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Modeling affect by mining students’ interactions within learning environments

Mavrikis, Manolis, D'Mello, Sidney, Porayska-Pomsta, Kaska, Cocea, Mihaela and Graesser, Art (2010) Modeling affect by mining students’ interactions within learning environments. In: Handbook of Educational Data Mining. CRC Press, pp. 231-244. ISBN 978-143980458-2

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Official URL: https://doi.org/10.1201/b10274

Abstract

In the past decade, research on affect-sensitive learning environments has emerged as an important area in artificial intelligence in education (AIEd) and intelligent tutoring systems (ITS) [1-6]. These systems aspire to enhance the effectiveness of computer-mediated tutorial interactions by dynamically adapting to individual learners’ affective and cognitive states [7] thereby emulating accomplished human tutors [7,8]. Such dynamic adaptation requires the implementation of an affective loop [9], consisting of (1) detection of the learner’s affective states, (2) selection of systems actions that are sensitive to a learner’s affective and cognitive states, and sometimes (3) synthesis of emotional expressions by animated pedagogical agents that simulate human tutors or peer learning companions [9,10].

Item Type: Book Section
Additional Information: © 2010 by Taylor & Francis Group, LLC.
Subjects: L Education > L Education (General)
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
L Education > LC Special aspects / Types of education > E-Learning
Divisions: School of Computing > Staff Research and Publications
Depositing User: Tamara Malone
Date Deposited: 05 Dec 2023 14:03
Last Modified: 05 Dec 2023 14:03
URI: https://norma.ncirl.ie/id/eprint/6878

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