Application of A.I IN HIGHER EDUCATION

  • Unique Paper ID: 183325
  • PageNo: 1010-1014
  • Abstract:
  • This research aims to reframe the discussion around AI in higher education, emphasizing its potential to create a more adaptive and student-centred learning environment. The focus will be on: • Personalization through AI: Examining how AI can analyse student data (learning styles, strengths, weaknesses) to personalize educational experiences. • Adaptive Learning Systems: Investigating how AI-powered platforms adjust learning content and difficulty based on student performance. • Optimizing Learning Pathways: Exploring how AI can recommend courses, resources, and support systems tailored to individual student goals. The report will address: • Benefits: Improved learning outcomes, increased student engagement, and support for diverse learning styles. • Limitations: Potential biases in data analysis, need for human oversight, and ensuring equitable access to AI-powered tools.

Copyright & License

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.

BibTeX

@article{183325,
        author = {DEEPAK KUMAR},
        title = {Application of A.I IN HIGHER EDUCATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {1010-1014},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183325},
        abstract = {This research aims to reframe the discussion around AI in higher education, emphasizing its potential to create a more adaptive and student-centred learning environment.
The focus will be on:
•	Personalization through AI: Examining how AI can analyse student data (learning styles, strengths, weaknesses) to personalize educational experiences.
•	Adaptive Learning Systems: Investigating how AI-powered platforms adjust learning content and difficulty based on student performance.
•	Optimizing Learning Pathways: Exploring how AI can recommend courses, resources, and support systems tailored to individual student goals.

The report will address:
•	Benefits: Improved learning outcomes, increased student engagement, and support for diverse learning styles.
•	Limitations: Potential biases in data analysis, need for human oversight, and ensuring equitable access to AI-powered tools.},
        keywords = {},
        month = {August},
        }

Cite This Article

KUMAR, D. (2025). Application of A.I IN HIGHER EDUCATION. International Journal of Innovative Research in Technology (IJIRT), 12(3), 1010–1014.

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