Author: Diler Öner, Boğaziçi University, Türkiye
Email: [email protected]
Published: August 25, 2025
https://doi.org/10.22492/ije.13.2.02
Citation: Öner, D. (2024). Building Artificial Intelligence Literacy for Research: Technical Understanding as the Foundation for Critical Evaluation. IAFOR Journal of Education, 13(2). https://doi.org/10.22492/ije.13.2.02
Abstract
This case study investigated the development of AI literacy among novice educational researchers through an AI literacy course. AI literacy requires a high level of competence involving the ability to understand AI, use it effectively for specific tasks, evaluate and create AI, and exhibit ethical behavior in its use. The AI literacy course was designed for graduate students in the field of educational sciences and was based on four main dimensions: knowing and understanding AI, using and applying AI, evaluating and creating AI, and considering and following AI ethics. Data were collected quantitatively, using an AI literacy scale, and qualitatively, through semi-structured interviews and AI literacy journals kept by the course participants throughout the semester. Students were investigated as cases, selected using the maximal variation sampling method, focusing on the changes in their AI literacy scores throughout the semester. The analysis of the AI literacy scale showed that the biggest improvement for each case participant was in technical understanding, followed by critical appraisal and practical application. However, the qualitative data analysis also indicated that all case participants significantly improved their critical perspectives on using AI in research and began considering various ethical issues related to AI. Key course elements contributing to this outcome included allocating sufficient time to cover what AI is and how it works, and implementing an AI-based course assignment that required critical reflection on AI’s performance.
Keywords
AI literacy; higher education; graduate education