Behavioral Patterns of AI Behavioral Patterns of Artificial Intelligence Integration in Instructional Management Among Student Teachers
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Abstract
The objectives of this research were: 1) to examine the levels of Artificial Intelligence (AI) integration in teaching and learning among student teachers during their professional internships; and 2) to compare these behavioral patterns based on gender, major, school size, and institutional affiliation. This study employed a quantitative survey research design. The population comprised 755 student teachers practicing in educational institutions during the 2025 academic year. A sample size of 270 participants was determined and selected through proportional stratified random sampling, categorized by major, gender, school size, and affiliation. The final participants were recruited via simple random sampling using a random number table. The research instrument was a 5-point Likert scale questionnaire assessing AI application behaviors. Data were analyzed using descriptive statistics, including frequency (n), percentage (%), mean (ðĨĖ), and standard deviation (S.D.), while inferential statistics involved t-tests and One-Way ANOVA.
The findings revealed that: 1) the level of AI application in instructional management among pre-service teachers was at a moderate level (ðĨĖ = 3.48, S.D. = 0.83). 2) Student Teachers with different academic majors exhibited statistically significant differences in their AI utilization behaviors at the .05 level. However, no significant differences were found when categorized by gender, school size, or school affiliation.
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