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International Journal of Research in Education and Science
Article . 2025 . Peer-reviewed
License: CC BY NC SA
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<b>Integrating AI into Education: Perspectives from Mathematics Teachers </b><b></b>

Authors: Abdullah S. Albalawi;

<b>Integrating AI into Education: Perspectives from Mathematics Teachers </b><b></b>

Abstract

This study examines mathematics teachers’ perceptions of using artificial intelligence (AI) in teaching. A survey was conducted among math teachers in Tabuk City, Saudi Arabia, encompassing three primary domains (knowledge and awareness, perceived benefits, concerns, and challenges) to ascertain mathematics teachers’ views on using AI in teaching. Completed questionnaires from 149 participants were examined. Results indicate that math teachers perceive AI knowledge and awareness positively. They acknowledge AI’s importance in enhancing their digital abilities, addressing students’ individual needs, and benefiting student assessment and personalised learning. They exhibit a neutral stance on several factors of AI use in teaching, including time adequacy, and accessibility, and AI-based apps. They expressed a need for more financial and moral incentives to integrate AI into professional training programmes. No statistically significant differences among math teachers’ perceptions of AI use in instruction were found based on gender, teaching stage, years of experience or the interaction between stage and experience.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
gold