Implementation of AI-Based Automatic Question Generation for Online Assessments: A Case Study of Federal University, Lafia (Lafia LGA, Nasarawa State)
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Background of the Study
In the digital age, online assessments have become increasingly popular in universities due to their convenience, scalability, and the ability to reach a larger student population. However, the challenge lies in ensuring that the questions remain dynamic, varied, and aligned with learning outcomes. Traditional methods of creating assessment questions can be time-consuming and prone to bias, particularly as universities adopt blended or fully online learning environments. The need for automated systems that can generate relevant, high-quality questions for assessments has emerged.
AI-based automatic question generation (AQG) systems use natural language processing (NLP) and machine learning (ML) techniques to automatically generate relevant questions from given text, course material, or textbooks. Such systems can significantly reduce the time required to prepare assessments while maintaining the quality and variety of the questions. In addition, the use of AI can lead to personalized and adaptive learning experiences where students are assessed on their understanding of specific topics.
Federal University, Lafia, located in Lafia LGA, Nasarawa State, seeks to enhance its online assessment practices by integrating AI-based question generation systems. This study will explore the development and implementation of an AI-based automatic question generation system at the university and its impact on the quality and efficiency of online assessments.
Statement of the Problem
At Federal University, Lafia, online assessments often rely on manually crafted questions, which are time-consuming to produce and lack the diversity needed to fully assess students' knowledge. Additionally, as student numbers grow and course content expands, maintaining question quality and variety becomes even more difficult. This issue highlights the need for an automated system that can generate questions efficiently, ensuring both variety and relevance to the learning objectives. This study will investigate the feasibility of implementing AI-based automatic question generation in the context of online assessments at the university.
Objectives of the Study
1. To design and implement an AI-based automatic question generation system for online assessments at Federal University, Lafia.
2. To evaluate the quality and relevance of the questions generated by the AI system in comparison to manually created questions.
3. To assess the impact of AI-generated questions on the efficiency of online assessment processes.
Research Questions
1. How effective is the AI-based automatic question generation system in producing high-quality assessment questions?
2. How does the quality of AI-generated questions compare to those created manually by lecturers?
3. What impact does the use of AI-based question generation have on the efficiency of online assessments at Federal University, Lafia?
Research Hypotheses
1. The AI-based automatic question generation system will produce questions of similar quality to those created manually by lecturers.
2. The AI system will significantly improve the efficiency of online assessment creation at Federal University, Lafia.
3. The AI-generated questions will effectively assess the learning outcomes and knowledge of students.
Significance of the Study
This study will provide valuable insights into the use of AI for automating question generation in higher education. By evaluating the effectiveness of such a system, the research will help Federal University, Lafia, enhance the quality of its online assessments while improving efficiency. The findings will contribute to the broader discussion on the integration of AI in academic practices, offering a potential model for other universities seeking to adopt similar systems.
Scope and Limitations of the Study
The study will focus on the implementation of an AI-based automatic question generation system at Federal University, Lafia, located in Lafia LGA, Nasarawa State. The research will assess the quality, relevance, and efficiency of the generated questions in the context of online assessments. Limitations include potential challenges in data collection and the system’s ability to handle diverse course materials and subject areas.
Definitions of Terms
• Automatic Question Generation (AQG): The process of using AI algorithms to generate relevant and diverse assessment questions based on given content.
• Natural Language Processing (NLP): A branch of AI that focuses on the interaction between computers and human language.
• Online Assessment: An evaluation method where students complete exams or assignments electronically, often using a learning management system (LMS).
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