@inproceedings{152394cee80b4b25be32b0feaabf6c75,
title = "Towards collaborative intelligent tutors: Automated recognition of users' strategies",
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.",
author = "Ya'Akov Gal and Elif Yamangil and Shieber, {Stuart M.} and Andee Rubin and Grosz, {Barbara J.}",
year = "2008",
month = jan,
day = "1",
doi = "10.1007/978-3-540-69132-7_21",
language = "English",
isbn = "3540691308",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "162--172",
booktitle = "Intelligent Tutoring Systems - 9th International Conference, ITS 2008, Proceedings",
address = "Germany",
note = "9th International Conference on Intelligent Tutoring Systems, ITS 2008 ; Conference date: 23-06-2008 Through 27-06-2008",
}