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Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making
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Chen, Guanliang; Ferreira, Rafael; Lang, David; Gasevic, Dragan – International Educational Data Mining Society, 2019
For the development of successful human-agent dialogue-based tutoring systems, it is essential to understand what makes a human-human tutorial dialogue successful. While there has been much research on dialogue-based intelligent tutoring systems, there have been comparatively fewer studies on analyzing large-scale datasets of human-human online…
Descriptors: Student Attitudes, Intelligent Tutoring Systems, Computer Software, Dialogs (Language)
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Underwood, Joshua – Research-publishing.net, 2021
Voice interaction assistants, such as "Siri," "Alexa," or "Google Assistant," offer new opportunities to create meaningful, fun tasks for language learning that require accurate spoken production. Designing good tasks requires an understanding of the learning context and needs as well as the interactional…
Descriptors: Audio Equipment, Second Language Learning, Second Language Instruction, Student Motivation