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Jordan, Pamela; Albacete, Patricia; Katz, Sandra – Grantee Submission, 2016
Prior research aimed at identifying linguistic features of tutoring that predict learning found interactions between student characteristics (e.g., incoming knowledge level, gender, and affect) and learning. This paper addresses the question: "What do these interactions suggest for developing adaptive natural-language tutoring systems?"…
Descriptors: Intelligent Tutoring Systems, Tutoring, Natural Language Processing, Student Characteristics
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Katz, Sandra; Albacete, Patricia; Jordan, Pamela – Grantee Submission, 2016
This poster reports on a study that compared three types of summaries at the end of natural-language tutorial dialogues and a no-dialogue control, to determine which type of summary, if any, best predicted learning gains. Although we found no significant differences between conditions, analyses of gender differences indicate that female students…
Descriptors: Natural Language Processing, Intelligent Tutoring Systems, Reflection, Dialogs (Language)