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Academic integrity is a critical aspect of modern education, and detecting unethical practices such as cribbing or plagiarism has become a major challenge in digital learning environments. This paper presents a study on the cognizance (awareness and detection) of cribbing using data excavation techniques, also known as data mining. The proposed approach employs text mining, pattern recognition, and similarity analysis to identify instances of copied or suspicious content in academic submissions. By analyzing large datasets of student records, assignments, and examination scripts, the system extracts relevant features and applies algorithms such as cosine similarity, clustering, and classification to detect content overlap and behavioral patterns. The use of data excavation enables automated, efficient, and accurate cribbing detection, reducing manual efforts and enhancing academic transparency. Furthermore, the system can generate analytical reports to help educators understand trends in academic misconduct and implement preventive strategies. The proposed framework contributes to maintaining fairness and integrity in educational evaluation systems.
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Copyright © 2020, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: S. Phani Kumar, ph2in3856@sasi.ac.in
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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