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BELT: Bluejeans codE Leak deTection

Published: 12 August 2020 Publication History

Abstract

As online educational programs scale, monitoring peer collaboration in platforms like BlueJeans for plagiarism becomes difficult. Recent studies indicate that students are less likely to cheat if presented with direct warning messages prior to engaging in online activities. In this work, we present Bluejeans codE Leak deTection (BELT), a system that monitors online BlueJeans meetings for shared code and sends timely warning messages to meeting participants. To test BELT's robustness as an online proctor, we evaluate its code-text disambiguation, code detection from images of varying quality, and code detection from videos of varying resolution. We conclude this work by pinpointing areas of improvement and briefly discuss possible extensions for future work.

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MP4 File (3386527.3406727.mp4)
As online educational programs scale, monitoring peer collaboration in platforms like BlueJeans for plagiarism becomes\r\ndifficult. Recent studies indicate that students are less likely to cheat if presented with direct warning messages prior to engaging in online activities. In this talk, we present Bluejeans codE Leak deTection (BELT), a system that monitors online BlueJeans meetings for shared code and sends timely warning messages to meeting participants. We show a demo of BELT in action and conclude the presentation by discussing next steps for this work in progress.

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Cited By

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  • (2023)A systemic model of academic (mis)conduct to curb cheating in higher educationHigher Education10.1007/s10734-023-01077-x87:5(1529-1549)Online publication date: 19-Jul-2023
  • (2022)On the necessity (or lack thereof) of digital proctoring: Drawbacks, perceptions, and alternativesJournal of Computer Assisted Learning10.1111/jcal.1270038:5(1482-1496)Online publication date: 26-Jun-2022
  • (2021)Source Code Plagiarism Detection in an Educational Context: A Literature Mapping2021 IEEE Frontiers in Education Conference (FIE)10.1109/FIE49875.2021.9637155(1-9)Online publication date: 13-Oct-2021

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L@S '20: Proceedings of the Seventh ACM Conference on Learning @ Scale
August 2020
442 pages
ISBN:9781450379519
DOI:10.1145/3386527
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2020

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Author Tags

  1. moocs
  2. online learning
  3. online meeting
  4. plagiarism
  5. programming language detection

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L@S '20

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Overall Acceptance Rate 117 of 440 submissions, 27%

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Cited By

View all
  • (2023)A systemic model of academic (mis)conduct to curb cheating in higher educationHigher Education10.1007/s10734-023-01077-x87:5(1529-1549)Online publication date: 19-Jul-2023
  • (2022)On the necessity (or lack thereof) of digital proctoring: Drawbacks, perceptions, and alternativesJournal of Computer Assisted Learning10.1111/jcal.1270038:5(1482-1496)Online publication date: 26-Jun-2022
  • (2021)Source Code Plagiarism Detection in an Educational Context: A Literature Mapping2021 IEEE Frontiers in Education Conference (FIE)10.1109/FIE49875.2021.9637155(1-9)Online publication date: 13-Oct-2021

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