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Download full textCrossley, Scott; Kyle, Kristopher; Davenport, Jodi; McNamara, Danielle S. – International Educational Data Mining Society, 2016
This study introduces the Constructed Response Analysis Tool (CRAT), a freely available tool to automatically assess student responses in online tutoring systems. The study tests CRAT on a dataset of chemistry responses collected in the ChemVLab+. The findings indicate that CRAT can differentiate and classify student responses based on semantic…
Descriptors: Intelligent Tutoring Systems, Chemistry, Natural Language Processing, High School Students
Direct linkStefan Ruseti; Mihai Dascalu; Amy M. Johnson; Renu Balyan; Kristopher J. Kopp; Danielle S. McNamara – Grantee Submission, 2018
This study assesses the extent to which machine learning techniques can be used to predict question quality. An algorithm based on textual complexity indices was previously developed to assess question quality to provide feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). In…
Descriptors: Questioning Techniques, Artificial Intelligence, Networks, Classification
Cummings, Alycia E.; Barlow, Jessica A. – Clinical Linguistics & Phonetics, 2011
The goal of this research programme was to evaluate the role of word lexicality in effecting phonological change in children's sound systems. Four children with functional speech sound disorders (SSDs) were enrolled in an across-subjects multiple baseline single-subject design; two were treated using high-frequency real words (RWs) and two were…
Descriptors: Language Processing, Generalization, Phonology, Diagnostic Tests
