Enhancing Academic Integrity in Universities Using AI-Based Anti-Plagiarism Software: A Case Study of Kaduna State University (Kaduna North LGA, Kaduna State)
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- NGN 5000
Background of the Study
Academic integrity is a core principle that ensures the credibility and quality of education at universities. Plagiarism, the act of using someone else’s work without proper citation, undermines academic integrity and distorts the fairness of the educational system (Gundogan et al., 2023). With the rapid growth of digital content and online resources, plagiarism detection has become a challenge for universities worldwide. Traditional manual detection methods are often insufficient and time-consuming, prompting the need for automated, efficient solutions. AI-based anti-plagiarism software, utilizing machine learning algorithms and natural language processing (NLP), offers a promising solution by automatically scanning and comparing student submissions against a vast database of academic papers, journals, and online content (Onyeka & Eze, 2024). This technology not only detects instances of plagiarism but also provides detailed reports, helping instructors maintain academic honesty and prevent cheating.
At Kaduna State University, located in Kaduna North LGA, Kaduna State, the academic community faces challenges with maintaining academic integrity due to the increasing ease of accessing and copying content online. This study aims to assess the effectiveness of AI-based anti-plagiarism software in improving academic integrity by providing an automated solution for detecting plagiarism in students' works.
Statement of the Problem
Plagiarism has become a widespread issue at Kaduna State University, particularly with the rise of internet usage among students. Traditional plagiarism detection methods rely heavily on manual checking, which can be inefficient and inconsistent. The university needs a more effective and efficient system to ensure academic honesty. AI-based anti-plagiarism software provides a potential solution, but its effectiveness in identifying plagiarism in the university context has not been fully explored.
Objectives of the Study
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To assess the effectiveness of AI-based anti-plagiarism software in detecting instances of plagiarism at Kaduna State University.
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To evaluate the impact of AI-based anti-plagiarism software on the academic integrity of the university.
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To examine how AI-based plagiarism detection systems can streamline the academic evaluation process at Kaduna State University.
Research Questions
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How effective is AI-based anti-plagiarism software in detecting plagiarism in student submissions at Kaduna State University?
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What impact does the use of AI-based anti-plagiarism software have on academic integrity at the university?
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How can AI-based plagiarism detection systems streamline the academic review process?
Significance of the Study
This study will contribute valuable insights into how AI can be used to enhance academic integrity by effectively detecting plagiarism. The findings could influence the adoption of AI-based systems in other universities, leading to a more efficient and transparent educational system.
Scope and Limitations of the Study
The study will focus on evaluating the effectiveness of AI-based anti-plagiarism software at Kaduna State University, located in Kaduna North LGA, Kaduna State. The research will specifically examine how well the software detects plagiarism in student academic work, excluding other areas of academic integrity.
Definitions of Terms
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AI-Based Anti-Plagiarism Software: Automated tools that use artificial intelligence to scan academic works for similarities with existing content, helping to identify plagiarism.
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Academic Integrity: The adherence to ethical standards in education, including honesty, fairness, and transparency in academic work.
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Plagiarism: The act of using someone else's work, ideas, or expressions without proper acknowledgment, constituting an unethical practice in academia.
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