AI Literacy in Distance Learning: Analyzing Graduate Students' Competencies Across Key Variables

Abstract

This study was conducted to examine the artificial intelligence literacy levels of non-thesis graduate students studying through distance education in terms of different variables. A total of 354 distance education graduate students participated in the quantitative research. The data were collected using the “Artificial Intelligence Literacy Scale” developed by Wang, Rau, and Yuan (2023) and adapted into Turkish by Çelebi et al. (2023). Some of the findings obtained as a result of the research are as follows: (1) Students' AI literacy levels show a significant difference according to monthly income level, duration of using technological devices and frequency of using AI tools. (2) Artificial intelligence usage levels of students working in the private sector are higher than those of students working in the public sector. (3) Artificial intelligence literacy levels of students with incomes above the poverty line were found to be higher than those of students with incomes between hunger and poverty line. (4) It was determined that students who always or very often use artificial intelligence tools have highe levels of artificial intelligence literacy, artificial intelligence awareness, artificial intelligence tool use and evaluation skills, and knowledge of artificial intelligence ethics than students who rarely or never use these tools. (5) It was determined that students mostly use artificial intelligence tools for translation, producing written texts, and for courses and academic studies.