Optimization of AI-Based Adaptive Testing Models for University Entrance Examinations in Modibbo Adama University, Yola, Adamawa State
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- NGN 5000
Background of the Study
University entrance examinations are critical in determining the academic readiness of students and their eligibility for higher education. Traditional entrance exams often rely on fixed question sets, which may not effectively assess the diverse abilities of students. Adaptive testing, on the other hand, adjusts the difficulty of questions based on a student's performance, providing a more personalized and accurate measure of their abilities. Artificial intelligence (AI) has made it possible to create adaptive testing systems that can analyze student responses in real time and adjust the question difficulty dynamically. This study explores the implementation of an AI-based adaptive testing model for university entrance examinations at Modibbo Adama University, Yola, Adamawa State, with the goal of improving the fairness and effectiveness of the assessment process.
Statement of the Problem
At Modibbo Adama University, university entrance examinations often follow a one-size-fits-all approach, which may not accurately reflect each candidate's capabilities. The existing fixed-question exam format does not consider the varying levels of preparedness among applicants, which can lead to unfair assessment outcomes. AI-based adaptive testing models can offer a more tailored and accurate way of assessing students by adjusting the difficulty of the exam based on individual responses. However, the application of AI in adaptive testing for university entrance exams has not been fully explored in this context. This study aims to develop and evaluate an AI-based adaptive testing model that can enhance the fairness and accuracy of entrance examinations at the university.
Objectives of the Study
1. To design and implement an AI-based adaptive testing model for university entrance examinations at Modibbo Adama University.
2. To evaluate the effectiveness of the AI-based adaptive testing model in assessing student abilities more accurately compared to traditional fixed-question formats.
3. To assess the feasibility of implementing AI-based adaptive testing models for university entrance examinations in the context of Modibbo Adama University.
Research Questions
1. How accurate is the AI-based adaptive testing model in assessing the academic abilities of university entrance examination candidates?
2. How does the AI-based adaptive testing model compare with traditional fixed-question exam formats in terms of fairness and accuracy?
3. What is the level of acceptance among students and faculty regarding the use of AI in entrance examination testing?
Research Hypotheses
1. The AI-based adaptive testing model will more accurately assess student abilities compared to traditional fixed-question formats.
2. The AI-based system will provide a more fair and personalized assessment for university entrance exam candidates.
3. Students and faculty will have a high level of acceptance regarding the use of AI-based adaptive testing for university entrance examinations.
Significance of the Study
This study will contribute to the advancement of AI-based solutions in educational assessments, particularly for university entrance exams. The implementation of adaptive testing models could improve the fairness, accuracy, and efficiency of entrance examinations at Modibbo Adama University, leading to better outcomes in student selection.
Scope and Limitations of the Study
The study will focus on the design, implementation, and evaluation of an AI-based adaptive testing model for university entrance examinations at Modibbo Adama University, Yola, Adamawa State. Limitations include the availability of data for training the AI model and the potential resistance to adopting AI-based testing methods among stakeholders.
Definitions of Terms
• AI-Based Adaptive Testing: A testing approach that uses artificial intelligence to dynamically adjust the difficulty of questions based on a student's performance during the exam.
• University Entrance Examination: A standardized test used to assess the academic preparedness of students seeking admission to a university.
• Adaptive Testing: A form of assessment that adjusts the difficulty of test questions based on the examinee's previous responses, offering a personalized assessment experience.
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