教育数字化转型背景下，人工智能（Artificial Intelligence，AI）技术成为助推新时代素养导向教与学方式转变的重要动力，中小学教师面临着智能时代专业发展的迫切需求。然而，目前有关中小学教师面向智能时代专业发展的研究存在严重缺位，并未形成能够指导实践开展的理论，也缺少在真实情境下的长周期实践探索。面对智能时代日益发展的教学结构升级变革趋势和素养导向人才培养需求，中小学教师需要持续变革和更新自身知识结构，在教学中实现AI技术、学科内容与教学方法的有效融合运用。在这一背景下，面向整合AI技术的学科教学知识（Artificial Intelligence Technology Pedagogical and Content Knowledge, AI-TPACK）的教师变革性专业发展（Transformative Professional Development，TPD）成为新时代教学创新的突破口。

传统教师信息技术能力提升实践过程中存在教研培训活动分离、脱离教学实践情境、流于形式表面等问题，难以满足教师AI-TPACK跃升性变革发展需求。本研究以教育数字化转型及智能化升级发展下的中小学教师专业发展为目标，以“促进中小学教师AI-TPACK发展”为核心研究内容，重构了AI-TPACK的概念框架与测评工具，基于成人变革性学习理论构建了教师AI-TPACK发展“A4C”模型，并依托这一模型开展了长周期的准实验研究，系统性探索了影响教师AI-TPACK发展的关键要素及目标AI-TPACK提升的有效机制。研究旨在从理论层面对中小学教师在智能时代的专业发展理论进行系统化发展和创新，在实践层面推动中小学教师更好地开展智能技术背景下的人机协同教学，从而回应当前大规模课堂教学实践常态化、系统性变革的进程需要。 总的来说，本研究取得了以下四个方面的进展：

研究一面向教与学创新及智能技术发展当下进程，明晰和界定了中小学教师AI-TPACK内涵，在智能技术环境下时代性发展了TPACK理论。本研究在智能时代背景下，基于技术价值的二重性理论和成人变革性学习理论，从价值层、角色层和融合层三个角度出发，深入发展了教师的AI-TPACK内涵。从价值层的创新来看，本研究从AI教学的外在价值知识与内在价值知识两个方面重构了AI-TPACK的概念框架，有助于引导教师在教学实践中确保技术的合理、合法和道德地使用。从角色层的创新来看，本研究突显了人机协同教学中“人师”与“机师”的双主体角色特征，为智能时代的人才培养和教学变革开创可行之路。从融合层的创新来看，本研究从AI与具体学科教学融合的不同发展阶段出发，解构了教师AI-TPACK在不同层次的表现性特征和关键要素，为指导教师智能教学实践和专业发展提供了更具操作性的理论框架。

研究二基于研究与实践发展当前样态，深度突显具体学科特征，设计、开发和验证了中学英语教师AI-TPACK评价工具。本研究以英语学科为例，开展了覆盖国内外112篇论文的系统性文献综述，综合17款智能英语教学软件情况，充分了解了研究和市场中智能教学产品的实际情况。在此基础上，本研究收集多位专家及英语教师的修改意见和内容效度评分，并在2021、2022、2023年先后收集470份、659份和366份英语教师有效样本数据，验证了量表信效度。本研究开发的AI-TPACK量表旨在从智能教学不同发展阶段引导规范教师发展和教学转型，为AI与学科教学融合的实践提供监测和预警。

研究三面向区域教师智能时代专业发展需求，构建了中小学教师AI-TPACK发展“A4C”模型，在智能环境下创新性发展了教师变革性专业发展理论。本研究在2020年11月对163名中学英语教师开展书面结构化访谈，对15名教师开展群体访谈，深入了解了一线教师智能教学的内在发展需求与外部支持需求，基于教师变革性专业发展理论，总结提炼了面向AI-TPACK的教师变革性专业发展“A4C”模型，其中“A”指的是在个体层面强调以AI教学科研消费与科研生产活动为“自下而上”的行动研究（Action Research）主线，“4C”指的是在外部环境层面强调技术环境精准赋能（Catalytic Technology）、制度环境多域协同（Cooperative Multi-Institution）、人际环境共同体构建（Constructed Community）、时间维度持续发展（Continuous Span）的“自上而下”外部支持，从系统性视角回应了区域大规模教师实现常态化智能教学的发展需求。为了验证模型效果，本研究设计了详细行动方案，在北京市东城区招募了147位中学英语教师（共组成28个行动研究共同体）作为实验组，将东城区未参与实验的教师作为对照组，在2021年5月-2023年12月进行了长达两年多的准实验研究。经有效样本数据检验，东城区实验组教师比对照组教师获得了更好的AI-TPACK发展，且教师发展能够有效促进学生英语学习自我效能感提升。同时，跨区域对比结果显示，东城区教师比国内其他三个区域（均为智能技术助推教师队伍建设区域）教师具备更高的AI-TPACK水平。这一经过长期实证检验的模型能够为中小学教师智能时代的专业发展提供可靠的实施路径与体系创新依据，为智能技术在更大范围、更宽领域、更多学科的教学中深度应用提供参考和指导。

