AI-Driven Exam Grading, Percentile Calculation, and Plagiarism Detection System for Educational Integrity

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 16 | 01 | Page :
    By

    Tajjuddin Malnas,

  • Prasanna Pandhare,

  • Divyank Panwar,

  • Sphurti Deshmukh,

  1. Student, Department Information Technology, Pimpri Chinchwad College of Engineering Pune, Maharashtra, India
  2. Student, Department Information Technology, Pimpri Chinchwad College of Engineering Pune, Maharashtra, India
  3. Student, Department Information Technology, Pimpri Chinchwad College of Engineering Pune, Maharashtra, India
  4. Assistant Professor, Department Information Technology, Pimpri Chinchwad College of Engineering Pune, Maharashtra, India

Abstract

The influence of artificial intelligence (AI) on academic evaluation has become increasingly significant, particularly in areas such as automated grading, large-scale content analysis, and plagiarism detection. These technologies provide educators with rapid processing, consistent scoring, and timely feedback that can support both teaching and learning. However, alongside these advantages, serious concerns have emerged regarding the reliability and fairness of AI-driven assessments. The growing presence of AI-generated content has further complicated the evaluation process, often leading to false positives, misclassification, and questionable judgments about academic integrity. These issues highlight the ethical challenges educators face when relying solely on automated systems. Therefore, a more balanced and responsible approach is essential—one that blends human expertise with the analytical power of AI. Such a hybrid framework can help reduce errors, improve transparency, and maintain accountability within academic environments. By combining human judgment with technological efficiency, institutions can promote a more reliable, ethical, and high-quality assessment process, ensuring that AI- supported educational tools genuinely enhance learning rather than compromise it.

Keywords: AI-powered education, grading, academic integrity, plagiarism detection, hybrid framework, ethical educational, AI content, human-AI collaboration, content analysis, human insights, misclassification.

How to cite this article:
Tajjuddin Malnas, Prasanna Pandhare, Divyank Panwar, Sphurti Deshmukh. AI-Driven Exam Grading, Percentile Calculation, and Plagiarism Detection System for Educational Integrity. Current Trends in Information Technology. 2025; 16(01):-.
How to cite this URL:
Tajjuddin Malnas, Prasanna Pandhare, Divyank Panwar, Sphurti Deshmukh. AI-Driven Exam Grading, Percentile Calculation, and Plagiarism Detection System for Educational Integrity. Current Trends in Information Technology. 2025; 16(01):-. Available from: https://journals.stmjournals.com/ctit/article=2025/view=232416


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Ahead of Print Subscription Original Research
Volume 16
01
Received 19/05/2025
Accepted 16/09/2025
Published 17/11/2025
Publication Time 182 Days
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