Investigating the role of generative artificial intelligence literacy for learning in student engagement among distance education students

Within the scope of this study, the aim was to examine the role of generative artificial intelligence (AI) literacy for learning in student engagement among distance education students. Based on the purpose of the research, the study was conducted using a mixed-methods research design and carried out in three main stages: (1) identifying a framework for generative AI literacy for learning through a qualitative research method, (2) developing a measurement tool based on the quantitative data collected in line with this framework, and (3) testing structural relationships among digital literacy, generative AI literacy for learning, and student engagement through a model with educational level and gender as moderators. In the first stage, using the grounded theory approach, four key dimensions of generative AI literacy for learning were identified: Needs Analysis, Prompting and Language Skills, Autonomous Learning, and Critical Thinking. In addition, readiness factors, potential outcomes, and potential challenges and negative effects were revealed. In the second stage, the "Generative AI Literacy for Learning Scale", consisting of four factors and 29 items, was developed and validated through reliability and validity analyses. In the third stage, using data collected from 337 distance education students from three universities in Turkey, it was found that digital literacy has a significant effect on generative AI literacy for learning, generative AI literacy for learning has a significant effect on student engagement, and digital literacy has a direct and significant effect on student engagement. Furthermore, generative AI literacy for learning was found to significantly mediate the relationship between digital literacy and student engagement. In this context, educational level was found to have a significant moderating effect on the relationship between generative AI literacy for learning and student engagement, whereas gender did not have a significant moderating effect. The findings indicate that generative AI literacy for learning supports student engagement in distance education; however, its effect is greater at the associate degree level compared to the undergraduate level. This study contributes to the literature by providing a conceptual framework for generative AI literacy for learning, a valid and reliable measurement tool, and a relational model that enhances student engagement in distance education, offering suggestions for future research and practical implementations.