Graph Mining and Outlier Detection Meet Logic Proof Tutoring

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00076475" target="_blank" >RIV/00216224:14330/14:00076475 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Graph Mining and Outlier Detection Meet Logic Proof Tutoring

Popis výsledku v původním jazyce

We introduce a new method for analysis and evaluation of logic proofs constructed by undergraduate students, e.g. resolution or tableaux proofs. This method employs graph mining and outlier detection. The data has been obtained from a web-based system for input of logic proofs built at FI MU. The data contains a tree structure of the proof and also temporal information about all actions that a student performed, e.g. a node insertion into a proof, or its deletion, drawing or deletion of an edge, or textmanipulations. We introduce a new method for multi-level generalization of subgraphs that is useful for characterization of logic proofs. We use this method for feature construction and perform class-based outlier detection on logic proofs represented by these new features. We show that this method helps to find unusual students' solutions and to improve semi-automatic evaluation of the solutions.

Název v anglickém jazyce

Graph Mining and Outlier Detection Meet Logic Proof Tutoring

Popis výsledku anglicky

We introduce a new method for analysis and evaluation of logic proofs constructed by undergraduate students, e.g. resolution or tableaux proofs. This method employs graph mining and outlier detection. The data has been obtained from a web-based system for input of logic proofs built at FI MU. The data contains a tree structure of the proof and also temporal information about all actions that a student performed, e.g. a node insertion into a proof, or its deletion, drawing or deletion of an edge, or textmanipulations. We introduce a new method for multi-level generalization of subgraphs that is useful for characterization of logic proofs. We use this method for feature construction and perform class-based outlier detection on logic proofs represented by these new features. We show that this method helps to find unusual students' solutions and to improve semi-automatic evaluation of the solutions.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of EDM 2014 Ws Graph-based Educational Data Mining (G-EDM)

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

8

Strana od-do

43-50

Název nakladatele

CEUR-WS.org

Místo vydání

London

Místo konání akce

London, United Kingdom

Datum konání akce

4. 7. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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