A Recommendation System Based on an Adaptive Learning Cognitive Map Model and Its Effects

Autor/inn/en	Wan, Haipeng; Yu, Shengquan
Titel	A Recommendation System Based on an Adaptive Learning Cognitive Map Model and Its Effects
Quelle	In: Interactive Learning Environments, 31 (2023) 3, S.1821-1839 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Wan, Haipeng) ORCID (Yu, Shengquan)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2020.1858115
Schlagwörter	Electronic Learning; Intelligent Tutoring Systems; Artificial Intelligence; Cognitive Mapping; Cognitive Structures; Cognitive Style; Learning Activities; Information Technology; Difficulty Level; Elementary School Students; Foreign Countries; Academic Achievement; China + Suchen Sie Ihr Suchwort? Intelligentes Tutorsystem; Künstliche Intelligenz; Cognitive structure; Kognitive Struktur; Cognitive styles; Kognitiver Stil; Lernaktivität; Informationstechnologie; Schwierigkeitsgrad; Ausland; Schulleistung
Abstract	Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance to make a procedural reflection and self-directed adjustment. This study proposed an adaptive learning cognitive map model and developed an online learning system based on this model. The proposed system could represent learners' knowledge structure and cognitive state that allow learning contents, learning activities, learning paths and learning partners to be adjusted continuously, thus providing learners with appropriate learning resources and initiative reflection opportunities during the whole learning procedure. This study conducted a contrast experiment to evaluate the effectiveness of the proposed system. Students in the experimental group received learning interventions according to their adaptive learning cognitive maps. The result demonstrated that the proposed system with the learning cognitive map improved students' learning achievement, learning satisfied, user acceptance of information technology and learning interaction while did not reduce or increase cognitive load. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01