Revolutionizing Assessment
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