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January 14, 2026Computers22 citationsOpen Access

Artificial Intelligence in K-12 Education: A Systematic Review of Teachers’ Professional Development Needs for AI Integration

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SASpyridon AravantinosKLKonstantinos LavidasVKVassilis Komis

Key Points

  • This research examines the professional development needs of K-12 teachers for integrating artificial intelligence in education.
  • Conducted a systematic review of 43 empirical studies from Scopus and Web of Science.
  • Followed PRISMA guidelines to synthesize findings.
  • Identified themes related to teachers' needs for AI integration and professional development.
  • Successful AI integration requires pedagogical knowledge, organizational support, and positive attitudes.
  • Technical training alone is inadequate for effective AI use in classrooms.
  • Proposed a four-level framework for continuous professional development in AI education.

Abstract

Artificial intelligence (AI) is reshaping how learning environments are designed and experienced, offering new possibilities for personalization, creativity, and immersive engagement. This systematic review synthesizes 43 empirical studies (Scopus, Web of Science) to examine the training needs and practices of primary and secondary education teachers for effective AI integration and overall professional development (PD). Following PRISMA guidelines, the review gathers teachers’ needs and practices related to AI integration, identifying key themes including training practices, teachers’ perceptions and attitudes, ongoing PD programs, multi-level support, AI literacy, and ethical and responsible use. The findings show that technical training alone is not sufficient, and that successful integration of AI requires a combination of pedagogical knowledge, positive attitudes, organizational support, and continuous training. Based on empirical data, a four-level, process-oriented PD framework is proposed, which bridges research with educational practice and offers practical guidance for the design of AI training interventions. Limitations and future research are discussed.

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Cite This Study

Aravantinos et al. (2026) studied this question.

synapsesocial.com/papers/6966e72413bf7a6f02bff8dahttps://doi.org/10.3390/computers15010049
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