Thesis:

Identifying the fields of augmented reality-based training in teaching basic motor skills

The purpose of the research was to identify the areas of augmented reality-based education in motor skills education. Given the nature of the subject and to achieve a deeper understanding and ultimately the possibility of a more valid analysis, this research was conducted in a qualitative (analytical-deductive) manner. This research is a qualitative research and phenomenological type. The statistical population of the present study is all experts and informants on the subject, all professors of physical education, educational sciences and information technology who have been selected using the theoretical sampling method. The sampling method of the present study is purposive snowball or network sampling. The number of samples was determined by information saturation. In the current study, the number of selected samples was 14 professors of physical education, educational sciences and information technology. In this study, in-depth face-to-face interviews with open-ended questions were used with professors of physical education, educational sciences and information technology. Each interview took approximately 60 minutes. To gain a more detailed understanding of the perspectives expressed by the participants, the interviews were immediately analyzed and the conversations were reviewed after recording. The results indicate that, according to the questions asked, for the causal conditions of the use of augmented reality-based education in teaching fundamental motor skills, 16 subcategories were obtained, which were categorized into 7 main categories using axial coding. For the intervention conditions, 12 subcategories were obtained, which were categorized into 4 main categories using axial coding. For the contextual conditions, 20 subcategories were obtained, which were categorized into 5 main categories using axial coding. For the strategies for the use of education, 17 subcategories were obtained, which were categorized into 5 main categories using axial coding. For the consequences of the use of education, 27 subcategories were obtained, which were categorized into 4 main categories using axial coding.

Keywords: Identifying educational contexts, augmented reality, motor skills training.