Titlebook: Intelligent Tutoring Systems; 14th International C Roger Nkambou,Roger Azevedo,Julita Vassileva Conference proceedings 2018 Springer Intern

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Identifying How Metacognitive Judgments Influence Student Performance During Learning with MetaTutortechnologies such as intelligent tutoring systems (ITSs), including MetaTutorIVH. However, there is a paucity of research examining how metacognitive monitoring processes such as ease of learning (EOLs) judgments can be used to provide adaptive scaffolding and predict student performance during lear

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Predicting Learners’ Emotions in Mobile MOOC Learning via a Multimodal Intelligent Tutorw engagement, low retention rate, and lack of personalization. We propose AttentiveLearner., a multimodal intelligent tutor running on unmodified smartphones, to supplement today’s clickstream-based learning analytics for MOOCs. AttentiveLearner. uses both the front and back cameras of a smartphone

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Toward Tutoring Systems Inspired by Applied Behavioral Analysise application branch of analysis of behavior that derives from Behaviorism in psychology and has relevant features that can be transferred in an effective tutoring systems: the techniques of ABA are reproduced in the ABA tutor..Moreover we describe the first implementation of ABA tutor and the appli

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Programming Intelligent Embodied Pedagogical Agents to Teach the Beginnings of Industrial Revolutiony. The paper shows how this programming environment was used to create an interactive, animated and intelligent virtual world, focused on teaching the beginnings of Industrial Evolution. This educational virtual world was positively evaluated through experiments carried out with simulated classes of History.

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The Allocation of Time Matters to Students’ Performance in Clinical Reasoningediated the relationship between students’ allocation of time and diagnostic performance outcomes. The high-performing students showed different patterns of time management with low-performing students when solving both simple and complex cases. Moreover, the durations of behaviors predicted students’ performance in clinical reasoning.

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