FIT

2011 - 2015

FIT Logo

Intelligent tutoring systems (ITS) have been getting more and more popular. The applicability of ITSs is typically restricted to well-defined domains where a domain formalization is easily possible. For ill-defined domains, human tutors still by far outperform the performance of ITSs, or the latter are not applicable at all. The goal of the FIT project was to develop novel ITS methods which extend the applicability of ITS systems to ill-defined domains by means of machine learning techniques which can autonomously infer structures and feedback options from given data (e.g., student solutions). For this purpose, prototype based machine learning methods and recent developments for general non-vectorial data structures were extended such that they allow to simultaneously structure solution spaces, learn metrics for structures, align student solutions with clusters of other solutions, and infer appropriate feedback based thereon. In this project which was part of the DFG priority programme "Autonomous Learning", the CSES group cooperated with the research group of Prof. Dr. Barbara Hammer which is located at the Faculty of Technology at Bielefeld University.

Persons

Images


Publications

2017
[17] 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.
[BIB] [DOI] [URL]
[16] S. Gross, M. Kliemannel, N. Pinkwart (2017). Orientation and Navigation Support in Resource Spaces Using Hierarchical Visualizations. i-com, 16(1), 35--44.
[BIB] [DOI]
2016
[15] 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).
[BIB] [URL]
2015
[14] S. Gross, B. Mokbel, B. Hammer, N. Pinkwart (2015). Learning Feedback in Intelligent Tutoring Systems. KI - Künstliche Intelligenz, 1--6.
[BIB] [PDF] [DOI]
[13] S. Gross, N. Pinkwart (2015). How Do Learners Behave in Help-Seeking When Given a Choice? In Cristina Conati, Neil Heffernan, Antonija Mitrovic, M. Felisa Verdejo, eds., Lecture Notes in Computer Science - Artificial Intelligence in Education (pp. 600--603). Springer International Publishing.
[BIB] [PDF] [DOI]
[12] S. Gross, N. Pinkwart (2015). Towards an Integrative Learning Environment for Java Programming. In D. G. Sampson, R. Huang, G.-J. Hwang, T.-Z. Liu, N.-S. Chen, Kinshuk, C.-C. Tsai, eds., IEEE 15th International Conference on Advanced Learning Technologies (ICALT), 2015 (pp. 24--28). Los Alamitos, CA, IEEE Computer Society Press.
[BIB] [PDF] [DOI]
[11] 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).
[BIB] [URL]
2014
[10] S. Gross, B. Mokbel, B. Hammer, N. Pinkwart (2014). How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning. In S. Trausan-Matu, K. E. Boyer, M.and Panourgia K. Crosby, eds., Lecture Notes in Computer Science (8474) - Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS) (pp. 340--347). Berlin, Germany, Springer Verlag.
[BIB] [DOI]
[9] S. Gross, B. Mokbel, B. Paassen, B. Hammer, N. Pinkwart (2014). Example-based feedback provision using structured solution spaces. International Journal of Learning Technology, 9(3), 248--280.
[BIB] [DOI]
2013
[8] S. Gross, B. Mokbel, B. Hammer, N. Pinkwart (2013). Towards Providing Feedback to Students in Absence of Formalized Domain Models. In H. C. Lane, K. Yacef, J. Mostow, P. Pavlik, eds., Lecture Notes in Computer Science - Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED) (pp. 644--648). Berlin, Germany, Springer Verlag.
[BIB] [DOI]
[7] S. Gross, B. Mokbel, B. Hammer, N. Pinkwart (2013). Towards a Domain-Independent ITS Middleware Architecture. In N.-S. Chen, R. Huang, Kinshuk, Y. Li, D. G. Sampson, eds., Proceedings of the 13th IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 408--409). Los Alamitos, CA, IEEE Computer Society Press.
[BIB] [DOI]
[6] B. Mokbel, S. Gross, B. Paassen, N. Pinkwart, B. Hammer (2013). Domain-Independent Proximity Measures in Intelligent Tutoring Systems. In S. K. D'Mello, R. A. Calvo, A. Olney, eds., Proceedings of the 6th International Conference on Educational Data Mining (EDM) (pp. 334--335). Memphis, TN.
[BIB]
[5] B. Mokbel, B. Paassen, M. Lux, S. Gross, N. Pinkwart, B. Hammer (2013). Interpretable proximity measures for intelligent tutoring systems. University of Applied Sciences Mittweida, Machine Learning Reports 04/2013, p. 13. Abstract.
[BIB] [URL]
2012
[4] S. Gross, B. Mokbel, B. Hammer, N. Pinkwart (2012). Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces. In J. Desel, J. M. Haake, C. Spannagel, eds., GI Lecture Notes in Informatics (P-207) - Tagungsband der 10. e-Learning Fachtagung Informatik (DeLFI) (pp. 27--38). Bonn, Germany, GI.
[BIB] [PDF]
[3] S. Gross, X. Zhu, B. Hammer, N. Pinkwart (2012). Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems. In S. Cerri, W. Clancey, G. Papadourakis, K. Panourgia, eds., Lecture Notes in Computer Science (7315) - Proceedings of the 11th International Conference on Intelligent Tutoring Systems (ITS) (pp. 699--700). Berlin, Germany, Springer Verlag.
[BIB] [PDF]
[2] B. Mokbel, S. Gross, M. Lux, N. Pinkwart, B. Hammer (2012). How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning? In N. Mana, F. Schwenker, E. Trentin, eds., Lecture Notes in Computer Science (7477) - Proceedings of the 5th International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR) (pp. 1--13). Berlin, Germany, Springer Verlag.
[BIB] [PDF]
[1] N. Pinkwart, B. Hammer (2012). Towards Learning Feedback in Intelligent Tutoring Systems by Clustering Spaces of Student Solutions. In G. M. Youngblood, P. McCarthy, eds., Proceedings of the 25th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS) (pp. 572). Marco Island, FL, AAAI.
[BIB] [PDF]