Discerning the Incursion of AI-Generated Texts in Dissertations

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dc.contributor.authorAoued ,Khouloud
dc.contributor.authorBougamouza ,Fateh
dc.date.accessioned2024-10-24T07:21:54Z
dc.date.available2024-10-24T07:21:54Z
dc.date.issued2024
dc.description.abstractArtificial intelligence has revolutionized many industries, including academic research. With the emergence of AI-generated texts, researchers can now produce content with minimal human effort that appears high-quality but actually lacks the foundations of scientific research. However, the use of AI-generated texts in dissertations raises significant questions about their impact on research quality and integrity. In this work, we propose an approach to address both human-generated and AI-generated scientific texts in academic dissertations and theses. The ThesisGuard AI application aims to enhance academic integrity and quality while avoiding total and direct reliance on artificial intelligence, due to its impact on individual abilities and the limitations it imposes on intellectual creativity. This approach involves using AI to detect and analyze the authenticity of the texts in question.
dc.identifier.urihttp://dspace.univ-skikda.dz:4000/handle/123456789/2998
dc.language.isoen
dc.publisherFaculty of Sciences
dc.titleDiscerning the Incursion of AI-Generated Texts in Dissertations
dc.title.alternativeAdvanced Information System and Applications
dc.typeMasters degree Thesis
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