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Project INF

inf

Prof. Dr. Enkelejda Kasneci, Dr. Stephan Hachinger & Prof. Dr. Matthias Stadler

Information Infrastructure

The Information Infrastructure Project INF will develop the SHARP-specific part of the technical and data infrastructure. It will provide expertise and technology to ensure a state-of-the-art technical implementation of personalised simulations supported by artificial intelligence for experimental studies in the SHARP research projects. In addition, this project will offer expertise and technology to establish and maintain an advanced rese-arch data management (RDM) based on the FAIR principles. Finally, the information infrastructure project will facilitate the data science literacy of researchers in the CRC.

Selected publications

  • Gao, H., Bozkir, E., Hasenbein, J., Göllner R., & Kasneci, E. (2021). Digital transformations of classrooms in virtual reality. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–10. https://doi.org/10.1145/3411764.3445596
  • Hachinger, S., Golasowski, M., Martinovič, J., Hayek, M., García-Hernández, R. J., Slaninová, K., Levrier, M., Scionti, A., Donnat, F., Vitali, G., Magarielli, D., Goubier, T., Parodi, A., Harsh, P., Dees, A., & Terzo, O. (2022). Leveraging high-performance computing and cloud computing with unified big-data workflows: The LEXIS project. In E. Curry, S. Auer, A. J. Berre, A. Metzger, M. S. Perez, & S. Zillner (Eds.), Technologies and Applications for Big Data Value (pp. 105–127). Springer, Cham. https://doi.org/10.1007/978-3-030-78307-5_8
  • Hou, R., Fütterer, T., Bühler, B., Bozkir, E., Gerjets, P., Trautwein, U., & Kasneci, E. (2024). Automated assessment of encouragement and warmth in classrooms leveraging multimodal emotional features and ChatGPT. In The 25th International Conference on Artificial Intelligence in Education (pp. 101–112). https://doi.org/10.1007/978-3-031-64302-6_5
  • Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning & Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  • Kasneci, E., Gao, H., Özdel, S., Maquiling, V., Thaqi, E., Lau, C., Rong, Y., Kasneci, G., & Bozkir, E. (2024). Introduction to eye tracking: A hands-on tutorial for students and practitioners. arXiv. https://arxiv.org/abs/2404.15435
  • Richters, C., Stadler, M., Radkowitsch, A., Schmidmaier, R., Fischer, M. R., & Fischer, F. (2023). Who is on the right track? Behavior-based prediction of diagnostic success in a collaborative diagnostic reasoning simulation. Large-Scale Assessments in Education, 11(1), 3. https://doi.org/10.1186/s40536-023-00151-1
  • Rong, Y., Leemann, T., Nguyen, T., Fiedler, L., & Qian, P. (2023). Towards human-centered explainable AI: A survey of user studies for model explanations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, 2104–2122. https://doi.org/10.1109/TPAMI.2023.3331846
  • Stadler, M., Brandl, L., & Greiff, S. (2023). 20 years of interactive tasks in large‐scale assessments: Process data as a way towards sustainable change?. Journal of Computer Assisted Learning, 39(6), 1852-1859. https://doi.org/10.1111/jcal.12847
  • Stadler, M., Iliescu, D., & Greiff, S. (2021). Validly authentic: Some recommendations to researchers using simulations in psychological assessment [Editorial]. European Journal of Psychological Assessment, 37(6), 419–422. https://doi.org/10.1027/1015-5759/a000686
  • Sümer, Ö., Goldberg, P., D'Mello, S., Gerjets, P., Trautwein, U., & Kasneci, E. (2021). Multimodal engagement analysis from facial videos in the classroom. IEEE Transactions on Affective Computing, 14(2). https://doi.org/10.1109/TAFFC.2021.3127692