The Training Curriculum Development for Supervising Teachers to Enhance Competency in Thai Language Communicative Management Using a Coaching Model Integrated with Artificial Intelligence
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Abstract
Background and Aim: In the context of 21st-century education, communicative competence in the Thai language is a critical skill for supervisory teachers, who play a central role in mentoring and instructional leadership. Despite the growing complexity of communication in digital learning environments, existing professional development programs for supervisory teachers remain fragmented and lack integration with modern pedagogical frameworks and technological innovations. This research addresses this gap by developing a training curriculum that synthesizes Artificial Intelligence (AI) with a coaching model to enhance communication management in Thai language instruction systematically. The study aimed to: (1) examine the current context, needs, and barriers to effective communication management among supervisory teachers; (2) design and validate an AI-integrated coaching curriculum; (3) implement the curriculum in a real-world educational setting; and (4) evaluate its effectiveness and identify areas for improvement.
Materials and Methods: Adopting a mixed-methods exploratory sequential design, the study proceeded in two phases: qualitative inquiry followed by quantitative validation. The research process comprised four stages: (1) a needs assessment involving document analysis and semi-structured interviews with 120 stakeholders (supervisors, Thai language teachers, and educational experts); (2) curriculum design and expert validation by a panel of five specialists; (3) implementation with 30 purposively sampled supervisory teachers, evaluated through pre-post assessments of knowledge, competence, instructional planning, and learner outcomes; and (4) curriculum refinement based on empirical feedback.
Results: Findings revealed a critical and clearly articulated need for a structured training model focused on communication management. The developed curriculum—comprising pedagogical objectives, modular content, AI-assisted learning activities, and formative evaluation—was rated as highly appropriate by experts. Post-implementation assessments indicated statistically significant improvements in supervisors’ pedagogical knowledge and communicative competence (p < .05). Student teachers under their supervision also exhibited strong performance in lesson planning (M = 4.55, SD = 0.66), instructional delivery (M = 4.57, SD = 0.53), and learner engagement (M = 4.59, SD = 0.71). Recommendations for refinement included expanding content depth, adjusting training duration, and introducing post-training support mechanisms.
Conclusion: This study contributes to the field of teacher professional development by offering an empirically grounded, AI-supported coaching curriculum tailored to the communicative demands of Thai language supervision. The integration of AI within an instructional coaching framework not only enhanced supervisory competencies but also addressed a notable gap in existing training literature. The findings support the curriculum’s applicability and adaptability for sustained use in broader educational contexts.
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