The aim of this study is to determine the artificial intelligence literacy levels of music teachers. The research was conducted using the survey model under the quantitative research paradigm. While determining the study group, easily accessible case sampling technique, which is one of the purposeful sampling methods, was used and 132 music teachers working in public schools constituted the study group. In the data collection process, “Artificial Intelligence Literacy Level Scale” was used to measure the artificial intelligence literacy levels of music teachers. For the analysis of the data, normality analyses were performed first and accordingly, it was decided which statistical analyses to use and independent groups t-test and one-way Analysis of Variance (Anova) were used in the study. The artificial intelligence literacy levels of the teachers were examined in terms of various variables and the data were tabulated and reported. As a result of the research, it was determined that the average level of artificial intelligence literacy of music teachers was at a medium level. In terms of gender variable, it was determined that the artificial intelligence literacy levels of music teachers were higher than those of female music teachers in the “Artificial Intelligence Literacy Scale” general total and “Awareness” sub-dimension. According to the marital status variable, in the “Evaluation” sub-dimension, it was seen that single music teachers had higher levels of AI literacy compared to married teachers. However, there was no significant difference according to professional seniority, graduation status, faculty of graduation and frequency of internet use. However, it was concluded that the artificial intelligence literacy levels of music teachers who have knowledge about artificial intelligence, artificial intelligence programs and use artificial intelligence programs and these programs in music and music education are significant. It has been observed that there is a direct relationship between artificial intelligence literacy, knowledge and frequency of use, and as the level of knowledge and awareness increases, teachers’ skills in evaluating and using artificial intelligence increase.
Before the data collection phase, ethical approval was obtained from the Ethics Committee of the Social and Human Sciences Research and Publication Ethics Committee of Kafkas University on 09/07/2024 with approval number 59.
No funding
we thanks to music teachers.
Primary Language | English |
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Subjects | Music Education |
Journal Section | AI, Metaverse and Advanced Technologies in Art |
Authors | |
Early Pub Date | May 24, 2025 |
Publication Date | June 30, 2025 |
Submission Date | December 2, 2024 |
Acceptance Date | May 3, 2025 |
Published in Issue | Year 2025 Volume: 6 Issue: 2 |