Abstract
iSTART is a web-based reading comprehension tutor. A recent translation of iSTART from English to Spanish has made the system available to a new audience. In this paper, we outline several challenges that arose during the development process, specifically focusing on the algorithms that drive the feedback. Several iSTART activities encourage students to use comprehension strategies to generate self-explanations in response to challenging texts. Unsurprisingly, analyzing responses in a new language required many changes, such as implementing Spanish natural language processing tools and rebuilding lists of regular expressions used to flag responses. We also describe our use of an algorithm inspired from genetics to optimize the Fischer Discriminant Function Analysis coefficients used to determine self-explanation scores.
Original language | English (US) |
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Title of host publication | Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings |
Editors | Elisabeth Andre, Xiangen Hu, Ma. Mercedes T. Rodrigo, Benedict du Boulay, Ryan Baker |
Publisher | Springer Verlag |
Pages | 485-489 |
Number of pages | 5 |
ISBN (Print) | 9783319614243 |
DOIs | |
State | Published - 2017 |
Externally published | Yes |
Event | 18th International Conference on Artificial Intelligence in Education, AIED 2017 - Wuhan, China Duration: Jun 28 2017 → Jul 1 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10331 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 18th International Conference on Artificial Intelligence in Education, AIED 2017 |
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Country/Territory | China |
City | Wuhan |
Period | 6/28/17 → 7/1/17 |
Bibliographical note
Funding Information:This work was partially funded by the FP7 2008-212578 LTfLL project, by University Politehnica of Bucharest through the “Excellence Research Grants” Program UPB–GEX 12/26.09.2016, as well as by the Institute for the Science of Teaching & Learning (IES R305A130124) and the Office of Naval Research (ONR N000141410343 and ONR N00014-17-1-2300).
Publisher Copyright:
© Springer International Publishing AG 2017.
Keywords
- Intelligent tutoring systems
- Natural language processing
- Optimizing score prediction
- Reading comprehension