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Graph analysis of student model networks

Guerra, J and Huang, Y and Hosseini, R and Brusilovsky, P (2015) Graph analysis of student model networks. In: UNSPECIFIED.

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This paper explores the feasibility of a graph-based approach to model student knowledge in the domain of programming. The key idea of this approach is that programming concepts are truly learned not in isolation, but rather in combination with other concepts. Following this idea, we represent a student model as a graph where links are gradually added when the student's ability to work with connected pairs of concepts in the same context is confirmed. We also hypothesize that with this graph-based approach a number of traditional graph metrics could be used to better measure student knowledge than using more traditional scalar models of student knowledge. To collect some early evidence in favor of this idea, we used data from several classroom studies to correlate graph metrics with various performance and motivation metrics.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Guerra, Jjdg60@pitt.eduJDG60
Huang, Yyuh43@pitt.eduYUH43
Hosseini, Rroh38@pitt.eduROH38
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 January 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: CEUR Workshop Proceedings
Volume: 1446
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Intelligent Systems
School of Information Sciences > Information Science
Refereed: Yes
ISSN: 1613-0073
Date Deposited: 10 Aug 2015 16:15
Last Modified: 01 Nov 2017 12:57


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