Implementation of an AI-Based Examination Question Generator for Secondary Schools in Federal University Wukari, Taraba State
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Background of the Study
The generation of examination questions is a critical yet time-consuming aspect of the educational process in secondary schools. In response to the growing demand for efficiency and innovation, an AI-based examination question generator has been proposed for implementation in secondary schools associated with Federal University Wukari, Taraba State. This technology utilizes advanced natural language processing and machine learning algorithms to automatically create high-quality, diverse, and curriculum-aligned questions from a large corpus of educational content (Ibrahim, 2023). The use of AI in this capacity not only accelerates the question development process but also ensures consistency, fairness, and a reduced risk of human bias. By automating the generation of assessment items, educators can devote more time to instructional design and individualized student support (Nwankwo, 2024).
Moreover, the AI-based system is capable of tailoring questions to different difficulty levels, ensuring that assessments accurately reflect the range of student abilities. This dynamic approach supports differentiated instruction and can be instrumental in identifying learning gaps. The integration of AI into examination question generation represents a significant advancement over traditional manual methods, which are often labor-intensive and prone to inconsistencies. Recent studies have demonstrated that AI-generated questions can match or even exceed the quality of human-created assessments when properly calibrated (Okechukwu, 2025). Additionally, the system’s ability to continuously learn and adapt based on feedback ensures that it remains relevant and effective in a rapidly evolving educational landscape.
Despite its potential, the implementation of an AI-based question generator in secondary schools poses challenges related to system accuracy, data privacy, and teacher acceptance. The complexity of natural language processing, particularly in local contexts with diverse linguistic nuances, may affect the reliability of the generated questions. This study, therefore, aims to critically assess the feasibility, challenges, and benefits associated with deploying such a system in secondary schools, with a focus on improving assessment quality and educational outcomes (Ibrahim, 2023).
Statement of the Problem
The introduction of an AI-based examination question generator in secondary schools faces several critical challenges. One of the main issues is the complexity of ensuring that the generated questions are not only accurate but also contextually relevant and aligned with the curriculum (Ibrahim, 2023). In many instances, AI systems may struggle to capture local linguistic nuances and educational standards, leading to questions that do not accurately reflect the intended learning outcomes. Furthermore, there is apprehension among educators regarding the reliability of AI-generated content, as the technology may produce questions that vary significantly in difficulty or contain ambiguities (Nwankwo, 2024).
Additionally, concerns regarding data privacy and security have emerged, particularly with the need to handle sensitive student and educational data securely. The lack of robust regulatory frameworks to govern the use of AI in educational assessments further complicates the matter. Resistance from teachers, who may view the technology as a threat to their professional expertise, also poses a significant barrier to implementation (Okechukwu, 2025). These challenges underscore the need for a systematic evaluation of the AI-based system’s performance in real classroom settings. The study seeks to identify the key factors contributing to these challenges and propose strategies to mitigate them, ensuring that the technology is implemented in a manner that enhances rather than disrupts the assessment process (Ibrahim, 2023).
Objectives of the Study:
- To develop and implement an AI-based examination question generator tailored for secondary schools in Federal University Wukari.
- To evaluate the accuracy, relevance, and fairness of the generated examination questions.
- To identify challenges and recommend strategies for effective integration of AI in exam question generation.
Research Questions:
- How accurate and contextually relevant are the AI-generated examination questions compared to those developed manually?
- What challenges do educators face in adopting AI-based question generators?
- How can data privacy and system reliability be ensured in the implementation of the AI-based generator?
Significance of the Study
This study is significant as it investigates the practical application of AI in automating examination question generation for secondary schools, aiming to enhance assessment quality and efficiency. By addressing challenges related to accuracy, contextual relevance, and data security, the research provides valuable insights for educators and policymakers. The findings are expected to contribute to more reliable and fair assessment practices, ultimately improving educational outcomes and supporting the digital transformation of the examination process (Nwankwo, 2024).
Scope and Limitations of the Study:
This study is limited to the implementation and evaluation of an AI-based examination question generator in secondary schools in Federal University Wukari, Taraba State, and does not extend to other assessment technologies or educational levels.
Definitions of Terms:
- AI-Based Examination Question Generator: A system that uses artificial intelligence to automatically create exam questions from a predefined corpus of educational content (Ibrahim, 2023).
- Natural Language Processing (NLP): A branch of AI that focuses on the interaction between computers and human language, used here to generate exam questions (Nwankwo, 2024).
- Contextual Relevance: The degree to which generated exam questions align with local curriculum standards and linguistic nuances (Okechukwu, 2025).
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