Beyond Algorithms: How AI-Driven Formative Assessment Transforms Teacher-Student Relationships

Abstract

The integration of artificial intelligence (AI) in formative assessment represents a paradigmatic shift in educational practice that extends far beyond computational efficiency. This paper examines how AI-driven formative assessment systems fundamentally transform the relational dynamics between teachers and students, moving from traditional evaluative hierarchies toward collaborative, data-informed partnerships. Through theoretical analysis of emerging pedagogical frameworks and examination of empirical evidence, this study argues that AI-mediated assessment facilitates three primary relational transformations:

• The democratization of feedback through real-time, personalized responses
• The evolution of teachers from assessors to learning facilitators and interpreters of algorithmic insights
• The empowerment of students as active partners in their learning trajectory through enhanced metacognitive awareness.

The findings suggest that while AI algorithms provide the technical infrastructure for continuous assessment, the transformative potential lies in how these systems reshape the fundamental social contract of classroom relationships, fostering more equitable, responsive, and collaborative learning environments. Implications for teacher preparation, professional development, and educational policy are discussed.