Adaptive structure metrics for automated feedback provision in Java programming

Paaßen B, Mokbel B, Hammer B (2015)
In: Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); 307-312.

Konferenzbeitrag | Veröffentlicht | Englisch
 
Download
OA
Herausgeber*in
Abstract / Bemerkung
Today's learning supporting systems for programming mostly rely on pre-coded feedback provision, such that their applicability is restricted to modelled tasks. In this contribution, we investigate the suitability of machine learning techniques to automate this process by means of a presentationm of similar solution strategies from a set of stored examples. To this end we apply structure metric learning methods in local and global alignment which can be used to compare Java programs. We demonstrate that automatically adapted metrics better identify the underlying programming strategy as compared to their default counterparts in a benchmark example from programming.
Stichworte
intelligent tutoring systems; metric learning; sequence alignment
Erscheinungsjahr
2015
Titel des Konferenzbandes
Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Seite(n)
307-312
Konferenz
ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Konferenzort
Bruges, Belgium
Konferenzdatum
2015-04-22 – 2015-03-24
ISBN
978-2-87587-014-8
Page URI
https://pub.uni-bielefeld.de/record/2724156

Zitieren

Paaßen B, Mokbel B, Hammer B. Adaptive structure metrics for automated feedback provision in Java programming. In: Verleysen M, ed. Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2015: 307-312.
Paaßen, B., Mokbel, B., & Hammer, B. (2015). Adaptive structure metrics for automated feedback provision in Java programming. In M. Verleysen (Ed.), Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 307-312).
Paaßen, B., Mokbel, B., and Hammer, B. (2015). “Adaptive structure metrics for automated feedback provision in Java programming” in Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Verleysen, M. ed. 307-312.
Paaßen, B., Mokbel, B., & Hammer, B., 2015. Adaptive structure metrics for automated feedback provision in Java programming. In M. Verleysen, ed. Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. pp. 307-312.
B. Paaßen, B. Mokbel, and B. Hammer, “Adaptive structure metrics for automated feedback provision in Java programming”, Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, M. Verleysen, ed., 2015, pp.307-312.
Paaßen, B., Mokbel, B., Hammer, B.: Adaptive structure metrics for automated feedback provision in Java programming. In: Verleysen, M. (ed.) Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 307-312. (2015).
Paaßen, Benjamin, Mokbel, Bassam, and Hammer, Barbara. “Adaptive structure metrics for automated feedback provision in Java programming”. Proceedings of the ESANN, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ed. Michel Verleysen. 2015. 307-312.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2019-09-25T06:37:58Z
MD5 Prüfsumme
eb5da8e64a83a2ebdb14fd103ace0b50

Material in PUB:
Zitiert
Java Sorting Programs
Paaßen B (2016)
Bielefeld University.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Suchen in

Google Scholar
ISBN Suche