Adaptive structure metrics for automated feedback provision in intelligent tutoring systems

Paaßen B, Mokbel B, Hammer B (2016)
Neurocomputing 192(SI): 3-13.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
Typical intelligent tutoring systems rely on detailed domain-knowledge which is hard to obtain and difficult to encode. As a data-driven alternative to explicit domain-knowledge, one can present learners with feedback based on similar existing solutions from a set of stored examples. At the heart of such a data-driven approach is the notion of similarity. We present a general-purpose framework to construct structure metrics on sequential data and to adapt those metrics using machine learning techniques. We demonstrate that metric adaptation improves the classification of wrong versus correct learner attempts in a simulated data set from sports training, and the classification of the underlying learner strategy in a real Java programming dataset.
Stichworte
metric learning; intelligent tutoring systems; sequential data; learning vector quantization; algebraic dynamic programming
Erscheinungsjahr
2016
Zeitschriftentitel
Neurocomputing
Band
192
Ausgabe
SI
Seite(n)
3-13
ISSN
0925-2312
eISSN
1872-8286
Page URI
https://pub.uni-bielefeld.de/record/2783224

Zitieren

Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing. 2016;192(SI):3-13.
Paaßen, B., Mokbel, B., & Hammer, B. (2016). Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing, 192(SI), 3-13. doi:10.1016/j.neucom.2015.12.108
Paaßen, B., Mokbel, B., and Hammer, B. (2016). Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing 192, 3-13.
Paaßen, B., Mokbel, B., & Hammer, B., 2016. Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing, 192(SI), p 3-13.
B. Paaßen, B. Mokbel, and B. Hammer, “Adaptive structure metrics for automated feedback provision in intelligent tutoring systems”, Neurocomputing, vol. 192, 2016, pp. 3-13.
Paaßen, B., Mokbel, B., Hammer, B.: Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing. 192, 3-13 (2016).
Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. “Adaptive structure metrics for automated feedback provision in intelligent tutoring systems”. Neurocomputing 192.SI (2016): 3-13.
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Material in PUB:
Zitiert
Java Sorting Programs
Paaßen B (2016)
Bielefeld University.