Formative Assessment in Kazakhstan’s English Language Classrooms: A Narrative Review of Current Practices and the Role of AI Tools

Abstract

Formative assessment (FA) has emerged as a critical component of effective teaching and learning, providing ongoing feedback that guides both teachers and students in improving educational outcomes. This narrative literature review examines the implementation of formative assessment in Kazakhstan’s English language classrooms and explores how artificial intelligence (AI) tools are enhancing and could further enhance these practices. The review synthesizes international and local research on FA – defining its key concepts, components, benefits, and challenges – within the context of Kazakhstan’s recent education reforms that mandate a criteria-based (formative) assessment system. It also discusses current applications of AI (such as adaptive learning platforms, natural language processing for feedback, and AI-driven peer/self-assessment tools) in education, and considers potential future uses of AI to support teachers and learners in formative assessment. The findings indicate that while formative assessment is valued for improving student engagement and achievement, Kazakhstani teachers face challenges in its implementation, including large classes and shifts in ingrained grading practices. AI technologies offer promising solutions to personalize feedback, automate routine assessment tasks, and inform data-driven instruction, albeit with the need for teacher training and careful integration. The review concludes with implications for educators and policymakers in Kazakhstan, emphasizing that blending proven formative assessment strategies with AI support can foster more responsive and effective English language teaching.