Abstract:
This research aimed to study the current state of AI-integrated Supervision of teaching model for extra-large secondary schools under the Office of the Basic Education Commission (OBEC). It also aimed to create a model for AI integrated supervision and to evaluate its suitability. The research process consisted of two phases:
1. Phase 1: Studying the Current State. This phase used a questionnaire to assess the current state of AI-integrated instructional supervision. The questionnaires quality was validated by 5 experts using the IOC (Index of Item Objective Congruence) analysis. The sample for a pilot study consisted of 30 teachers (2 from each of 15 extra-large schools). The reliability was checked using Cornbrashs Alpha Coefficient. Data were then collected from the research sample of 360 teachers (2 from each of 180 extra-large schools).
2. Phase 2: Developing and Evaluating the Model. This phase involved drafting the AI-supported instructional supervision model and then evaluating it for suitability through a seminar with 9 experts.
The statistics used in the research were frequency, percentage, mean, standard deviation, content analysis, needs assessment results (PNI), and confirmatory factor analysis (CFA).
Research Findings
1. Current and Expected State: The current state of AI-integrated supervision was at a high level (mean 3.59), with the highest-rated step being Media & Supervisory Tools (3.67) and the lowest being Supervision Motoring (3.54). The expected state was at the highest level (mean 4.55), with teachers having the highest expectations for Integration of Knowledge and Pedagogy (4.56).
2. Needs Assessment: The overall Needs Assessment Index (PNI modified) was 0.07. The lowest scores were for Organizing Learning Activities and Creating a Positive Atmosphere (0.06 and 0.04, respectively), as these were areas where teachers already performed well.
3. The Developed Model: The developed AI-integrated supervision of teaching model for extra large secondary schools under the Office of the Basic Education Commission consists of 6 steps where AI acts as a supporting tool to systematically link all supervision stages. These steps are:
1. Analysis: Using AI to analyze teaching data and teacher needs.
2. Planning: Using AI to design personalized supervision plans.
3. Media & Supervisory Tools: Using AI tools like Canva to create automated teaching media.
4. Implementation: Putting the plan into practice with an AI-powered alert system and automatic plan adjustments.
5. Supervision Motoring: Using AI to track results in real-time.
6. Report & Reflection: Using AI to automatically summarize results.
This model impacts teachers learning management in 6 areas: 1) Curriculum development, 2) Integration of knowledge and pedagogy, 3) Individualized learning, 4) Organizing learning activities and creating a positive atmosphere, 5) Research, innovation, and technology for learning, and 6) Creative and collaborative professional development.
4. Model Focus: The model aims for AI to serve as a supporting tool in every step of supervision. This makes the teacher development process more accurate, targeted, and adaptable to the unique context of each school. It also helps teachers use AI to promote learner-centered instruction that aligns with the 21st-century skills.
Keywords: supervision, Artificial Intelligence, learning management, teachers in extra- large secondary schools