Bridging educational theories and practices: An interdisciplinary exploration of AI-driven pedagogical innovations in multicultural classrooms

This study explores the role of Artificial Intelligence (AI) in multicultural education through thematic analysis, content analysis, and cross-referencing analysis approaches. Drawing on current literature, the study identified key themes such as personalization of learning, cultural sensitivity in AI systems, ethical concerns and data bias, and professional development for educators. Content analysis assessed the frequency of occurrence of these themes across educational materials, while cross-referencing analysis integrated findings from both previous methods to provide a more comprehensive understanding. The results show that AI has great potential to support multicultural education, but there are significant gaps in its implementation, especially related to cultural sensitivity and professional development for educators. These findings highlight the need for more focused strategies to ensure AI is used ethically and inclusively in culturally diverse educational contexts.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-08-19
DOI
https://doi.org/10.6092/issn.1970-2221/20214
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Bridging educational theories and practices: An interdisciplinary exploration of AI-driven pedagogical innovations in multicultural classrooms

SHILAP Revista de lepidopterología
Intelligent Tutoring Systems and Adaptive Learning
article

Bridging educational theories and practices: An interdisciplinary exploration of AI-driven pedagogical innovations in multicultural classrooms

article en

Abstract

This study explores the role of Artificial Intelligence (AI) in multicultural education through thematic analysis, content analysis, and cross-referencing analysis approaches. Drawing on current literature, the study identified key themes such as personalization of learning, cultural sensitivity in AI systems, ethical concerns and data bias, and professional development for educators. Content analysis assessed the frequency of occurrence of these themes across educational materials, while cross-referencing analysis integrated findings from both previous methods to provide a more comprehensive understanding. The results show that AI has great potential to support multicultural education, but there are significant gaps in its implementation, especially related to cultural sensitivity and professional development for educators. These findings highlight the need for more focused strategies to ensure AI is used ethically and inclusively in culturally diverse educational contexts.

SHILAP Revista de lepidopterología
University of Brawijaya (ID), Islamic University (BD)
Quality Education
Openalex Percentile: Top 67%
Intelligent Tutoring Systems and Adaptive Learning
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