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1719369PublishedVol 10 · Issue 1

AI-Based Student Performance Prediction System

KM Richa Verma Dr. Abdul Majid Farooqi

Subject area: Science,Engineering and Technology  ·  Area of research: Student Performance Prediction System

DOI: https://doi.org/10.64388/IREV10I1-1719369

Abstract

Educational institutions generate a significant amount of student-related data, including attendance records, examination scores, assignment performance, and participation in academic activities. However, much of this data remains underutilized in identifying students who may face academic difficulties in the future.

How to cite this paper

KM Richa Verma, Dr. Abdul Majid Farooqi "AI-Based Student Performance Prediction System" Iconic Research And Engineering Journals Volume 10 Issue 1 2026 Page 281-283 https://doi.org/10.64388/IREV10I1-1719369
KM Richa Verma, Dr. Abdul Majid Farooqi "AI-Based Student Performance Prediction System" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026, doi: https://doi.org/10.64388/IREV10I1-1719369
KM Richa Verma, Dr. Abdul Majid Farooqi (2026). AI-Based Student Performance Prediction System. Iconic Research And Engineering Journals, 10(1). doi: https://doi.org/10.64388/IREV10I1-1719369
KM Richa Verma, Dr. Abdul Majid Farooqi "AI-Based Student Performance Prediction System" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026. Crossref, https://doi.org/10.64388/IREV10I1-1719369
@article{1719369,
      author = {KM Richa Verma, Dr. Abdul Majid Farooqi},
      title = {AI-Based Student Performance Prediction System},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {281-283},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719369.pdf},
      abstract = {Educational institutions generate a significant amount of student-related data, including attendance records, examination scores, assignment performance, and participation in academic activities. However, much of this data remains underutilized in identifying students who may face academic difficulties in the future.},
      month = {July},
      doi = {https://doi.org/10.64388/IREV10I1-1719369}
  }