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Direct linkChango, Wilson; Cerezo, Rebeca; Sanchez-Santillan, Miguel; Azevedo, Roger; Romero, Cristóbal – Journal of Computing in Higher Education, 2021
The aim of this study was to predict university students' learning performance using different sources of performance and multimodal data from an Intelligent Tutoring System. We collected and preprocessed data from 40 students from different multimodal sources: learning strategies from system logs, emotions from videos of facial expressions,…
Descriptors: Grade Prediction, Intelligent Tutoring Systems, College Students, Data Use
Download full textLallé, Sébastien; Conati, Cristina; Azevedo, Roger; Mudrick, Nicholas; Taub, Michelle – International Educational Data Mining Society, 2017
In this paper, we investigate the relationship between students' learning gains and their compliance with prompts fostering self-regulated learning (SRL) during interaction with MetaTutor, a hypermedia-based intelligent tutoring systems (ITS). When possible, we evaluate compliance from student explicit answers on whether they want to follow the…
Descriptors: Compliance (Psychology), Metacognition, Computer Software, Eye Movements
Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger – Journal of Educational Data Mining, 2013
In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Individualized Instruction
