Automatic Modeling Learner's Personality Using Learning Analytics Approach in an Intelligent Moodle Learning Platform

Autor/inn/en	Tlili, Ahmed; Denden, Mouna; Essalmi, Fathi; Jemni, Mohamed; Chang, Maiga; Kinshuk; Chen, Nian-Shing
Titel	Automatic Modeling Learner's Personality Using Learning Analytics Approach in an Intelligent Moodle Learning Platform
Quelle	In: Interactive Learning Environments, 31 (2023) 5, S.2529-2543 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Tlili, Ahmed) ORCID (Essalmi, Fathi)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2019.1636084
Schlagwörter	Learning Analytics; Learning Management Systems; Intelligent Tutoring Systems; Bayesian Statistics; Personality Traits; State Universities; Recall (Psychology); Accuracy; Extraversion Introversion; Neurosis; Personality Measures; Learning Processes; Instructional Effectiveness; Game Based Learning; Teaching Methods; Foreign Countries; Undergraduate Students; Majors (Students); Computer Science Education; Information Technology; Tunisia; Big Five Inventory + Suchen Sie Ihr Suchwort? Intelligentes Tutorsystem; Individual characteristics; Personality characteristic; Persönlichkeitsmerkmal; Staatliche Universität; Abberufung; Neurose; Learning process; Lernprozess; Unterrichtserfolg; Teaching method; Lehrmethode; Unterrichtsmethode; Ausland; Computer science lessons; Informatikunterricht; Informationstechnologie; Tunesien
Abstract	The ability of automatically modeling learners' personalities is an important step in building adaptive learning environments. Several studies showed that knowing the personality of each learner can make the learning interaction with the provided learning contents and activities within learning systems more effective. However, the traditional method of modeling personality is using self-reports, such as questionnaire, which is subjective and with several limitations. Therefore, this study presents a new unobtrusive method to model the learners' personalities in an intelligent Moodle (iMoodle) using Learning Analytic (LA) approach with Bayesian network. To evaluate the accuracy of the proposed approach, an experiment was conducted with one hundred thirty-nine learners in a public university. Results showed that recall, precision, F-measure and accuracy values are in acceptance range for three personality dimensions including extraversion, openness, and neuroticism. Moreover, the results showed that the LA approach has a fair agreement with the Big Five Inventory (BFI) in modeling these three personality dimensions. Finally, this study provides several recommendations which can help researchers and practitioners develop effective smart learning environments for both learning and modeling. For example, it is needed to help identify more features of the hardest personality traits, such as agreeableness, using gamification courses. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01