Research Professorship of Learning Analytics in Higher Education

Portraits Kamila Misiejuk, Ioana Jivet, Volkan Yücepur, Ekaterina Soroka — The Learning-Analytics-team f. l. t. r.: Kamila Misiejuk, Ioana Jivet, Volkan Yücepur, Ekaterina Soroka

Supporting student success with learner data

Learning at a university can be challenging for students due to limited feedback, difficulties in managing time, and adapting to self-directed learning. At the same time, teachers face the significant task of providing individualized support to each student, adding to their workload. Could the data breadcrumbs that students leave online as they interact with learning environments help us understand where the challenges lie and what kind of student support would be most effective?

Jun.-Prof. Dr. Ioana Jivet is dedicated to designing and implementing student-facing learning analytics feedback systems. This interdisciplinary effort, at the crossroads of computer and data science, artificial intelligence, learning sciences, and human-computer interaction, aims to develop innovative feedback systems. These systems will not only provide personalized student support but also offer actionable insights, thereby significantly enhancing the educational experience in higher education settings.

News from the Research Professorship

LEAD:FUH – An opportunity for learning analytics research

Evidence-based learning analytics applications in a new teaching architecture: That is the goal of the new million-euro project LEAD:FUH. CATALPA is contributing crucial expertise.

As part of her project "Emerging Network Techniques to Model Educational Data," Kamila Misiejuk traveled to Finland and the US this summer to deepen her collaboration with international colleagues and advance new insights.

The group’s research focuses on three directions, all related to the life-cycle of developing student feedback systems.

1. Information needs and data sources—Arguably, one of the most important aspects of feedback design is choosing relevant and meaningful information to provide as feedback. We investigate data sources and key indicators for student-facing learning analytics that are essential for effective learning and are perceived as valuable by students, ensuring a balance of pedagogical grounding, human-centered design, and technical feasibility.

2. Delivery and sense-making—Computed relevant learning analytics indicators are nothing without an appropriate way of delivering this information to its users. It is crucial that students and teachers can easily unpack and make sense of the information provided. Here, we explore design features that support student sense-making, be it with LA dashboards or text generated with LLMs, but also how we can keep the inner workings of our systems transparent to the students.

3. Reflection and action — Once a feedback system is in place, it is essential to understand how the system is being used by students, what insights they extract from the provided feedback, and who benefits the most from the system. With this information at hand, we explore effective reflection triggers and how support for reflection and action can be embedded into the student-facing learning analytics for the students who need it.

In each of these three directions, we also aim to understand how student skills, goals, and cultural values influence expectations, needs, concerns, and the adoption of learning analytics, allowing us to personalize the systems.

Jun.-Prof. Dr. Ioana Jivet

Maria Efstathiadou

Assistant of the research professorship Learning Analytics

Email: maria.efstathiadou

Phone: +49 2331 987-4678

PRG, Room B 113 (1st Floor)

Research Assistant:

Leo Oelscher

Mohammed Rizwan

Sascha Wanninger

2026

Journals

Kaliisa, R., Damşa, C., Eagan, B., Esterhazy, R., Langfold, M., & Misiejuk, K. (2026). Do modes of presence matter? regulation and participation in graduate students’ hybrid synchronous group-based collaboration. Learning and Instruction, 105, 102405. https://doi.org/10.1016/j.learninstruc.2026.102405

López-Pernas, S., Misiejuk, K., & Saqr, M. (2026). How AI ‐Generated Feedback Hinders or Helps Learning: A Heterogeneous TNA Study of Learning Dynamics. Journal of Computer Assisted Learning, 42(4), Article e70285. https://doi.org/10.1002/jcal.70285

López-Pernas, S., Oliveira, E. A., Misiejuk, K., Deriba, F. G., Kaliisa, R., & Saqr, M. (2026). Can AI deliver appropriate support for diverse student profiles? A large-scale evaluation. Computers in Human Behavior: Artificial Humans, 9, 100357. https://doi.org/10.1016/j.chbah.2026.100357

Misiejuk, K., López-Pernas, S., Kaliisa, R., & Saqr, M. (2026). Cognitive offloading in student–AI collaboration: A longitudinal analysis of prompting strategies. Computers in Human Behavior Reports, 22, 101130. https://doi.org/10.1016/j.chbr.2026.101130

