Design of AI-Based Real-Time Lecture Feedback Analysis Systems in Nasarawa State University, Keffi, Nasarawa State
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Background of the Study
The importance of student feedback in shaping the teaching and learning process cannot be overstated. Traditionally, feedback is collected from students at the end of the semester, but this timing limits the ability to address issues in real-time. With the advent of artificial intelligence (AI), it is now possible to develop real-time feedback systems that provide instant analysis of student input, enabling lecturers to adjust their teaching methods during the course (Raj & Sharma, 2023). AI-based systems can aggregate, analyze, and interpret feedback from students regarding the lecture content, teaching methods, and classroom environment, allowing for immediate improvements in teaching quality.
At Nasarawa State University, Keffi, the implementation of an AI-based real-time feedback analysis system could help lecturers monitor student satisfaction and make necessary adjustments throughout the semester. By automating the feedback analysis process, AI can provide valuable insights more efficiently and in a manner that is both comprehensive and actionable (Ahmed & Ali, 2024). This study will focus on the design and implementation of such a system, assessing its effectiveness in improving student engagement and overall lecture quality.
Statement of the Problem
In Nasarawa State University, Keffi, student feedback is often collected through surveys or paper forms at the end of the semester, which limits its utility for real-time improvements. Lecturers are unable to address concerns or adjust their teaching methods immediately based on feedback, resulting in missed opportunities for enhancement. This study aims to investigate the feasibility and effectiveness of an AI-based system for real-time feedback analysis, with the potential to improve teaching methods and student satisfaction during the course.
Objectives of the Study
- To design and implement an AI-based real-time lecture feedback analysis system for Nasarawa State University, Keffi.
- To evaluate the effectiveness of the AI system in providing real-time insights into student satisfaction and course engagement.
- To assess the impact of AI-based feedback analysis on improving teaching quality and student learning outcomes.
Research Questions
- How effective is the AI-based real-time feedback system in analyzing student input and providing actionable insights to lecturers?
- What impact does the AI-based feedback system have on student engagement and course satisfaction?
- What are the challenges and benefits of implementing AI-based real-time feedback analysis systems in Nigerian universities?
Research Hypotheses
- The AI-based real-time feedback system provides more accurate and timely insights into student satisfaction compared to traditional methods.
- Lecturers who use the AI-based real-time feedback system improve their teaching quality and student engagement compared to those who do not.
- The implementation of AI-based feedback analysis faces challenges such as system integration and faculty resistance to new technologies.
Significance of the Study
The study will contribute to improving the teaching and learning environment at Nasarawa State University, Keffi, by introducing a real-time feedback system powered by AI. The insights gained will inform future implementations of similar systems in Nigerian universities and improve the overall quality of education.
Scope and Limitations of the Study
This research will focus on the design and implementation of the AI-based real-time lecture feedback analysis system at Nasarawa State University, Keffi. The study will be limited to a selected group of undergraduate courses and will not include postgraduate programs or courses outside the chosen scope.
Definitions of Terms
AI-Based Feedback Analysis: The use of artificial intelligence to collect, process, and interpret student feedback in real-time.
Real-Time Feedback: Immediate student input on various aspects of the lecture that can be used for ongoing improvements.
Teaching Quality: The effectiveness of lecturers in delivering content and engaging students in the learning process.
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