Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning

July 09, 2018 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Ravi Kokku, Aditya Vempaty, Tamer Abuelsaad, Prasenjit Dey, Tammy Humphrey, Akimi Gibson, Jennifer Kotler arXiv ID 1807.03224 Category cs.AI: Artificial Intelligence Cross-listed cs.HC Citations 3 Venue arXiv.org Last Checked 4 months ago
Abstract
This paper presents our experiences in designing, implementing, and piloting an intelligent vocabulary learning tutor. The design builds on several intelligent tutoring design concepts, including graph-based knowledge representation, learner modeling, and adaptive learning content and assessment exposition. Specifically, we design a novel phased learner model approach to enable systematic exposure to words during vocabulary instruction. We also built an example application over the tutor platform that uses a learning activity involving videos and an assessment activity involving word to picture/image association. More importantly, the tutor adapts to the significant variation in children's knowledge at the beginning of kindergarten, and evolves the application at the speed of each individual learner. A pilot study with 180 kindergarten learners allowed the tutor to collect various kinds of activity information suitable for insights and interventions both at an individual- and class-level. The effort also demonstrates that we can do A/B testing for a variety of hypotheses at scale with such a framework.
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