Misiejuk, K., Oliveira, E. A., López-Pernas, S., Eagan, B., & Saqr, M. (2026). Comparing human and LLM ordered coding of qualitative data: How coding differences cascade through temporal analysis. Computers and Education: Artificial Intelligence, 100649. https://doi.org/10.1016/j.caeai.2026.100649

Saqr, M., Misiejuk, K., & López-Pernas, S. (2026). Human-AI collaboration or obedient and often clueless AI in instruct, serve, repeat dynamics? The Internet and Higher Education, 70, 101087. https://doi.org/10.1016/j.iheduc.2026.101087

Conferences
- Abu Hayya, M., Saqr, M., López-Pernas, S., & Misiejuk, K. (in print). Gender Bias in Multilingual LLMs' Student Profiling and Learning Support in Arabic Language. In Proceedings of the 14th Technological Ecosystems for Enhancing Multiculturality Conference (TEEM’26).
- López-Pernas, S., Misiejuk, K., Oliveira, E. A., & Saqr, M. (in print). Using AI Blurs Skill Differences and Levels Learning, Regulation, and Achievement in Programming Education. In Proceedings of the 28th International Symposium on Informatics in Education (SIIE’26), Zamora, Spain.
- López-Pernas, S., Misiejuk, K., & Saqr, M. (in print). Transition Trajectories of Students’ Interactions with AI. In K. Misiejuk, S. López-Pernas, E. Araujo Oliveira, & M. Saqr (Eds.), Communications in Computer and Information Science (CCIS), Proceedings of the 2nd Workshop on Transition Network Analysis (TNA). Springer.
- López-Pernas, S., Misiejuk, K., & Saqr, M. (2026). Using BERT-like Language Models for Automated Discourse Coding: A Primer and Tutorial. In M. Saqr & S. López-Pernas (Eds.), Advanced Learning Analytics Methods (pp. 235–259). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-95365-1_10
- López-Pernas, S., Misiejuk, K., Tikka, S., & Saqr, M. (2026). Role Dynamics in Student-AI Collaboration: A Heterogeneous Transition Network Analysis Approach. In Communications in Computer and Information Science (CCIS), Innovations in Analytics of Learning Dynamics: Proceedings of the 1st Workshop on Transition Network Analysis (TNA). Springer. https://doi.org/10.2139/ssrn.6082190
- Misiejuk, K., Kaliisa, R., López-Pernas, S., & Saqr, M. (2026). Expanding the Quantitative Ethnography Toolkit with Transition Network Analysis: Exploring Methodological Synergies and Boundaries. In G. Carmona, C. Lima, M. J. Santos, H. Benítez, L. Montero-Moguel, & B. Galarza-Tohen (Eds.), Communications in Computer and Information Science, Advances in Quantitative Ethnography (pp. 147–161). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-12229-2_10
- Misiejuk, K., Kolarik, S., Lehnert, F., Rinja, D., Yücepur, V., & Specht, M. (in print). Student-AI Dialogue Through Multiple Lenses: Interaction Profiles, Linguistic Patterns, and Content Trajectories. In Transition Network Analysis Workshop (LAK 26). Springer LNET.
- Misiejuk, K., Kolarik, S., Lehnert, F., Rinja, D., Yücepur, V., & Specht, M. (in print). Student–AI Dialogue Through Multiple Lenses: Interaction Profiles, Language Patterns, and Content Trajectories. In Communications in Computer and Information Science (CCIS), Innovations in Analytics of Learning Dynamics: Proceedings of the 1st Workshop on Transition Network Analysis (TNA). Springer.
  
  Misiejuk, K., Oliveira, E. A., López-Pernas, S., & Saqr, M. (in print). Ordering Bias and Ordering Variability: A Three-Step Approach for Interrater Reliability in Ordered Qualitative Coding. In K. Misiejuk, S. López-Pernas, E. Araujo Oliveira, & M. Saqr (Eds.), Communications in Computer and Information Science (CCIS), Proceedings of the 2nd Workshop on Transition Network Analysis (TNA). Springer.
  
  Misiejuk, K., Rinja, D., López-Pernas, S., & Saqr, M. (in print). Reliance, Reluctance and Relegation: A Semester-Long Analysis of Student-AI Interactions. In Proceedings of the 28th International Symposium on Informatics in Education (SIIE’26), Zamora, Spain.
  
