• Kaliisa R., López‐Pernas, S., Misiejuk, K., Damşa, C., Sobocinski, M., Järvelä, S. & Saqr, M. (2025). A Topical Review of Research in Computer-Supported Collaborative Learning: Questions and Possibilities. Computers & Education. 105246. https://doi.org/10.1016/j.compedu.2025.105246
  • Misiejuk, K., Samuelsen, J., Kaliisa, R. & Prinsloo, P. (2025). Idiographic learning analytics: Mapping of the ethical issues. Learning and Individual Differences, 117.
  • Misiejuk, K., Kaliisa, R., & Scianna, J. (2024). Augmenting assessment with AI coding of online student discourse: A question of reliability. Computers and Education: Artificial Intelligence, 100216.
  • Misiejuk, K., Ness, I. J., Gray, R., & Wasson, B. (2023). Changes in online course designs: Before, during, and after the pandemic. Frontiers in Education, 7.
  • Misiejuk, K., & Wasson, B. (2021). Backward evaluation in peer assessment: A scoping review. Computers & Education, 175, 1–12.
  • Misiejuk, K., Wasson, B., & Egelandsdal, K. (2021). Using learning analytics to understand student perceptions of peer feedback. Computers in Human Behavior, 117, 1–13.


‌Book Chapters

  • López-Pernas, S., Misiejuk, K., Kaliisa, R., Conde-González, M. Á., & Saqr, M. (2024). Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods. In M. Saqr & S. López-Pernas (Eds.), Learning analytics methods and tutorials: A practical guide using R. Springer. 
  • López-Pernas, S., Misiejuk, K., Tikka, S., Saqr, M., & Kopra, J. (2024). Data visualization and reporting in Learning Analytics with R. In M. Saqr & S. López-Pernas (Eds.), Learning analytics methods and tutorials: A practical guide using R. Springer.
  • Misiejuk, K., & Wasson, B. (2023). Learning analytics for peer assessment - A scoping review. In O. Noroozi & B. De Wever (Eds.), The Power of Peer Learning. Springer.


‌Conference Proceedings

  • Saqr, M., López-Pernas, S., Törmänen, T., Kaliisa, R., Misiejuk, K., & Tikka, S. (2025). Transition Network Analysis: A Novel Framework for Modeling, Visualizing, and Identifying the Temporal Patterns of Learners and Learning Processes.  In Proceedings of the 15th Learning Analytics and Knowledge Conference.
  • Kaliisa, R., López-Pernas, S., Misiejuk, K., Saqr, M., & Damşa, C. (2024). Exploring the Dynamics and Trends of Knowledge Exchange: A Structured Topic Modeling Approach of the CSCL Conference Proceedings. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS’24).
  • Kaliisa, R., Misiejuk, K., López-Pernas, S., Khalil, M., & Saqr, M. (2024). Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students’ Achievement, Motivation, Participation and Attitude (Best Paper Award). In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 295–304).
  • Misiejuk, K., & Khalil, M. (2024). The Co-Design Process of an Instructor Dashboard for Remote Labs in Higher Education. In Lecture Notes in Computer Science, LNCS 14722, volume 39, Proceedings of the 26th International Conference on Human-Computer Interactions.
  • Misiejuk, K., López-Pernas, S., Kaliisa, R., & Saqr, M. (2024). Learning together: Student-AI interactions to generate learning resources. In Proceedings of the 12th Technological Ecosystems for Enhancing Multiculturality Conference.
  • Misiejuk, K., Pawelec, A., Ershova, T., & Bastesen, J. (2024). An exploratory analysis of AI-supported essay writing and group peer assessment. In Companion Proceedings of the 8th International Conferenc on Learning Analytics and Knowledge (pp. 269–271). Society for Learning Analytics Research.
  • Misiejuk, K., Khalil, M., & Wasson, B. (2023). Tackling the challenges with data access in learning analytics research: A case study of virtual labs. In Proceedings of the Technology-Enhanced Learning in Laboratories workshop (TELL 2023). CEUR Workshop Proceedings.
  • Kaliisa, R., Misiejuk, K., Arastoopour Irgens, G., & Misfeldt, M. (2021). Scoping the emerging field of quantitative ethnography: Opportunities, challenges and future directions. In Proceedings of the 2nd International Conference on Quantitative Ethnography (pp. 3–17). Springer.
  • Misiejuk, K., Scianna, J., Kaliisa, R., Vachuska, K., & Shaffer, D. W. (2021). Incorporating sentiment analysis with epistemic network analysis to enhance discourse analysis of Twitter data. In Proceedings of the 2nd International Conference on Quantitative Ethnography (pp. 375–389). Springer.
  • Misiejuk, K. (2018). The potential of learning analytics to support peer assessment. In Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge. Society for Learning Analytics Research.
  • Misiejuk, K., & Wasson, B. (2018). Challenges in using learning analytics to explore peer assessment data. In 44th International Association for Educational Assessment Annual Conference Abstracts. International Association for Educational Assessment.


‌REports

  • Ferguson, R., Coughlan, T., Egelandsdal, K., Gaved, M., Herodotou, C., Hillaire, G., Jones, D., Jowers, I., Kukulska-Hulme, A., McAndrew, P., Misiejuk, K., Ness, I. J. , Rienties, B., Scanlon, E., Sharples, M., Wasson, B., Weller, M. & Whitelock, D. (2019). Innovating Pedagogy 2019 (Open University Innovation Report 7). The Open University.
  • Misiejuk, K., & Wasson, B. (2017). State of the field report on learning analytics. SLATE report 2017-2. Centre for the Science of Learning & Technology (SLATE), University of Bergen

Journal articles