What is Adaptive Testing

This chapter examines the integration of artificial intelligence (AI) in language learning assessment and feedback. It highlights limitations of traditional models before exploring AI-driven innovations in automated scoring, speech recognition, multimodal analytics and adaptive testing. The ensuing pedagogical transformation is discussed. AI feedback mechanisms including automated writing evaluation, intelligent tutoring systems, conversational agents, affective computing and learning analytics dashboards are analyzed. Benefits are presented alongside challenges regarding ethics, overreliance on technology and transparency. Case studies provide examples across educational contexts. The future outlook considers emerging innovations, increased accessibility, research gaps, policies and human-AI partnerships. The conclusion emphasizes responsible, human-centric integration of AI to enhance pedagogy and learner experience.