Humboldt-Universität zu Berlin - Faculty of Mathematics and Natural Sciences - Computer Science Education | Computer Science and Society

FIT

2011 - 2015

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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.

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Publications with the keyword "fit"


J. Coenen, S. Gross, and N. Pinkwart
Comparison of Feedback Strategies for Supporting Programming Learning in Integrated Development Environments (IDEs)
Advanced Computational Methods for Knowledge Engineering: Proceedings of the 5th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2017, Springer International Publishing, 2017, ISBN 978-3-319-61911-8
dynafit fit
DOI, ISBN, RIS, BibTex
S. Gross and N. Pinkwart
Konzept-Lernressourcen-Beziehungen als Unterstützung von Selbstreflexion in einem Learning-Analytics-Werkzeug
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), CEUR Workshop Proceedings (CEUR-WS.org), 2016
dynafit fit learning analytics werkzeug lernressource visualisierung konzept
URL, RIS, BibTex
S. Gross and N. Pinkwart
Ressourcenorientierte Visualisierungen als Learning-Analytics-Werkzeuge für Lehrende und Lerner
Proceedings of DeLFI Workshops 2015 co-located with 13th e-Learning Conference of the German Computer Society (DeLFI 2015), CEUR Workshop Proceedings (CEUR-WS.org), 2015
dynafit fit learning analytics werkzeug lernressource visualisierung konzept
URL, RIS, BibTex
S. Gross and N. Pinkwart
How Do Learners Behave in Help-Seeking When Given a Choice?
Artificial Intelligence in Education, Springer International Publishing, 2015, ISBN 978-3-319-19772-2
fit intelligent tutoring system help-seeking feedback choice
DOI, ISBN, PDF, RIS, BibTex
S. Gross, B. Mokbel, B. Hammer, and N. Pinkwart
How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning
Proceedings of the 12th International Conference on Intelligent Tutoring Systems (ITS), Springer Verlag, 2014
fit
DOI, RIS, BibTex
B. Mokbel, S. Gross, B. Paassen, N. Pinkwart, and B. Hammer
Domain-Independent Proximity Measures in Intelligent Tutoring Systems
Proceedings of the 6th International Conference on Educational Data Mining (EDM), 2013
fit
RIS, BibTex
S. Gross, B. Mokbel, B. Hammer, and N. Pinkwart
Towards a Domain-Independent ITS Middleware Architecture
Proceedings of the 13th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE Computer Society Press, 2013
fit
DOI, RIS, BibTex
S. Gross, B. Mokbel, B. Hammer, and N. Pinkwart
Towards Providing Feedback to Students in Absence of Formalized Domain Models
Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED), Springer Verlag, 2013
fit
DOI, RIS, BibTex
N. Pinkwart and B. Hammer
Towards Learning Feedback in Intelligent Tutoring Systems by Clustering Spaces of Student Solutions
Proceedings of the 25th International Conference of the Florida Artificial Intelligence Research Society (FLAIRS), AAAI, 2012
fit
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B. Mokbel, S. Gross, M. Lux, N. Pinkwart, and B. Hammer
How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning?
Proceedings of the 5th International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Springer Verlag, 2012
fit
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S. Gross, X. Zhu, B. Hammer, and N. Pinkwart
Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems
Proceedings of the 11th International Conference on Intelligent Tutoring Systems (ITS), Springer Verlag, 2012
fit
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