【作 者】：
孙 硕，胡小勇，穆 肃，刘 阳
【关 键 词 】：
师范生； 教学基本技能； 微技能观测指标； 智能实训； 数字画像
【栏 目】：
学科建设与教师发展
【中文摘要】：
师范生作为教师队伍的储备力量，影响着教育未来的发展。依据《普通高等学校师范类专业认证标准》与教育部两批《人工智能助推教师队伍建设行动试点工作的通知》等政策文件要求，研究针对师范生教学基本技能培养难题与发展要求，结合人工智能技术潜能构建了面向师范生教学基本技能培养的“四维度18指标”微技能观测指标框架，设计了四层架构的师范生教学基本技能智能实训分析系统模型，提出了智能分析特点及教学基本技能“智学”实训方式，并于所在师范院校开展了试验应用。研究表明，以人工智能技术助推师范生高质量培养为导向，进行师范生教学基本技能智能实训框架模型构建、技术方法实现、实训场景设计和数字画像生成，能够提升师范生实训效果。
【英文摘要】：
As the reserve force of teaching force, normal university students affect the future development of education. According to the requirements of the Standards of Professional Accreditation for Normal Colleges and Universities and the Ministry of Education's two batches of Notice on Launching Pilot Work on Artificial Intelligence Booting Teacher Team Construction, aiming at the training problems and development requirements of normal university students' basic teaching skills, this study has constructed a micro-skill observation index framework of "four dimensions and 18 indicators" for the training of normal university students' basic teaching skills, combined with the potentials of artificial intelligence. Moreover, this study has designed a four-layer intelligent training and analysis system model for normal university students' basic teaching skills, and put forward the characteristics of intelligent analysis and the "ZHIXUE" training method of basic teaching skills, which have been applied in the normal university. The results show that guided by artificial intelligence technology to promote high-quality training of normal university students, the construction of the framework model, the realization of technical methods, the design of training scenarios and the generation of digital portraits can improve the training effect of normal university students' basic teaching skills .