Andi Asrifan, Rismawati Rismawati, Juvrianto Chrissunday Jakob, Andi Syarifah Irmadani, Musdalifah Musdalifah
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. Copyright © 2026 by IGI Global Scientific Publishing. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Use of this publication to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development.
Universitas Negeri Makassar, Indonesia; Universitas Muhammadiyah, Palopo, Indonesia; Politeknik Negeri, Ambon, Indonesia; Institut Ilmu Kesehatan Pelamonia Makassar, Indonesia