  Misiejuk, K., Song, Y., Oliveira, E. A., López-Pernas, S., & Saqr, M. (in print). Modeling Sequential Context: A Stanza Window Extension of Co-occurrence Transition Network Analysis. In Communications in Computer and Information Science (CCIS), Innovations in Analytics of Learning Dynamics: Proceedings of the 1st Workshop on Transition Network Analysis (TNA). Springer.
- Pande, S., Song, Y., Misiejuk, K., López-Pernas, S., Saqr, M., & Oliveira, E. A. (2026). Profiling Writing Skills at Scale: A Hybrid Stylometry-LLM Pipeline for Formative Feedback. In X. Ochoa, A. Oh, Z. Pardos, & J. Kim (Eds.), Proceedings of the Thirteenth ACM Conference on Learning @ Scale (pp. 491–495). ACM. https://doi.org/10.1145/3774398.3811578
  
  Rinja, D., Oliveira, E. A., López-Pernas, S., Saqr, M., Specht, M., & Misiejuk, K. (2026). Unpacking Vibe Coding: Help-Seeking Processes in Student-AI Interactions While Programming. In E. G. Blanchard, G. Chen, M. Chi, & S. Isotani (Eds.), Lecture Notes in Computer Science, Artificial Intelligence in Education (pp. 515–530). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-29763-1_35
- Saqr, M., Misiejuk, K., Tikka, S., & López-Pernas, S. (2026). Artificial Intelligence: Using Machine Learning to Classify Students and Predict Low Achievers. In M. Saqr & S. López-Pernas (Eds.), Advanced Learning Analytics Methods (pp. 79–112). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-95365-1_4
- Saqr, M., Misiejuk, K., Tikka, S., & López-Pernas, S. (2026). Artificial Intelligence: Using Machine Learning to Predict Students’ Performance. In M. Saqr & S. López-Pernas (Eds.), Advanced Learning Analytics Methods (pp. 41–78). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-95365-1_3
- Saqr, M., López-Pernas, S., & Misiejuk, K. (in print). Dynalytics: The Birth of a Framework for Rigorous Analytics of Dynamical Systems. In Communications in Computer and Information Science (CCIS), Innovations in Analytics of Learning Dynamics: Proceedings of the 1st Workshop on Transition Network Analysis (TNA). Springer.
  
  Saqr, M., López-Pernas, S., & Misiejuk, K. (in print). To TNA, or not to TNA: Model Assessment Selection and Validation. In K. Misiejuk, S. López-Pernas, E. Araujo Oliveira, & M. Saqr (Eds.), Communications in Computer and Information Science (CCIS), Proceedings of the 2nd Workshop on Transition Network Analysis (TNA). Springer.
  
  Soroka, E., Seidel, N., Specht, M., & Misiejuk, K. (2026). New Lenses on Learning Design: Course Types and Indicators from Large-Scale Moodle Data. In Proceedings of the 21st European Conference on Technology-Enhanced Learning (EC-TEL’26).
  
  Wu, D., Misiejuk, K., López-Pernas, S., Chen, G., Saqr, M., & Oliveira, E. A. (2026). From Writing Traces to Personalised Support: Guiding LLMs with Stylometric Fingerprints. In E. G. Blanchard, G. Chen, M. Chi, & S. Isotani (Eds.), Lecture Notes in Computer Science, Artificial Intelligence in Education (pp. 469–478). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-29755-6_34
- Proceedings
- Misiejuk, K., López-Pernas, S., Araujo Oliveira, E., & Saqr, M. (Eds.) (in print). Proceedings of the 2nd Workshop on Transition Network Analysis (TNA). Communications in Computer and Information Science (CCIS). Springer.
  
  Swiecki, Z., Misiejuk, K., Kaliisa, R., Shah, M., Eagan, B., Tan, Y., & Marquart, C. (Eds.) (in print). Quantitative Ethnography in the Age of AI: Advanced Tools and Methods for Learning Analytics. Communications in Computer and Information Science (CCIS). Springer.
- Talks and Poster Presentations
- Kaliisa, R., Damşa, C., & Misiejuk, K. (2026, June 10). The dynamics of collaborative problem solving in hybrid learning environments. Computers and Learning Research Group (CALRG) Conference 2026, online. https://www.open.ac.uk/blogs/CALRG/day-3-wednesday-10-june-2026/
  
