International Journal For Multidisciplinary Research

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AI-Supported Formative Assessment and Its Role in Enhancing Feedback Quality: A Conceptual Framework, Evidence Synthesis, and Implementation

Author(s) Dr.MD. Zakir Hussain
Country India
Abstract Among the many factors impacting learning, formative assessment is reported to be one of the more effective, as it provides learners with continuous feedback on their progress toward reaching their educational goals [1]. Feedback in the classroom is frequently delayed, cannot be specific enough, or does not match well enough with stated academic goals, especially in large classes and those with limited working resources. The introduction of new technologies in artificial intelligence (AI)—specifically, analytics software, automatic feedback submission, and generative AI—offers promise for improving the timeliness, personalization, diagnostic accuracy, and scalability of formative assessment feedback. The AI-FAST Framework (an AI-enabled formative assessment that is used to help students and teachers improve the quality of formative assessment) brings together the existing empirical evidence about the effectiveness of formative assessments and feedback from previous studies [1,5] and synthesizes newly generated evidence on feedback interventions powered by artificial intelligence and analytics [6,7].
Six dimensions identify the quality of feedback that AI-FAST uses, namely, timeliness, specificity, actionability (forward-looking), criterion alignment, learner agency (two-way feedback), and equity/ethics. The framework also provides information on how AI supports feedback generation and decision-making but retains the professionalism and expertise of the teacher through a "human in the loop" model based on the principles of international best practice for the responsible use of AI in education [8]. The paper positions the AI-FAST model within the Indian National Policy on Technology for Education and Digital Education Ecosystems [9,10] and discusses the implications for teachers, school leaders, institutions of teacher education, and researchers, including indicators of success and evaluation strategies. The paper concludes by indicating that AI has the potential to improve the quality of feedback when it is integrated into a quality formative assessment system and aligns with the curriculum and is ethically based.
Keywords Keywords: formative assessment; feedback quality; AI in education; learning analytics; automated feedback; generative AI; assessment for learning; educational policy.
Field Sociology > Education
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-03-04
DOI https://doi.org/10.36948/ijfmr.2026.v08i02.70541
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