Implementation of AI-Based Plagiarism Detection in Online Assignment Submissions for Universities in Katsina Local Government Area, Katsina State
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- NGN 5000
Background of the Study
Academic integrity is crucial in higher education, and the rise of online learning platforms has brought with it an increase in plagiarism among students. In Katsina Local Government Area, Katsina State, universities are embracing e-learning as a means of offering flexible learning opportunities. However, the challenge of ensuring academic honesty in online assignments has become a significant concern. AI-based plagiarism detection tools can play a vital role in identifying instances of plagiarism and ensuring that students submit original work.
AI algorithms, particularly those based on natural language processing (NLP) and machine learning, have proven to be effective in detecting various forms of plagiarism, including paraphrasing, text similarity, and source-based copying. This study focuses on the implementation of an AI-based plagiarism detection system for online assignment submissions in universities in Katsina Local Government Area. The goal is to develop and assess the effectiveness of such a system in maintaining academic integrity in online learning environments.
Statement of the Problem
Universities in Katsina Local Government Area, Katsina State, face significant challenges in ensuring the authenticity and originality of online assignments submitted by students. The use of traditional plagiarism detection tools is often inadequate, as they may fail to detect more sophisticated forms of plagiarism. The increasing reliance on e-learning platforms necessitates the integration of more advanced AI-based tools capable of accurately identifying plagiarism in various forms. However, the implementation and effectiveness of such systems in the local context remain underexplored.
Objectives of the Study
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To design and implement an AI-based plagiarism detection system for online assignment submissions in universities in Katsina Local Government Area, Katsina State.
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To assess the effectiveness of the AI-based system in detecting various forms of plagiarism.
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To evaluate the impact of the AI-based plagiarism detection system on academic integrity in online learning environments.
Research Questions
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How feasible is the implementation of an AI-based plagiarism detection system in universities in Katsina Local Government Area, Katsina State?
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What impact does the AI-based plagiarism detection system have on the detection of various forms of plagiarism in online assignments?
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How does the implementation of the AI-based plagiarism detection system influence academic integrity in online learning environments?
Research Hypotheses
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The implementation of an AI-based plagiarism detection system improves the accuracy of plagiarism detection in online assignments.
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The AI-based plagiarism detection system enhances academic integrity by reducing instances of plagiarism in online assignments.
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The implementation of an AI-based plagiarism detection system has a positive impact on the overall quality of online assignments submitted by students.
Significance of the Study
This study will provide insights into the effectiveness of AI-based plagiarism detection tools in enhancing academic integrity in online learning environments. The findings will be useful for universities in Katsina Local Government Area, Katsina State, and other institutions facing similar challenges in maintaining academic honesty in e-learning platforms.
Scope and Limitations of the Study
The study will focus on the design and implementation of an AI-based plagiarism detection system for online assignments in universities in Katsina Local Government Area, Katsina State. Limitations may include the technological requirements for implementing the AI system and challenges related to training both students and faculty to use the system effectively.
Definitions of Terms
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Plagiarism Detection: The process of identifying instances where students have copied or improperly cited work from others.
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AI-Based System: A system that utilizes artificial intelligence algorithms, such as machine learning and natural language processing, to perform tasks such as plagiarism detection.
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Academic Integrity: The adherence to ethical standards in academic work, including honesty and originality in assignments and examinations.
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