  Saqr, M., López-Pernas, S., & Misiejuk, K. (2026, November 18). Understanding high-order human ai interaction processes with higher-order networks. EARLI SIG27 Conference, Barcelona. https://www.earli.org/events/sig-27-conference-2026
  
  Saqr, M., Misiejuk, K., & López-Pernas, S. (2026, November 18). Capturing the dynamics of learning processes with transition and pattern analysis. EARLI SIG27 Conference, Barcelona. https://www.earli.org/events/sig-27-conference-2026
2025

Journals
- Giorgashvili, T., Jivet, I., Artelt, C., Biedermann, D., Bengs, D., Goldhammer, F., Hahnel, C., Mendzheritskaya, J., Mordel, J., Onofrei, M., Winter, M., Wolter, I., Horz, H., & Drachsler, H. (2025). From Reflection to Action: A Controlled Field Study on How Learners Interpret and Respond to Feedback in Learning Analytics Dashboards. Journal of Computer Assisted Learning, 41(4), Article e70073. https://doi.org/10.1111/jcal.70073
- 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, 228, 105246. https://doi.org/10.1016/j.compedu.2025.105246
- Kaliisa, R., Misiejuk, K., López-Pernas, S., & Saqr, M. (2025). How does artificial intelligence compare to human feedback? A meta-analysis of performance, feedback perception, and learning dispositions. Educational Psychology, 1–32. https://doi.org/10.1080/01443410.2025.2553639
- López-Pernas, S., Misiejuk, K., Kaliisa, R., & Saqr, M. (2025). Capturing the Process of Students' AI Interactions When Creating and Learning Complex Network Structures. IEEE Transactions on Learning Technologies, 18, 556–568. https://doi.org/10.1109/TLT.2025.3568599
- Misiejuk, K., Bastesen, J., & Ershova, T. (2025). How does using generative AI for essay writing impact peer assessment patterns? Insights from early adopters. Innovations in Education and Teaching International, 62(5), 1545–1558. https://doi.org/10.1080/14703297.2025.2516117
- Misiejuk, K., Samuelsen, J., Kaliisa, R., & Prinsloo, P. (2025). Idiographic learning analytics: Mapping of the ethical issues. Learning and Individual Differences, 117, 102599. https://doi.org/10.1016/j.lindif.2024.102599
- Oliveira, E., Misiejuk, K., López-Pernas, S., & Saqr, M. (in print). Writing under pressure: How time-induced stress and cognitive load shape student writing style. In Proceedings of the 9th International Conference on Smart Learning Environments (ICSLE 2025).
- Vogelsmeier, L. V., Oliveira, E., Misiejuk, K., López-Pernas, S., & Saqr, M. (2025). Delving into the psychology of Machines: Exploring the structure of self-regulated learning via LLM-generated survey responses. Computers in Human Behavior, 173, 108769. https://doi.org/10.1016/j.chb.2025.108769
- Woitt, S., Weidlich, J., Jivet, I., Orhan Göksün, D., Drachsler, H., & Kalz, M. (2025). Students’ feedback literacy in higher education: an initial scale validation study. Teaching in Higher Education(30 (1)), 257–276. 10.1080/13562517.2023.2263838
- Conferences
- Kaliisa, R., Damşa, C., Misiejuk, K., & Eagan, B. (2025). Understanding the Impact of Physical, Online, and Hybrid Modalities on Self and Co-Regulation during Collaborative Problem Solving. In Proceedings of the International Conference on Computer-supported for Collaborative Learning, Proceedings of the 18th International Conference on Computer-Supported Collaborative Learning - CSCL 2025 (pp. 634–636). International Society of the Learning Sciences. https://doi.org/10.22318/cscl2025.509380
  
  López-Pernas, S., Misiejuk, K., Griskova-Bulanova, I., Emara, M., Siddika, A. N. M., & Saqr, M. (in print). A Process-oriented View of Human-AI Interactions: Comparing Argumentative vs. Creative Writing. In Proceedings of the 9th International Conference on Smart Learning Environments (ICSLE 2025).
  
  López-Pernas, S., Misiejuk, K., Jovanović, J., Milić, M. R., Conde, M. Á., & Saqr, M. (2025). chatgptscrapeR: A Tool for Retrieving Student-AI Interactions. In 2025 IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 134–136). IEEE. https://doi.org/10.1109/ICALT64023.2025.00044
  
  López-Pernas, S., Misiejuk, K., Oliveira, E., & Saqr, M. (2025). Capturing the regulation process and dynamics of problem-solving in programming with AI. In Proceedings of Koli Calling 2025.
  
