Artificial Intelligence in Evaluation and Assessment in Teacher Education: Opportunities, Challenges and Pathways Forward

Teacher education is becoming a key component of this technological revolution as artificial intelligence (AI) continues to change educational evaluation and assessment. By synthesizing recent empirical and conceptual research on automated scoring, AI-assisted formative feedback, competency-based and practicum assessment, and learning analytics, this paper investigates the evolving role of AI in evaluation and assessment within teacher preparation programs. While critically analyzing the ethical, pedagogical, and contextual concerns related to AI-enabled assessment, the conversation is based on well-established viewpoints on formative assessment and Technological Pedagogical Content Knowledge (TPACK). Concerns about algorithmic bias, assessment validity, possible teacher de-skilling, and the digital divide receive special focus. The National Education Policy (NEP) 2020 and the National Curriculum Framework for Teacher Education (NCFTE) 2021 are two major advancements in Indian teacher education that are further examined in this paper. It makes the case that while AI has a lot of promise to improve and expand assessment procedures, it shouldn't take the place of teacher educators' knowledge and professional judgment. The establishment of strong institutional regulations and governance mechanisms, the preservation of significant human oversight in high-stakes assessment and evaluation decisions, and the incorporation of AI and assessment literacy into teacher education curriculum are all suggested in the paper's conclusion.