From AI Competence to Learning Competence: The Mediating Roles of Digital Literacy and Student Engagement
Description
Artificial intelligence (AI) is becoming an increasingly effective tool in education, providing new ways to reinforce learning experiences. The study aims to explore the role of AI competence in enhancing learning competence among undergraduate students, with the mediating role of digital literacy and student engagement. 7,020 undergraduate students from the University of Sargodha's Faculty of Social Sciences made up the study's population. The sample size was 278 based on a simple random sampling procedure. The researcher made in-person visits to gather data. SmartPLS was used for structural equation modeling (SEM) and mediation analysis, whereas SPSS was used for descriptive statistics. The findings of the study revealed that AI competency is a significant predictor of the digital literacy, student engagement and learning competence of university students. AI competency enhances teachers’ digital literacy, which in turn improves undergraduate learning competence. Furthermore, student engagement significantly partially mediated the relationship between digital literacy and student engagement.
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The study was based on positivist doctrine, which is associated with a quantitative approach and bases knowledge claims on objectivity, standardization, logical reasoning, and guidelines within the research process [50,51]. Undergraduate students were asked to complete a standardized questionnaire. A structured questionnaire included a total of 66 items associated with AI use (16 items), learning competence (16 items), student engagement (20 items) and digital literacy (14 items). Demographic variables such as gender, the program and the semester were included. The population of the study included undergraduate students of the faculty of social science from the University of Sargodha (7020) distributed across the departments of Education (1253), Social Work (428), Psychology (890), History and Pakistan Studies (340), Economics (600), Business (1200), Sociology & Criminology (763) and Political Science (1016). The choice of this faculty was guided by the growing use of AI tools for writing, research, and the analytical tasks that characterize social science education. To choose participants from the target population, this study used a simple random selection procedure. Simple random sampling reduces sampling bias by giving each member of the population an equal and independent probability of being chosen [52]. The sampling frame was the official academic records of the university, which included all the undergraduate students enrolled in each of the nine departments. Each student was assigned a unique number that ranged from 1 to 7020. A random number generator function of Excel was then used to choose 278 students from the population. Each undergraduate student had the same and independent probability of being selected, irrespective of their department, gender or degree. To maintain the required sample size, students who were selected but refused to participate were replaced by a random selection of replacement students from the same sampling frame.
Institutions
- University of SargodhaPunjab, Sargodha