since 2015

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The rapidly increasing availability of online educational resources and the recent attention gained by distance education methods such as massive open online courses (MOOCs) show the importance of intelligent tutoring systems (ITS) as adaptive educational technologies that can personalize e-Learning. Classical ITSs require an exact formalization of the learning task and learner-system interactions. Hence their applicability is typically limited to well-defined domains. In addition, their labor-intensive preparation restricts their use to static, large-scale applications where development costs do not play a significant role. Within the first period of the FIT project, we have developed a FIT ITS infrastructure which allows the construction of ITSs in ill-defined domains based on machine learning techniques. The goal of DynaFIT is to develop machine learning models which can generalize across different tasks and user behaviors and, based thereon, to enhance FIT ITSs via dynamic user-adaptive feedback and open learner models in ill-defined domains. In this project which is part of the DFG priority programme "Autonomous Learning", the CSES group cooperates with the research group of Prof. Dr. Barbara Hammer which is located at the Faculty of Technology at Bielefeld University.




[4] J. Coenen, S. Gross, N. Pinkwart (2017). Comparison of Feedback Strategies for Supporting Programming Learning in Integrated Development Environments (IDEs). In N.-T. Le, T. van Do, N. T. Nguyen, H. A. L.e Thi, eds., Advanced Computational Methods for Knowledge Engineering: Proceedings of the 5th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2017 (pp. 72--83). Cham, Springer International Publishing.
[3] S. Gross, M. Kliemannel, N. Pinkwart (2017). Orientation and Navigation Support in Resource Spaces Using Hierarchical Visualizations. i-com, 16(1), 35--44.
[2] S. Gross, N. Pinkwart (2016). Konzept-Lernressourcen-Beziehungen als Unterstützung von Selbstreflexion in einem Learning-Analytics-Werkzeug. In R. Zender, ed., Proceedings der Pre-Conference-Workshops der 14. E-Learning Fachtagung Informatik co-located with 14th e-Learning Conference of the German Computer Society (DeLFI 2016) (pp. 18--27). CEUR Workshop Proceedings (CEUR-WS.org).
[1] S. Gross, N. Pinkwart (2015). Ressourcenorientierte Visualisierungen als Learning-Analytics-Werkzeuge für Lehrende und Lerner. In S. Rathmayer, H. Pongratz, eds., Proceedings of DeLFI Workshops 2015 co-located with 13th e-Learning Conference of the German Computer Society (DeLFI 2015) (pp. 91--100). CEUR Workshop Proceedings (CEUR-WS.org).