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{174654,
        author = {P.DEVENDRA BABU},
        title = {Unveiling Patterns in Student Achievement Using K-Medoids Clustering},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {177-181},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174654},
        abstract = {In this research, the K-Medoids clustering algorithm is used to investigate student performance from information about grades, attendance, and participation in extracurricular activities. Three different clusters were identifier: Cluster 1 of high performing academics who also have good attendance, Cluster 2 of average performing students with poor attendance, and Cluster 3 low performing academics with high participation in extracurricular activities. The K-Medoids algorithm was used due to its outlier robustness to form accurate clusters.},
        keywords = {Student interest model; K-medoids clustering algorithm: Student performance model; segmentation of patterns},
        month = {March},
        }