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Education and Information Technologies

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21.10.2021

A systematic review of AI role in the educational system based on a proposed conceptual framework

verfasst von: Weiqi Xu, Fan Ouyang

Erschienen in: Education and Information Technologies | Ausgabe 3/2022

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Abstract

Artificial Intelligence in Education (AIEd) is an emerging interdisciplinary field that applies artificial intelligence technologies to transform instructional design and student learning. However, most research has investigated AIEd from the technological perspective, which cannot achieve a deep understand of the complex roles of AI in instructional and learning processes and its relationship with other educational elements. To fill this gap, this review research proposes a conceptual framework from complex adaptive systems theory perspective, uses a systematic literature review approach to locate and summarize articles, and categorizes the roles of AI in the educational system. The review results indicate that when AI is added into an educational system, its roles can be characterized into three categories: AI as a new subject, AI as direct mediator, and AI as a supplementary assistant to influence the instructor-student, student-self, and student-student relationships. Reviewed articles under each category are examined to understand the influences of AI applications on instruction and learning. Based on the results, this systematic review research proposes practical, theoretical, and technological implications of AIEd development.

Vorheriger Artikel The effect of different usage of the educational programming language in programming education on the programming anxiety and achievement

Nächster Artikel Gender differences in information and communication technology use & skills: a systematic review and meta-analysis

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Titel: A systematic review of AI role in the educational system based on a proposed conceptual framework
verfasst von: Weiqi Xu
Fan Ouyang
Publikationsdatum: 21.10.2021
Verlag: Springer US
Erschienen in: Education and Information Technologies / Ausgabe 3/2022
Print ISSN: 1360-2357
Elektronische ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-021-10774-y

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