Teaching iSTART to Understand Spanish
| Autor: | Christian Soto, Danielle S. McNamara, Tricia A. Guerrero, Laura K. Allen, Matthew E. Jacovina, Mihai Dascalu, Jianmin Dai |
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| Rok vydání: | 2017 |
| Předmět: |
Process (engineering)
Computer science Teaching method 05 social sciences 050301 education Computer-Assisted Instruction Constructed language Comprehension 050106 general psychology & cognitive sciences Reading comprehension Mathematics education 0501 psychology and cognitive sciences Regular expression TUTOR 0503 education computer computer.programming_language |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319614243 AIED |
| DOI: | 10.1007/978-3-319-61425-0_46 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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