Paper Title: An Analytical Study on AI-Based Intelligent Tutoring Systems for Personalised Learning of Mensuration at the Secondary Level
Author:
Abstract:
The integration of Artificial Intelligence (AI) into educational environments has attracted growing scholarly attention in recent years because of its potential to reshape traditional teaching–learning processes. One of the most significant applications of AI in education is the development of Intelligent Tutoring Systems (ITS), which are capable of providing adaptive instruction and supporting personalised learning experiences for students. In mathematics education, particularly at the secondary level, learners frequently encounter difficulties because many mathematical concepts are abstract in nature. Mensuration, which deals with the measurement of geometric figures such as area, surface area, and volume, is one such topic that often poses challenges for students. These difficulties frequently arise from the need for spatial reasoning and conceptual understanding rather than simple procedural knowledge. The present analytical study explores the potential role of AI-based Intelligent Tutoring Systems in facilitating personalised learning of mensuration among secondary school students. Drawing upon existing literature related to AI in education, personalised learning environments, and mathematics pedagogy, the study examines how AI-driven systems may support learners by identifying misconceptions, adapting instructional pathways, and providing interactive feedback. The study also discusses the pedagogical considerations involved in integrating AI technologies within secondary mathematics classrooms. The analysis indicates that AI-based tutoring systems have considerable potential to strengthen conceptual understanding, enhance student engagement, and support individualised instruction in mathematics learning. Recent research further suggests that AI-supported adaptive learning environments can meaningfully improve students’ conceptual mastery and engagement in mathematics learning contexts (Zawacki-Richter et al., 2019; Holmes et al., 2022). The study concludes that AI-supported learning environments can significantly contribute to improving students’ understanding of mensuration concepts when they are implemented alongside sound pedagogical practices and appropriate curriculum alignment.
Keywords:Artificial Intelligence (AI), Intelligent Tutoring Systems (ITS), Personalised Learning, Mathematics Education, Mensuration.
DOI Link – https://doi.org/10.63431/AIJITR/3.I.2026.124-128
Review By – Dr. Amit Adhikari and Dr. Rajib Sinha