  López-Pernas, S., Misiejuk, K., Oliveira, E., & Saqr, M. (2025). The dynamics of the self-regulation process in student-AI interactions. In J. Leinonen & R. Duran (Eds.), Proceedings of the 25th Koli Calling International Conference on Computing Education Research (pp. 1–12). ACM. https://doi.org/10.1145/3769994.3770043
  
  López-Pernas, S., Tikka, S., Misiejuk, K., & Saqr, M. (in print). Tna-web: Advanced analytics just a few clicks away. In Proceedings of the 13th Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM 2025).
- Misiejuk, K., Saqr, M., Törmänen, T [Tina], Kaliisa, R., Tikka, S., & López-Pernas, S. (2025). Frequency Transition Network Analysis (FTNA). In CSCL 2025 Proceedings. https://drive.google.com/file/d/1C82vzIINhxl_Nrev9OsoiH4NhnWefUrk/view
  
  Saqr, M., López-Pernas, S., Törmänen, T [Tiina], 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 International Learning Analytics and Knowledge Conference (pp. 351–361). ACM. https://doi.org/10.1145/3706468.3706513
- Saqr, M., Misiejuk, K., Oliveira, E., Vogelsmeier, L. V., & López-Pernas, S. (in print). Correction, Overcorrection or New Reality: AI Portrays Girls as Better Learners, Self-regulated and on par with Boys in STEM Fields. In Proceedings of the 9th International Conference on Smart Learning Environments (ICSLE 2025).
- Talks and Poster Presentations
- Jivet, I. (2025, November 4). Supporting Student Success with Learning Analytics-based Feedback. Universität Tübingen. LEAD Retreat, Tübingen.
- Misiejuk, K., & Kaliisa, R. (2025, May 20). Have Learning Analytics Dashboards Lived Up to the Hype? The University of Bergen. 10th anniversary of the Centre for the Science of Learning & Technology (SLATE). https://slate.uib.no/celebrating-slates-10-year-anniversary/programme
  
  Misiejuk, K. (2025, June 10-2025, June 13). Understanding the Impact of Physical, Online, and Hybrid Modalities on Self and Co-Regulation during Collaborative Problem Solving. 5th Annual Meeting of the International Society of the Learning Sciences (ISLS), Helsinki, Finland. https://2025.isls.org/
  
  Misiejuk, K. (2025, June 16). Capturing the Complexity of Feedback Processes through Peer Assessment. University of Eastern Finland. Future Technologies Research Seminar. https://sites.uef.fi/edtech/2025/05/27/future-technologies-research-seminar-june-16-2025/
- Misiejuk, K. (2025, October 12).: Expanding the quantitative ethnography toolkit with Transition Network Analysis: Exploring methodological synergies and boundaries. The 7th International Conference on Quantitative Ethnography, Mexico City, Mexico.
  
  Misiejuk, K. (2025, October 16). A Process-oriented View of Human-AI Interactions: Comparing Argumentative vs. Creative Writing. The 9th International Conference on Smart Learning Environments (ICSLE 2025), Joensuu, Finland.
  
  Misiejuk, K. (2025, October 28). Teacher-Facing Learning Analytics Dashboards: What We Know, What Works, and What’s Next. TeacherLA 2025 Symposium – Research and Research Perspectives on Teacher-Facing Learning Analytics Dashboards, Tübingen, Germany.
2024

Journals
- Cardenas Hernandez, F. P., Schneider, J., Di Mitri, D., Jivet, I., & Drachsler, H. (2024). Beyond hard workout: A multimodal framework for personalised running training with immersive technologies. British Journal of Educational Technology. 10.1111/bjet.13445
  
  Gombert, S., Fink, A., Giorgashvili, T., Jivet, I., Di Mitri, D., Yau, J., Frey, A., & Drachsler, H. (2024). From the Automated Assessment of Student Essay Content to Highly Informative Feedback: a Case Study. International Journal of Artificial Intelligence in Education, 1–39. 10.1007/s40593-023-00387-6
  
  Karademir, O., Di Mitri, D., Schneider, J., Jivet, I., Allmang, J., Gombert, S., Kubsch, M., Neumann, K., & Drachsler, H. (2024). I don’t have time! But keep me in the loop: Co-designing requirements for a learning analytics cockpit with teachers. Journal of Computer Assisted Learning. Advance online publication. https://doi.org/10.1111/jcal.12997
  
