A Systematic Literature Review on Integrating Artificial Intelligence (AI) in Primary School Teacher Education: Opportunities, Challenges, and Future Directions - Yasir Salih; Tedi Fauzi; Setyo Luthfi Okta (International Journal of Ethno-Sciences and Education Research, 2026)
The global education disruption caused by the COVID-19 pandemic has intensified learning loss, particularly in primary education, and highlighted the urgent need for innovative teaching approaches. This study aims to examine the integration of artificial intelligence in primary school teacher education as a strategic response to these challenges. Using a qualitative design through a systematic literature review, this research analyzes recent academic publications to explore the opportunities, challenges, and future directions of artificial intelligence in teacher education. The findings indicate that artificial intelligence enhances learning quality by enabling personalized instruction, improving instructional design, and increasing student engagement. It also supports pre-service teachers in developing adaptive and data-driven teaching practices. However, several challenges persist, including unequal access to digital infrastructure, limited technological competence, and ethical concerns related to data use. These barriers highlight the need for comprehensive curriculum reform and institutional support. Furthermore, the study emphasizes the importance of preparing future teachers who are not only technologically skilled but also capable of integrating artificial intelligence meaningfully into pedagogical practices. In conclusion, the integration of artificial intelligence in teacher education is essential for improving learning outcomes and building resilient education systems in the digital era.