Proof step analysis for proof tutoring - a learning approach to granularity

dc.contributor.authorSchiller, Marvin
dc.contributor.authorDietrich, Dominik
dc.contributor.authorBenzmüller, Christoph
dc.date.accessioned2024-09-04T09:45:58Z
dc.date.available2024-09-04T09:45:58Z
dc.date.issued2008-12-01
dc.description.abstractWe present a proof step diagnosis module based on the mathematical assistant system Ωmega. The task of this module is to evaluate proof steps as typically uttered by students in tutoring sessions on mathematical proofs. In particular, we categorise the step size of proof steps performed by the student, in order to recognise if they are appropriate with respect to the student model. We propose an approach which builds on reconstructions of the proof in question via automated proof search using a cognitively motivated proof calculus. Our approach employs learning techniques and incorporates a student model, and our diagnosis module can be adjusted to different domains and users. We present a first evaluation based on empirical data.en
dc.formatapplication/pdf
dc.identifier.citationTeaching Mathematics and Computer Science, Vol. 6 No. 2 (2008) , 325-343
dc.identifier.doihttps://doi.org/10.5485/TMCS.2008.0183
dc.identifier.eissn2676-8364
dc.identifier.issn1589-7389
dc.identifier.issue2
dc.identifier.jatitleTeach. Math. Comp. Sci.
dc.identifier.jtitleTeaching Mathematics and Computer Science
dc.identifier.urihttps://hdl.handle.net/2437/379640
dc.identifier.volume6
dc.languageen
dc.relationhttps://ojs.lib.unideb.hu/tmcs/article/view/14830
dc.rights.accessOpen Access
dc.rights.ownerMarvin Schiller, Dominik Dietrich and Christoph Benzmüller
dc.subjectproof tutoringen
dc.subjectautomated reasoningen
dc.subjectmachine learningen
dc.titleProof step analysis for proof tutoring - a learning approach to granularityen
dc.typefolyóiratcikkhu
dc.typearticleen
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