Revolutionizing Assessment

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Authors: Andi Asrifan, Rismawati Rismawati, Juvrianto Chrissunday Jakob, Andi Syarifah Irmadani, Musdalifah Musdalifah
Cited by: 3
References: 78

Abstract

The revolutionary impact of AI on educational evaluation through individualized and adaptive feedback mechanisms is examined in this chapter. AI technologies including natural language processing, machine learning, and learning analytics enable real-time, individualized feedback that encourages engagement, equity, and self-regulated learning. The chapter describes a pedagogical and technological framework for AI-facilitated feedback using constructivist and connectivist notions. Practical applications in K–12 and higher education show how intelligent systems improve formative assessment, student achievement, and inclusive teaching. Algorithmic bias, ethical issues, institutional readiness, and scalable, culturally appropriate implementations are carefully examined. The chapter concludes with policy, research, and practice proposals to make AI feedback systems dramatically improve assessment and curriculum design resilience in digital learning ecosystems.

Fields of Study & Subjects

Online Learning and Analytics Student Assessment and Feedback Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Publisher
IGI Global Scientific Publishing
Pages
243–266
Publication date
5 February 2026
Document type
Book chapter