  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, 6, 100216. https://doi.org/10.1016/j.caeai.2024.100216
- Seidenberg, N., Jivet, I., Scheffel, M., Kovanović, V., Lynch, G., & Drachsler, H. (2024). Learning At and From a Virtual Conference. Journal of Learning Analytics, 11(2), 281–296. https://doi.org/10.18608/jla.2024.8247
  
  Viberg, O., Kizilcec, R. F [Rene F.], Jivet, I., Monés, A. M., Oh, A., Mutimukwe, C., Hrastinski, S., & Scheffel, M. (2024). Cultural differences in students’ privacy concerns in learning analytics across Germany, South Korea, Spain, Sweden, and the United States. Computers in Human Behavior Reports, 14, 100416. https://doi.org/10.1016/j.chbr.2024.100416
  
  Viberg, O., Kizilcec, R. F [René F.], Wise, A. F., Jivet, I., & Nixon, N. (2024). Advancing equity and inclusion in educational practices with AI ‐powered educational decision support systems (AI ‐ EDSS ). British Journal of Educational Technology, 55(5), 1974–1981. https://doi.org/10.1111/bjet.13507
  
  Weidlich, J., Fink, A., Jivet, I., Yau, J., Giorgashvili, T., Drachsler, H., & Frey, A. (2024). Emotional and motivational effects of automated and personalized formative feedback: The role of reference frames. Journal of Computer Assisted Learning. Advance online publication. https://doi.org/10.1111/jcal.13024
Conferences
- Giorgashvili, T., Jivet, I., Artelt, C., Biedermann, D., Bengs, D., Goldhammer, F., Hahnel, C., Mendzheritskaya, J., Mordel, J., Onofrei, M., Winter, M., Wolter, I., Horz, H., & Drachsler, H. (2024). Exploring Learners’ Self-reflection and Intended Actions After Consulting Learning Analytics Dashboards in an Authentic Learning Setting. In R. Ferreira Mello, N. Rummel, I. Jivet, G. Pishtari, & J. A. Ruipérez Valiente (Eds.), Lecture Notes in Computer Science: Vol. 15159, Technology Enhanced Learning for Inclusive and Equitable Quality Education: 19th European Conference on Technology Enhanced Learning, EC-TEL 2024, Krems, Austria, September 16–20, 2024, Proceedings, Part I (1st ed. 2024, pp. 135–151). Springer Nature Switzerland; Imprint Springer. https://doi.org/10.1007/978-3-031-72315-5_10
  
  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. In LAK '24: Proceedings of the 14th Learning Analytics and Knowledge Conference. https://doi.org/10.1145/3636555.3636884
  
  Menzel, L., Jivet, I., Gombert, S., Schmitz, M., Giorgashvili, T., & Drachsler, H. (2024). 2nd Workshop on Highly Informative Learning Analytic (HILA). In Companion Proceedings of the 14th International Conference on Learning Analytics and Knowledge.
  
  Misiejuk, K., & Khalil, M. (2024). The Co-design Process of an Instructor Dashboard for Remote Labs in Higher Education. In P. Zaphiris & A. Ioannou (Eds.), Lecture Notes in Computer Science, Learning and Collaboration Technologies (pp. 65–76). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-61672-3_5
  
  Misiejuk, K., López-Pernas, S., Kaliisa, R., & Saqr, M. (2024). Learning together: Student-AI interactions to generate learning resources. (in press). In Proceedings of the 12th Technological Ecosystems for Enhancing Multiculturality Conference.
- Prieto, L. P., Viberg, O., Rodriguez-Triana, M. J., Jivet, I., Chen, B., & Scheffel, M. (2024). Culture and Values in Learning Analytics: A Human-Centered Design and Research Approach. In Companion Proceedings of the 14th International Conference on Learning Analytics and Knowledge. https://www.solaresearch.org/wp-content/uploads/2024/03/LAK24_CompanionProceedings.pdf
- Saqr, M., Törmänen, T., Kaliisa, R., Misiejuk, K., & Tikka, S. (2024). Capturing the depth and dynamics of collaborative learning with transition network analysis. In Proceedings of the 18th International Conference of Computer-Supported Collaborative Learning Conference.
Proceedings
- Ferreira Mello, R., Rummel, N., Jivet, I., Pishtari, G., & Ruipérez Valiente, J. A. (Eds.) (2024). Technology Enhanced Learning for Inclusive and Equitable Quality Education. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-72312-4
Chapters in Edited Books
- 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 (pp. 1–14). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54464-4_1
  
