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Jordan, Pamela W.; Albacete, Patricia L.; Katz, Sandra – Grantee Submission, 2015
Tutorial dialogue systems often simulate tactics used by experienced human tutors such as restating students' dialogue input. We investigated whether the amount of tutor restatement that supports student inference interacts with students' incoming knowledge level in predicting how much students learn from a system. We found that students with…
Descriptors: Intelligent Tutoring Systems, Man Machine Systems, Interaction, Student Reaction
Wolff, Annika; Mulholland, Paul; Zdrahal, Zdenek – Interactive Learning Environments, 2014
This paper describes an approach for supporting inquiry learning from source materials, realised and tested through a tool-kit. The approach is optimised for tasks that require a student to make interpretations across sets of resources, where opinions and justifications may be hard to articulate. We adopt a dialogue-based approach to learning…
Descriptors: Inquiry, Dialogs (Language), Feedback (Response), Web 2.0 Technologies

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