The combination of Artificial Intelligence (AI) and Formative Assessment (FA) in Teacher Education explores how emerging technologies can enhance teaching practices and professional development. AI tools can provide personalized feedback, identify learning needs, and support reflective practice among educators. Integrating AI-driven formative assessment methods allows for continuous evaluation of teaching competencies, promoting adaptive learning, data-informed decision-making, and improved instructional quality in teacher education programs. The purpose of this study was to conduct a systematic review of the use of Formative Assessment (FA) and Artificial Intelligence (AI) in Teacher Education (TE) during the period 2020–2025 (inclusive). The review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, which ensures a rigorous, transparent, and reproducible process in the selection and analysis of studies. To this end, scientific articles published in the Scopus, Web of Science and Dialnet databases were reviewed, considering publications in English and Spanish. The objective was to identify trends, methodological approaches, results, and research gaps that show how AI is being integrated, or not, into FA processes in TE. The review also sought to analyze the impact of AI on student participation in assessment, feedback, decision-making, and the learning and assessment process itself, synthesizing the current evidence on the relationship between AI and FA in TE.
Soria et al. (Tue,) studied this question.