  López-Pernas, S., Misiejuk, K., Tikka, S., Kopra, J., Heinäniemi, M., & Saqr, M. (2024). Visualizing and Reporting Educational Data with R. In M. Saqr & S. López-Pernas (Eds.), Learning Analytics Methods and Tutorials (pp. 151–194). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54464-4_6
Talks and Poster Presentations
- Giorgashvili, T., Jivet, I., Hahnel, C., Mendzheritskaya, J., Winter, M., Bengs, D., Wolter, I., Goldhammer, F., & Drachsler, H. (2024, September 16). Wie Studierende über personalisiertes Feedback mit Learning-Analytics in großen Lehrveranstaltungen reflektieren.
2023

Journals
- Ferguson, R., Khosravi, H., Kovanović, V., Viberg, O., Aggarwal, A., Brinkhuis, M., Buckingham Shum, S., Chen, L. K., Drachsler, H., Guerrero, V. A., Hanses, M., Hayward, C., Hicks, B., Jivet, I., Kitto, K., Kizilcec, R., Lodge, J. M., Manly, C. A., Matz, R. L., … Yan, V. X. (2023). Aligning the goals of learning analytics with its research scholarship: An open peer commentary approach. Journal of Learning Analytics, 10(2), 14–50. https://doi.org/10.18608/jla.2023.8197
- Kaliisa, R., Jivet, I., & Prinsloo, P. (2023). A checklist to guide the planning, designing, implementation, and evaluation of learning analytics dashboards. International Journal of Educational Technology in Higher Education, 20(1), 28. https://doi.org/10.1186/s41239-023-00394-6
- Wollny, S., Di Mitri, D., Jivet, I., Muñoz-Merino, P., Scheffel, M., Schneider, J., Tsai, Y.-S., Whitelock-Wainwright, A., Gašević, D., & Drachsler, H. (2023). Students’ expectations of learning analytics across europe. Journal of Computer Assisted Learning, 39(4), 1325–1338. https://doi.org/10.1111/jcal.12802
Conferences
- Egetenmeier, A., & Jivet, I. (2023). Ten years of learning analytics in the german-speaking space: Success, failure and lessons learned. Workshopband Der 21. Fachtagung Bildungstechnologien (DELFI), 13–16.
- Kizilcec, R. F., Viberg, O., Jivet, I., Martinez Mones, A., Oh, A., Hrastinski, S., Mutimukwe, C., & Scheffel, M. (2023). The Role of Gender in Students’ Privacy Concerns about Learning Analytics: Evidence from five countries. In LAK23: 13th International Conference on Learning Analytics and Knowledge. https://doi.org/10.1145/3576050.3576142
  
  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. https://scispace.com/papers/tackling-the-challenges-with-data-access-in-learning-1p0jlon3
Proceedings
- Viberg, O., Jivet, I., Muñoz-Merino, P. J., Perifanou, M., & Papathoma, T. (Eds.) (2023). Responsive and Sustainable Educational Futures. Lecture Notes in Computer Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-42682-7
Chapters in Edited Books
- Viberg, O., Jivet, I., & Scheffel, M. (2023). Designing culturally aware learning analytics: A value sensitive perspective. In O. Viberg & Å. Grönlund (Eds.), Practicable learning analytics (pp. 177–192). Springer. https://doi.org/10.48550/arXiv.2212.09645
Interested in writing your Master thesis at the research professorship Learning Analytics in Higher Education? As a first step, please read our Thesis Guidelines and contact us at ioana.jivet. You are welcome to include your own topic proposals.
- Template for theses
- Guidelines for theses (PDF 447 KB)
Theses in progress

"Multi-Label Short Text Classification for Automatic Coding of Student Reflections with Support from Residents of 123 Sesame Street”, Masterarbeit, 2026
Maria Efstathiadou

Assistence oft the research professorship Learning Analytics

E-Mail: maria.efstathiadou

Telefon: +49 2331 987-4678

PRG, Room B 113 (1st Floor)

CATALPA | 03.08.2026

Research Professorship of Learning Analytics in Higher Education

Supporting student success with learner data