BỒI DƯỠNG NĂNG LỰC KHAI THÁC AI TẠO SINH TRONG THIẾT KẾ BÀI DẠY CHO GIÁO VIÊN TIN HỌC TRUNG HỌC PHỔ THÔNG

Abstract

This study establishes a specialized competence framework and a structured five-step workflow for AI-integrated lesson plan design tailored to upper secondary school Computer Science teachers. The proposed framework aligns strictly with the legal requirements of Domain 6 (Artificial Intelligence Competence) in Circular No. 18/2026/TT-BGDĐT while incorporating a “human-in-the-loop” mechanism to regulate cognitive load. A pedagogical experiment was conducted on a sample of 72 teachers (N = 72) in Thanh Hoa province. Quantitative data processed via SPSS software reveals that the developed workflow significantly optimizes pedagogical efficiency, yielding an average reduction of 66.5% in lesson design time (p < 0.05). Furthermore, teachers' digital competencies after training demonstrated robust advancement, with Hake's normalized gain score reaching a high level of g = 0.68. The paper also illustrates advanced prompt engineering techniques (Few-shot and Chain-of-Thought) in designing Python learning materials, thereby offering a highly effective empirical model for teacher training institutions.