PSYCHOLOGICAL ADAPTATION AND MOTIVATIONAL FACTORS IN TEACHERS' USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES

This article analyzes the psychological adaptation and motivational factors that emerge when teachers in general education and higher educational institutions use artificial intelligence technologies. Specifically, it examines the interrelationships between attitudes towards technology, technological anxiety, intrinsic and extrinsic motivation, the desire for professional self-development, and innovative competencies. The study employed a mixed-method approach, combining questionnaires and semi-structured interviews; data collected from 180 teachers were processed using descriptive statistics and correlation analysis. Results indicate that perceived usefulness and ease of use of the technology, technological self-efficacy, and intrinsic motivation are strong predictors of teachers' positive attitudes and intention to use [1,3,6,17]. While technological anxiety remains at a moderate level, it is found that professional development programs focused on self-improvement can reduce this anxiety and significantly enhance innovative competencies [4,9,13,19]. The conclusions drawn provide practical recommendations for educational policy, pedagogical psychology, and the design of teacher training programs.本文针对普通教育与高等教育机构教师使用人工智能技术时产生的心理适应与动机因素展开分析。具体而言，本研究探讨了技术态度、技术焦虑、内外部动机、专业自我提升意愿与创新能力之间的内在关联。本研究采用混合研究方法，结合问卷调查与半结构化访谈；共收集180名教师的相关数据，并通过描述性统计与相关分析对数据进行处理。研究结果显示，技术的感知有用性、感知易用性、技术自我效能感以及内在动机，是教师形成积极技术态度与使用意愿的强预测因子[1,3,6,17]。尽管当前教师的技术焦虑仍处于中等水平，但研究发现，以自我提升为导向的专业发展项目可有效降低此类焦虑，并显著提升教师的创新能力[4,9,13,19]。本研究所得结论可为教育政策、教学心理学以及教师培训项目的设计提供实践参考。