Dataset: Predictors of Physical Education Teachers' Intentions to Learn Artificial Intelligence

This dataset accompanies the research titled, "Understanding Physical Education Teachers’ Intentions to Learn Artificial Intelligence: The Mediating Role of Attitudes Toward Artificial Intelligence."Background and Purpose:As artificial intelligence (AI) becomes integral to education, understanding the drivers of teacher adoption is critical. This study investigated the factors influencing physical education (PE) teachers' intentions to learn about AI. Specifically, it examined the direct and indirect relationships between AI self-efficacy, individual innovativeness, general attitudes toward AI, and AI learning intentions, testing the mediating role of attitudes toward AI.Methods:The research employed a cross-sectional, correlational survey design. Data were collected via an online survey from a sample of 1,021 physical education teachers recruited through snowball sampling. The survey instruments included validated scales measuring:AI Learning IntentionsIndividual InnovativenessAI Self-EfficacyGeneral Attitude Toward AIData and Files:The dataset ("Sheet 1") contains the raw, anonymized responses from the 1,021 participants. The data is structured for direct use in statistical analysis, particularly Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). All scales are measured on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). Demographic variables (Gender, School Level, Age Group) are included with clear coding schemes detailed in the accompanying README.Key Findings:The structural equation model revealed:A strong, direct positive relationship between teachers' attitudes toward AI and their intention to learn about AI (β = 0.64, p