FORMATIVE AND SUMMATIVE ASSESSMENT IN FOREIGN LANGUAGE LEARNING: INTEGRATING MULTIMODAL AI-DRIVEN APPROACHES

Abstract

This article examines the conceptual and practical frameworks of formative and summative assessment within the context of Foreign Language Learning (FLL). As the educational landscape increasingly integrates Artificial Intelligence (AI) and multimodal technologies, the traditional boundaries between "assessment for learning" and "assessment of learning" are being redefined. Drawing on the latest research from the Scopus database, this study explores how AI-driven tools can provide continuous diagnostic feedback (formative) while maintaining the rigor required for final evaluations (summative). The paper analyzes the perceived  opportunities—such as personalization and efficiency—alongside critical challenges including validity, reliability, and algorithmic bias. The conclusion  emphasizes a balanced pedagogical approach that leverages AI to create a more holistic and responsive assessment environment.