Towards collaborative intelligent tutors: Automated recognition of users' strategies.

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Towards collaborative intelligent tutors: Automated recognition of users' strategies.

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Title: Towards collaborative intelligent tutors: Automated recognition of users' strategies.
Author: Grosz, Barbara; Rubin, Andee; Yamangil, Elif; Shieber, Stuart; Gal, Ya'akov Kobi

Note: Order does not necessarily reflect citation order of authors.

Citation: Ya'akov Gal, Elif Yamangil, Stuart M. Shieber, Andee Rubin, and Barbara J. Grosz. Towards collaborative intelligent tutors: Automated recognition of users' strategies. In Proceedings of the Ninth International Conference on Intelligent Tutoring Systems, Montreal, Canada, 23-27 June 2008. The original publication is available at www.springerlink.com
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Abstract: This paper addresses the problem of inferring students’ strategies when they interact with data-modeling software used for pedagogical purposes. The software enables students to learn about statistical data by building and analyzing their own models. Automatic recognition of students’ activities when interacting with pedagogical software is challenging. Students can pursue several plans in parallel and interleave the execution of these plans. The algorithm presented in this paper decomposes students’ complete interaction histories with the software into hierarchies of interdependent tasks that may be subsequently compared with ideal solutions. This algorithm is evaluated empirically using commercial software that is used in many schools. Results indicate that the algorithm is able to (1) identify the plans students use when solving problems using the software; (2) distinguish between those actions in students’ plans that play a salient part in their problem-solving and those representing exploratory actions and mistakes; and (3) capture students’ interleaving and free-order action sequences.
Published Version: http://dx.doi.org/10.1007/978-3-540-69132-7_21
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:2252605

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  • FAS Scholarly Articles [6929]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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