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Examining the use of artificial intelligence in pre-service teacher education.

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Title: Examining the use of artificial intelligence in pre-service teacher education.
Authors: Ponomarenko, Elena B.1, Sergeeva, Olga V.2, Zheltukhina, Marina R.3 zzmr@mail.ru, Baranova, Kseniia M.4, Budkevich, Roza L.5, Melnik, Mariya V.6
Source: Contemporary Educational Technology. Apr2026, Vol. 18 Issue 2, p1-24. 24p.
Subject Terms: *Artificial intelligence, *Teacher training, *Digital literacy, *Student teachers, *Student teacher attitudes, *Educational technology, Artificial intelligence & ethics
Abstract: This systematic review investigates the current state of artificial intelligence (AI) integration in pre-service teacher (PST) education, with an emphasis on PSTs' perspectives, attitudes, knowledge levels, and AI-related educational experiences. The review intends to uncover the characteristics that influence PSTs' intents to employ AI technology, as well as the success of AI training programs. A thorough search of academic databases turned up 33 research published between 2021 and 2024, which were examined using a theme framework. The findings show that PSTs have both positive and negative attitudes about AI integration, with initial AI knowledge and skills being restricted but improving with targeted training and hands-on experiences. Perceived utility, ease of use, social impact, and self-efficacy have all been proven to influence PSTs' propensity to employ AI. The review also emphasizes PSTs' favorable experiences using AIbased instruction, such as lesson planning, collaborative learning, and feedback/evaluation. However, issues and ethical concerns regarding data privacy, academic honesty, fairness, and the possible harmful impact on student learning were highlighted. The review recommends that teacher education institutes prioritize AI literacy development, address PSTs' concerns, and incorporate ethical considerations into AI courses. The findings add to the expanding body of literature on AI integration in education, providing useful insights for defining teacher education practice and policy in the AI era. [ABSTRACT FROM AUTHOR]
Copyright of Contemporary Educational Technology is the property of Bastas Publications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Examining the use of artificial intelligence in pre-service teacher education.
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  Data: <searchLink fieldCode="AR" term="%22Ponomarenko%2C+Elena+B%2E%22">Ponomarenko, Elena B.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Sergeeva%2C+Olga+V%2E%22">Sergeeva, Olga V.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Zheltukhina%2C+Marina+R%2E%22">Zheltukhina, Marina R.</searchLink><relatesTo>3</relatesTo><i> zzmr@mail.ru</i><br /><searchLink fieldCode="AR" term="%22Baranova%2C+Kseniia+M%2E%22">Baranova, Kseniia M.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Budkevich%2C+Roza+L%2E%22">Budkevich, Roza L.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Melnik%2C+Mariya+V%2E%22">Melnik, Mariya V.</searchLink><relatesTo>6</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Contemporary+Educational+Technology%22">Contemporary Educational Technology</searchLink>. Apr2026, Vol. 18 Issue 2, p1-24. 24p.
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  Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Teacher+training%22">Teacher training</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+literacy%22">Digital literacy</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+teachers%22">Student teachers</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+teacher+attitudes%22">Student teacher attitudes</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence+%26+ethics%22">Artificial intelligence & ethics</searchLink>
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  Data: This systematic review investigates the current state of artificial intelligence (AI) integration in pre-service teacher (PST) education, with an emphasis on PSTs' perspectives, attitudes, knowledge levels, and AI-related educational experiences. The review intends to uncover the characteristics that influence PSTs' intents to employ AI technology, as well as the success of AI training programs. A thorough search of academic databases turned up 33 research published between 2021 and 2024, which were examined using a theme framework. The findings show that PSTs have both positive and negative attitudes about AI integration, with initial AI knowledge and skills being restricted but improving with targeted training and hands-on experiences. Perceived utility, ease of use, social impact, and self-efficacy have all been proven to influence PSTs' propensity to employ AI. The review also emphasizes PSTs' favorable experiences using AIbased instruction, such as lesson planning, collaborative learning, and feedback/evaluation. However, issues and ethical concerns regarding data privacy, academic honesty, fairness, and the possible harmful impact on student learning were highlighted. The review recommends that teacher education institutes prioritize AI literacy development, address PSTs' concerns, and incorporate ethical considerations into AI courses. The findings add to the expanding body of literature on AI integration in education, providing useful insights for defining teacher education practice and policy in the AI era. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Contemporary Educational Technology is the property of Bastas Publications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Apr2026
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