Book Title: Advanced Studies in Multidisciplinary Research and Innovation (ASMRI)
Chief Editors: Dr. Jagdish Kumar Sahu and Dr. Krishna Ashutoshbhai Vyas
Associate Editors: Dr. N. Ramesh Chandra Srikanth and Dr. Lourdu Vesna J
Co-Editors: Dr. Aarti Sharma and Dr. Pushpa Mamoria
ISBN: 978-93-7183-010-2
Chapter: 5
DOI: https://doi.org/10.59646/745/5
Authors: Dr. Pushpa Mamoria, and Dr. Rajeev Kumar Shakya
Abstract
Artificial Intelligence (AI) has had a profound impact on education, reshaping the landscape of teaching and learning. The integration of Artificial Intelligence (AI) in higher education has revolutionized the way learning and education are delivered, especially in the creation of personalized learning systems. The aim of this research paper is to examine the potential of AI-based personalized learning systems to improve learning outcomes, engagement and academic achievement in higher education environments. The study compares trends of AI use across institutions and explores how different institutions access, implement, and support the outcomes of AI use by learners. The research design is mixed-methods, which includes quantitative data from academic performance analysis tools and learning management systems as well as qualitative data collected from structured interviews with students and teacher participants. The results show significant differences in the use of AI learning systems; in the case of high resourcing institutions, the advanced technological infrastructure, institutional readiness and digital competency of professors are reflected, whereas low resourcing institutions face difficulties like limited technological infrastructure and support, weak funding, and lack of digital competency. However, AI-powered Personalised learning systems have helped to enhance the efficiency of learning, tailor content to individual learners, offer immediate feedback, and facilitate self-paced learning, despite these limitations. Moreover, learner satisfaction is a complex attitude; while in higher-level institutions, the value they place on system adaptability and performance analysis is present, in others, accessibility and ease of use, although limited in terms of technology, is highlighted. The study suggests investing in AI infrastructure, educating faculty on AI and implementing ethical policies for AI education. The results underscore the diverse effects of AI personalization on different institutions and its capacity to boost equity, efficiency, and student-centered learning. The analysis provides insights for policy makers, educational and instructional practitioners, and developers, and educates researchers in educational technology and helps to facilitate the sustainable application of AI in higher education.
Keywords: Artificial Intelligence, Personalized Learning Systems, Higher Education, Educational Technology, Adaptive Learning, Student Performance, AI in Education, Learning Analytics, Digital Education, EdTech