Now We're Talking: Leveraging the Power of Natural Language Processing to Inform ITS Development
نویسندگان
چکیده
In the current study, we utilize natural language processing techniques to examine relations between the linguistic properties of students’ self-explanations and their reading comprehension skills. Linguistic features of students’ aggregated selfexplanations were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. Results indicated that linguistic properties of self-explanations were predictive of reading comprehension ability. The results suggest that natural language processing techniques can serve as stealth assessments of abilities within intelligent tutoring systems.
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