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AI in Education: Cracking the Code Through Challenges: A Content Analysis of one of the recent Issues of Educational Technology and Society (ET&S) Journal

Authors: Nooshin Darvishinia;

AI in Education: Cracking the Code Through Challenges: A Content Analysis of one of the recent Issues of Educational Technology and Society (ET&S) Journal

Abstract

AI is rapidly being utilized in education, potentially altering the learning process by enhancing outcomes, increasing efficiency, and enriching the educational experience. However, the use of AI in education raises several concerns, including the need for high-quality data, ethical and privacy concerns, challenges in integrating AI technology into existing educational systems and practices, and a lack of expertise and knowledge of AI among educators and learners. This study investigated these topics by doing a content analysis of one of the most recent issues of the journal Educational Technology and Society (ET&S), with an emphasis on AI in education. The study adopted qualitative content analysis to identify and categorize the prevalent themes and issues connected with AI in education, such as possible advantages, challenges and risks, ethical and privacy concerns, and the need for additional AI education and training. The findings of this study suggest that a thoughtful and careful approach is necessary for integrating AI into education, focusing on addressing critical challenges identified in this study.

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Keywords

AI Challenges, AI in Education, High-quality data, Ethics, Advantages, Privacy Concerns.

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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!
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