Implementation of Automated Speech Recognition for Enhancing Learning in Universities: A Case Study of Modibbo Adama University, Yola (Yola North LGA, Adamawa State)
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Background of the Study
Automated Speech Recognition (ASR) is a technology that converts spoken language into text, enabling more interactive and accessible learning experiences. Modibbo Adama University in Yola, Adamawa State, provides various programs that could benefit from ASR technology, particularly in enhancing lecture delivery, supporting students with disabilities, and promoting more efficient note-taking. Integrating ASR into the learning process could improve both engagement and retention.
This study aims to explore how ASR can be implemented to enhance learning experiences at Modibbo Adama University, focusing on its applications in classrooms, e-learning platforms, and accessibility features for students with special needs.
Statement of the Problem
Despite the growing popularity of e-learning and online education, there remains a gap in accessibility for students, particularly those with hearing impairments or language barriers. Existing methods of content delivery may not be as inclusive or interactive as they could be. Automated Speech Recognition (ASR) could play a crucial role in bridging this gap, but its application and effectiveness at Modibbo Adama University have yet to be studied.
Objectives of the Study
1. To investigate the potential benefits of implementing ASR technology in the learning environment at Modibbo Adama University.
2. To assess the effectiveness of ASR in enhancing lecture accessibility, note-taking, and student engagement.
3. To identify challenges and limitations in implementing ASR technology in the university setting.
Research Questions
1. How can Automated Speech Recognition be integrated into learning platforms at Modibbo Adama University?
2. What impact does ASR technology have on student engagement and learning outcomes?
3. What are the key challenges in implementing ASR in the university's learning environments?
Research Hypotheses
1. The implementation of Automated Speech Recognition will significantly improve the accessibility and engagement of students at Modibbo Adama University.
2. Students using ASR technology will show better retention and understanding of lecture materials.
3. The main challenges to implementing ASR will include technical issues, such as the accuracy of speech recognition and resistance to technology adoption.
Significance of the Study
This study will contribute to the growing body of research on using ASR in higher education. It will provide insights into how universities like Modibbo Adama University can integrate ASR to improve accessibility, support students with disabilities, and enhance the overall learning experience. The findings could inform similar initiatives at other institutions.
Scope and Limitations of the Study
The study will focus on the integration of ASR technology in lecture environments at Modibbo Adama University, particularly for courses with significant oral communication components. Limitations include potential technical issues with speech recognition software and challenges in obtaining accurate data on student outcomes.
Definitions of Terms
• Automated Speech Recognition (ASR): Technology that converts spoken language into written text, allowing for more interactive learning experiences.
• E-learning: A mode of education where learning materials and lectures are delivered via electronic media, often online.
• Accessibility: The design of learning experiences that are accessible to all students, including those with disabilities.
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