Supporting Multiple Learning Experiences On A Childhood Vocabulary Tutoring Platform

INTELLIGENT TUTORING SYSTEMS, ITS 2018(2018)

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Abstract
We present a unified learner modeling approach in a childhood vocabulary tutoring platform that enables learning continuum across multiple learning experiences. By decoupling experiences from learner modeling, multiple learning experiences can be developed independently making learning approaches scalable in an inherently diverse setting: each child, his/her family, environment, geography, cultural differences can all make each learner really unique. By understanding the information-theoretic equivalence of different assessment types, and mapping different play and learning activities to one or more of these types, we can enable a rapid convergence of the learner model to better represent a young learner's knowledge. More interestingly, when normalized, different assessment types converge at different levels of the normalized score.
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