixeira, A. M. (2024). Personalized Feedback in Massive Open Online Courses: Harnessing the Power of LangChain and OpenAI API. Electronics (Switzerland), 13(10), 1–12. https://doi.org/10.3390/electronics13101960
Nera, K., Frenay, M., & Paquot, M. (2025). Improving argumentation quality on MOOC discussion forums: does learning to identify components of arguments help? Research and Practice in Technology Enhanced Learning, 20, 1–22. https://doi.org/10.58459/rptel.2025.20017
Nováková, D., & Němejc, K. (2024). Competences for the Future (Future Work 4S) – Green Skills and Environmental Education. In BioResources (Vol. 19, Issue 4, pp. 7381–7392). https://doi.org/10.15376/biores.19.4.7381-7392
Qi, X., Sun, G., & Yue, L. (2023). Applying Self-Optimised Feedback to a Learning Management System for Facilitating Personalised Learning Activities on Massive Open Online Courses. Sustainability (Switzerland), 15(16), 0–21. https://doi.org/10.3390/su151612562
Sappa, A. (2025). Assessing the Impact of Large Language Models on the Scalability and Efficiency of Automated Feedback Mechanisms in Massive Open Online Courses. Indian Journal of Information Sources and Services, 15(2), 275–286. https://doi.org/10.51983/ijiss-2025.IJISS.15.2.35
Sarilita, E., Rafisa, A., Desai, P., & Mossey, P. A. (2024). Utilising massive open online courses to enhance global learning dissemination in cleft lip and palate: a case report of penta helix collaboration. BMC Medical Education, 24(1), 1–8. https://doi.org/10.1186/s12909-024-05225-4
Selvaraj, R., Kuthadi, V., Baskar, S., & Acevedo, R. (2025). Exploring Motivation and Learning Factors in Digital Media Through the Lens of Activity Theory and Behavioural Influences. Indian Journal of Information Sources and Services, 15(3), 37–47. https://doi.org/10.51983/ijiss-2025.IJISS.15.3.05
Sriwisathiyakun, K. (2024). A MOOC-Integrated Design Thinking Model For Hearing-Impaired Learners. Journal of Information Technology Education: Research, 23, 6–14.
Ulfa, S., Surahman, E., Wedi, A., Fatawi, I., & Bringula, R. (2025). An adaptive assessment: Online summary with automated feedback as a self-assessment tool in MOOCs environments. Knowledge Management and E-Learning, 17(1), 88–113. https://doi.org/10.34105/j.kmel.2025.17.004
Wang, Y., Nie, L., & Jian, H. (2023). Valuation and Analysis of Online Teaching Platforms in Post-pandemic Era. International Journal of Information and Education Technology, 13(2), 257–265. https://doi.org/10.18178/ijiet.2023.13.2.1803
Wei, W., Liu, J., Xu, X., Kolletar-Zhu, K., & Zhang, Y. (2023). Effective interactive engagement strategies for MOOC forum discussion: A self-efficacy perspective. PLoS ONE, 18(11 November), 1–15. https://doi.org/10.1371/journal.pone.0293668
Wiese-Posselt, M., Saydan, S., Lâm, T. T., Rörig, A., Bergmann, C., Becker, F., Kurzai, O., Feufel, M. A., Gastmeier, P., & Schneider, S. (2025). Development and evaluation of a massive open online course (MOOC) to teach medical students the prudent use of antibiotics. Antimicrobial Resistance and Infection Control, 14(1). https://doi.org/10.1186/s13756-025-01640-4
Zhilmagambetova, R., Kopeyev, Z., Mubarakov, A., & Alimagambetova, A. (2023). The Role of Adaptive Personalized Technologies in the Learning Process: Stepik as a Tool for Teaching Mathematics. International Journal of Virtual and Personal Learning Environments, 13(1), 1–15. https://doi.org/10.4018/IJVPLE.324079
Published
2026-06-19
How to Cite
Noer Ekafitri Sam, Mukhlisin, M., & Luís Miguel Oliveira de Barros Cardoso. (2026). Assessment and Feedback Practices in MOOCs: A Systematic Literature Review of 2023–2025 Studies. International Journal of Technology and Education Research, 4(02), 1612-1627. https://doi.org/10.63922/ijeter.v4i02.4082
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