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The ethics of AI technology in academic work: assessing the line between assistance and plagiarism

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 16 No. 2 (2026)

DOI
10.11591/ijece.v16i2.pp924-944
ISSN
2722-2578, 2088-8708
Published
2026-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The integration of artificial intelligence (AI) into academia has transformed educational practices and enhanced personalized learning and problem-solving capabilities. However, this raises significant ethical concerns regarding the balance between legitimate assistance and plagiarism. This study investigated public perceptions of AI in academic settings, focusing on its impact on effectiveness, dependency, and ethical considerations of AI use. A survey of 498 respondents from various educational roles was conducted, and the data were analyzed using SPSS for descriptive statistics, chi-square tests, and regression analyses. The results identified a significant correlation between people’s educational roles and their interaction with AI tools (χ2(6) = 16.488, p = 0.036), reflecting the diverse patterns of interaction within the academic community. More frequent use of AI was linked to less dependency (β = −0.298, p

Collaboration network of the authors

7 authors · 21 co-authorship links · 5 across different organisations

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  • American International University-Bangladesh
  • Multimedia University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref 
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>The ethics of AI technology in academic work: assessing the line between assistance and plagiarism</dc:title><dc:creator>Patwary, Md. Owafeeuzzaman</dc:creator><dc:creator>Islam, Md. Reazul</dc:creator><dc:creator>Islam, Abtahi</dc:creator><dc:creator>Khan, Nur-e Sarjina</dc:creator><dc:creator>Al–Jubair, Md. Abdullah</dc:creator><dc:creator>Hossen, Md. Jakir</dc:creator><dc:creator>Mridha, M. F.</dc:creator><dc:description>&lt;jats:p&gt;The integration of artificial intelligence (AI) into academia has transformed educational practices and enhanced personalized learning and problem-solving capabilities. However, this raises significant ethical concerns regarding the balance between legitimate assistance and plagiarism. This study investigated public perceptions of AI in academic settings, focusing on its impact on effectiveness, dependency, and ethical considerations of AI use. A survey of 498 respondents from various educational roles was conducted, and the data were analyzed using SPSS for descriptive statistics, chi-square tests, and regression analyses. The results identified a significant correlation between people’s educational roles and their interaction with AI tools (χ2(6) = 16.488, p = 0.036), reflecting the diverse patterns of interaction within the academic community. More frequent use of AI was linked to less dependency (β = −0.298, p &amp;amp;lt; 0.001), contradicting the widespread belief of over-reliance on AI. Age and educational role had limited explanatory value in perception of AI dependency issues (R2 = 0.033). The findings indicate a strong correlation between AI usage frequency and dependency levels, with increased exposure to AI fostering a more critical approach rather than a dependent one. Concerns regarding the unethical use of AI, inaccuracies in AI-generated content, and the need for clear institutional policies were also highlighted. This study underscores the importance of responsible AI integration, advocating for ethical frameworks and educational interventions to ensure that AI enhances learning without compromising academic integrity.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2026-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v16i2.pp924-944</dc:identifier><dc:identifier>10.11591/ijece.v16i2.pp924-944</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 16 No 2 (2026); 924</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/40244/18732</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>