ARTIFICIAL INTELLIGENCE-POWERED SELF-REGULATED LEARNING AND BUSINESS EDUCATION UNDERGRADUATE STUDENTS’ ACADEMIC PERFORMANCE IN TERTIARY INSTITUTIONS IN AKWA IBOM STATE, NIGERIA

Samuel David Udo, PhD, Emmanuel Akpanobong Uyai, PhD, Samuel Ekoh Enyema

Abstract


 

This study investigated the relationship between artificial intelligence-powered self-regulated learning and the academic performance of Business Education undergraduate students in tertiary institutions in Akwa Ibom State. Self-regulated learning strategies studied were self-evaluation and goal setting. The dependent variable is academic performance, measured using students' Grade Point Average (GPA). Two research questions and two null hypotheses were stated to guide the study. The ex-post facto research design was employed for the study. The population of this study comprises 492 Business Education undergraduate students from the 2023/2024 academic year at the two tertiary institutions selected for the study. The purposive sampling technique was employed to select 114 Business Education undergraduate students from the study's population. A researcher-designed instrument titled “AI-Powered Self-Regulated Learning and Business Education Undergraduate Students’ Academic Performance Questionnaire” (AIPSRLBEUSAPQ) was used for data collection. The instrument was face validated by three experts. The reliability of the instrument was ascertained using the test-retest method, and Cronbach's Alpha was used to determine the reliability of the instrument, yielding a value of .80. Simple linear regression was employed to answer research questions and test the null hypotheses at a .05 level of significance. The study's findings revealed that AI-generated self-evaluation and AI-generated goal setting have weak positive relationships with students' academic performance. The study concludes that students are not engaging in self-directed learning effectively. The study recommends that lecturers should endeavour to utilise instructional techniques that arouse and maintain student interests in classrooms and taught content. This will support self-regulated learning with the aid of Artificial Intelligence.

Keywords: Artificial Intelligence, Self-Regulated Learning, Business Education, Academic Performance.

 


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