An assessment of the needs for teacher development on learning management of Artificial Intelligence Under Phitsanulok Primary Educational Service Area Office 2.

Abstract

This study aimed to investigate the priority needs and to propose guidelines for developing teachers’ competencies in implementing artificial intelligence (AI)–supported learning management under the Phitsanulok Primary Educational Service Area Office 2. The study was conducted in two phases. Phase 1 examined teachers’ priority needs regarding AI-supported learning management. The sample comprised 297 teachers under the Phitsanulok Primary Educational Service Area Office 2, determined using the Krejcie and Morgan sample size table. The research instrument was a questionnaire on priority needs for AI-supported learning management. Data were analyzed using means and standard deviations, and priority needs were identified using the modified Priority Needs Index (PNI_modified). Phase 2 explored guidelines for developing teachers in AI-supported learning management. Five experts were selected through purposive sampling as key informants. Data were collected using a semi-structured interview form and analyzed through content analysis.

The findings indicated that the overall priority needs index was 0.090. The highest priority need was AI-based administrative management (PNI_modified = 0.097), whereas the lowest priority need was AI-based learner support. The proposed teacher development guidelines comprised three key areas. First, in instructional planning and teaching development, teachers should be strengthened in critically reading and interpreting system-generated data, verifying consistency with classroom evidence prior to instructional decision-making, and using data to set clear, measurable individual goals and indicators aligned with curriculum standards, with continuous progress monitoring. Second, in learner support, teachers should analyze individual learners’ needs particularly those with special educational needs and select AI tools that directly address actual barriers to support access to content, facilitate expression and communication of ideas, and provide step-by-step skill practice with immediate feedback. Third, in administrative management, schools should streamline data recording and routine administrative tasks, reduce redundancy, and employ AI for categorization, completeness checking, and standardized reporting to support systematic monitoring and decision-making. In addition, school-level support mechanisms should be established, such as shared PLC practices and supervision/follow-up, alongside strict governance of ethics, privacy, and student data security.