Knowledge tracing is a popular and successful approach to modeling student learning. In this paper we investigate whether the addition of neuroimaging ...
Knowledge tracing is a popular and successful approach to modeling student learning. In this paper we investigate whether the addition of neuroimaging ...
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Oct 30, 2024 · Knowledge tracing is a technology that models students' changing knowledge state over learning time based on their historical answer records ...
In this paper, we investigate whether the addition of neuroimaging observations to a knowledge tracing model enables accurate prediction of memory performance ...
Knowledge tracing aims to quantify how well students master the knowledge (tags) being tutored by analyzing their learning activities (e.g., ...
Jan 25, 2024 · Knowledge tracing (KT) aims to leverage students' learning histories to estimate their mastery levels on a set of pre-defined skills, ...
Knowledge tracing—where a machine models the knowledge of a student as they interact with coursework—is a well established problem in computer supported.
Jul 20, 2022 · We propose a novel task of tracing the evolving classification behavior of human learners as they engage in challenging visual classification tasks.
In this paper, we compare three knowledge tracing models, Bayesian Knowledge. Tracing, Bayesian Knowledge Tracing with Forgetting, and the Additive Factors ...
Sep 7, 2017 · Knowledge tracing aims to quantify how well students master the knowledge (tags) being tutored by analyzing their learning activities (e.g., ...