Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{207730,
        author = {Dr.R.VIJAYAPRIYA and M.S.SIVASANKARAN},
        title = {ROLE OF AI-BASED LEARNING TOOLS IN IMPROVING STUDENTS’ ACADEMIC PERFORMANCE IN THE NILGIRIS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {2540-2546},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207730},
        abstract = {Higher education serves as an important platform for students to acquire specialised knowledge, develop employability skills, and strengthen their intellectual abilities. AI technology enables computer systems to perform tasks that require human-like intelligence, such as learning, reasoning, problem-solving, and decision-making. AI-based learning tools support students through personalised learning, instant feedback, and easy access to academic resources. Their effective use can enhance learning efficiency, engagement, knowledge retention, and overall academic performance. AI-based learning tools are increasingly used by Arts and Science students to support learning, academic activities, and knowledge acquisition. However, their effectiveness in improving students’ academic performance may vary depending on usage patterns, awareness, and learning needs. Therefore, this study aimed to examine the role of AI-based learning tools in improving the academic performance of Arts and Science students in The Nilgiris. The study adopted a descriptive research design and utilised both primary and secondary data. A sample of 213 Arts and Science students in The Nilgiris was selected using the simple random sampling technique. Primary data were collected through a structured questionnaire covering the students’ demographic profile, usage of AI-based learning tools, and academic performance. The questionnaire included closed-ended questions and five-point Likert scale statements related to students’ academic performance. The collected data were systematically coded and analysed using SPSS. Statistical tools such as percentage analysis, mean, standard deviation and Analysis of Variance (ANOVA) were employed to analyse the sample data. Null hypotheses were formulated to examine the significant differences in students’ academic performance with respect to selected AI-based learning tool usage variables. This study noticed from the study that the highest level of students’ academic performance is perceived by science students, UG students, 2nd year students, students using Chatbots, students using AI tools for academic research and students using AI tools for 1–2 hours per day.},
        keywords = {Artificial Intelligence, AI-Based Learning Tools, Academic Performance, Arts and Science Students, Higher Education, Student Engagement, Personalised Learning.},
        month = {August},
        }