Forschungsprofessur „Learning Analytics in Higher Education"

English

Ioana Jivet, Kamila Misiejuk, Volkan Yücepur Foto: Hardy Welsch

Lerndaten für den Erfolg von Studierenden

Ein Universitätsstudium kann für Studierende zur Herausforderung werden, wenn sie nur sehr begrenzt Feedback erhalten, sich im Zeitmanagement oder mit eigenverantwortlichem Lernen schwer tun. Lehrende auf der anderen Seite stehen vor der großen Aufgabe, Studierenden individuelle Unterstützung zu bieten, was enorme Auswirkungen auf ihre Arbeitsbelastung hat. Können die digitalen Spuren, die Studierende hinterlassen, wenn sie mit Lernumgebungen interagieren, uns helfen zu verstehen, wo die Herausforderungen liegen und welche Art von Unterstützung am effektivsten wäre?

Jun.-Prof. Dr. Ioana Jivet widmet sich im Rahmen ihrer Forschungsprofessur der Gestaltung und Implementierung von Student-Facing Learning-Analytics Feedbacksystemen. Ihre interdisziplinäre Forschung an der Schnittstelle von Computer- und Data Science, Künstlicher Intelligenz, Erziehungswissenschaften und Human-Computer-Interaction zielt darauf ab, innovative Feedbacksysteme zu entwickeln. Diese Systeme sollen Studierenden nicht nur individuelle Unterstützung bieten, sondern auch umsetzbare Erkenntnisse liefern und dadurch das Bildungserlebnis im Hochschulbereich erheblich verbessern.

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  • Die Forschung der Gruppe konzentriert sich auf drei Bereiche, die alle mit dem Lebenszyklus der Entwicklung von Feedbacksystemen für Studierende verbunden sind.

    1. Informationsbedarfe und Datenquellen — Einer der wichtigsten Aspekte bei der Gestaltung von Feedback ist die Auswahl relevanter und aussagekräftiger Informationen. Wir untersuchen relevante Datenquellen und Indikatoren für Learning Analytics, die für effektives Lernen unerlässlich sind und von Studierenden als wertvoll wahrgenommen werden. Dabei achten wir auf ein Gleichgewicht zwischen psychologisch-erziehungswissenschaftlicher Fundierung, nutzerorientiertem Design und technischer Realisierbarkeit.

    2. Bereitstellung und Sensemaking — Berechnete relevante Learning Analytics Indikatoren sind ohne eine geeignete Art der Bereitstellung wertlos. Es ist entscheidend, dass Studierende und Lehrende die bereitgestellten Informationen leicht verstehen und interpretieren können. Hier untersuchen wir Designmerkmale, die die Sinngebung für Studierende unterstützen, sei es durch Learning Analytics Dashboards oder durch Texte, die mit Sprachmodellen (LLMs) generiert wurden. Gleichzeitig erforschen wir, wie wir die Funktionsweise unserer Systeme für die Studierenden transparent halten können.

    3. Reflexion und Umsetzung — Sobald ein Feedbacksystem implementiert ist, ist es wichtig zu verstehen, wie es von den Studierenden genutzt wird. Welche Erkenntnisse gewinnen sie aus dem Feedback und wer profitiert am meisten davon? Mit diesen Informationen erforschen wir effektive Reflexionstrigger und wie Unterstützung für Reflexion und Umsetzung in die Student-Facing Learning Analytics integriert werden können, um den Studierenden, die es benötigen, zu helfen.

    In allen drei Bereichen wollen wir außerdem verstehen, wie studentische Fähigkeiten, Ziele und kulturelle Werte die Erwartungen, Bedürfnisse, Bedenken und die Akzeptanz von Learning Analytics beeinflussen, um die Systeme individuell anpassen zu können.

  • Jun.-Prof. Dr. Ioana Jivet

    Ioana JivetFoto: Hardy Welsch

    Maria Efstathiadou

    Assistenz der Forschungsprofessur

    E-Mail: maria.efstathiadou

    Telefon: +49 2331 987-4678

    PRG, Raum B 113 (1. Etage)

    Dr. Kamila Misiejuk

    Kamila MisiejukFoto: Hardy Welsch

    Volkan Yücepur

    Volkan YücepurFoto: Hardy Welsch

    Ekaterina Soroka

    EkaterinasorokaFoto: Privat

    Wissenschaftliche Hilfskraft:

    Leo Oelscher

  • 2026

    Konferenzbeiträge

    • 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
    • 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.

    • 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

    2025

    Zeitschriftenartikel

    • 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

    • 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

    • Konferenzbeiträge

    • 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., 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

    • 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).

      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 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).

    • Vorträge und Posterpräsentationen

    • 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

    Zeitschriftenartikel

    • 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

    Konferenzbeiträge

    • 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. https://www.solaresearch.org/wp-content/uploads/2024/03/LAK24_CompanionProceedings.pdf

      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.

    • Herausgeberschaften

    • 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

    • Buchbeiträge

    • 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

    • Vorträge und Posterpräsentationen

    • 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

    Zeitschriftenartikel

    • 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


    Konferenzbeiträge

    • 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.

    Buchbeiträge

    • Viberg, O., Jivet, I., & Scheffel, M. (2023). Designing culturally aware learning analytics: A value sensitive perspective. In O. Viberg & Å. Grönlund (Hrsg.), Practicable Learning Analytics (S. 177–192). Springer. https://doi.org/10.48550/arXiv.2212.09645

    • Herausgeberschaften

    • 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

  • Maria Efstathiadou

    Assistenz der Forschungsprofessur Learning Analytics

    E-Mail: maria.efstathiadou

    Telefon: +49 2331 987-4678

    PRG, Raum B 113 (1. Etage)

CATALPA | 20.03.2026