研究四采用结构方程建模与质性访谈，揭示了影响中小学教师AI-TPACK发展的关键要素和作用机制。为了进一步完善AI-TPACK变革性专业发展“A4C”模型，本研究在2022年12月和2023年12月分别采集285份和200份有效教师样本进行结构方程模型分析，从个体行动研究活动要素（AI教学科研消费与生产）及外部环境要素（技术环境、人际环境、制度环境与时间维度）出发，挖掘了预测教师AI-TPACK发展的关键要素及其内部作用机制，并通过访谈对量化数据结果进行了解释和补充。研究结果发现，从个体层面来看，教师行动研究中的“科研消费”与“科研生产”活动都能够正向预测其AI-TPACK发展，各要素在不同阶段的关联能够与本研究的行动方案设计能够相互对应。从外部因素来看，技术环境激发教师“AI使用意愿”与制度环境的“多域协同”是预测AI-TPACK的直接要素，而人际维度的“共同体构建”与时间维度的“持续发展”是预测AI-TPACK的间接要素。最终，本研究对于教师AI-TPACK发展的关键要素和作用机制进行了提炼总结，基于实证数据进一步完善了教师AI-TPACK发展“A4C”模型，为教师面向AI-TPACK的变革性专业发展提供了细节更为详实、机制更为明确的理论框架。

总的来看，本研究实现了理论、工具与实践三方面的创新。在理论层面，本研究构建了面向教师AI-TPACK变革性专业发展的“A4C”理论模型，对教师变革性专业发展理论和TPACK理论进行了智能时代的新发展，强调了行动研究、精准赋能、多域协同、共同体构建、持续发展等要素，能够指导一线教师智能时代专业发展。在工具层面，本研究对教师AI-TPACK理论的概念框架在价值层、角色层和融合层进行了创新性发展，构建了面向教师AI-TPACK发展水平的三阶段测评工具，深入具体学科且贴近一线教师真实需求，能够为当下教师发展提供测评依据与价值引领。在实践层面，本研究在实验区域通过长期实验推动了中小学教师的AI-TPACK发展，推动了区域教师专业发展模式及新型体系建构，并通过国家智慧教育示范区与智能社会治理实验基地的示范引领作用带动更多教师的发展，成果能够服务于智能时代教师专业发展新进程。

Under the background of digital transformation of education, Artificial Intelligence (AI) technology has become an important driving force to achieving literacy-oriented teaching and learning methods, and K-12 teachers facing an urgent need for professional development in the AI era. However, there is a serious lack of research on the professional development of K-12 teachers facing the AI era, which lacks of a theory that can guide practical development, and a long-term practical exploration in the real situation. In the face of the increasing trend of upgrading teaching structure in the AI era and the demand for literacy-oriented talent training, K-12 teachers need to continuously change and update their own knowledge structure, and realize the effective integration and application of AI technology, pedagogical knowledge and content knowledge in teaching. Against this background, the transformative professional development (TPD) of teachers’ Artificial Intelligence Technological Pedagogical and Content Knowledge (AI-TPACK) has become the breakthrough of teaching innovation in the new era.

In the process of improving teachers’ using technology, there are some problems such as separation of training and teaching, separation of teaching practice and teacher development, superficial form, etc., which is difficult to meet the needs of teachers’ AI-TPACK transformation and development. Aiming at the professional development of K-12 teachers under the development of education digital transformation and intelligent upgrading, this study takes promoting the development of K-12 teachers AI-TPACK as the core research content, constructs an model of teacher AI-TPACK’s transformative professional development based on the adult transformative learning theory, and carries out a long-term research based on this model. This paper systematically explores the key factors affecting the development of AI-TPACK for teachers and the effective mechanism of AI-TPACK promotion. The research aims to systematically develop and innovate the professional development theory of K-12 teachers in the intelligent era from the theoretical level, and promote the human-computer collaborative teaching under the background of intelligent technology for K-12 teachers in practice, so as to respond to the needs of the normalization and systematic reform of the current large-scale classroom teaching practice. In general, this study has made progress in the following four aspects:

The first study focuses on the current process of teaching and learning innovation and the development of AI technology, clarifying and defining the connotation of AI-TPACK for K-12 teachers, and developing the TPACK theory in the context of intelligent technology. In the context of the AI age, based on the duality theory of technology value and the transformative learning theory of adults, this research deeply develops the connotation of AI-TPACK for teachers from three perspectives, including value layer, role layer and integration layer. From the value level, this study reconstructs the conceptual framework of AI-TPACK from the two aspects of external value knowledge and intrinsic value knowledge in AI teaching, which helps guide teachers to ensure the reasonable, legal and ethical use of technology in teaching practice. From the perspective of innovation at the role level, this study highlights the dual role characteristics of human teacher and machine teacher in human-machine collaborative teaching, and creates a feasible way for talent training and teaching reform in the intelligent era. From the perspective of innovation at the integration level, this study starts from the different development stages of the integration of AI and specific subject teaching, deconstructs the performance characteristics and key elements of teachers’ AI-TPACK at different levels, and provides a more operational theoretical framework for guiding teachers’ intelligent teaching practice and professional development.

Based on the current pattern of research and practice development, the second study deeply highlights the characteristics of specific disciplines, and designs, develops and validates the AI-TPACK evaluation tool for middle school English teachers. Taking English as an example, this study carried out a systematic literature review covering 112 papers, integrated 17 AI English teaching software, and fully understood the actual situation of intelligent teaching products in the research and market. On this basis, this study collected modification opinions and content validity scores from a number of educational technology experts, staff of the District Education Commission and English teachers, and collected 470, 659 and 366 valid sample data of English teachers in 2021, 2022 and 2023 respectively to verify the reliability and validity of the scale. The AI-TPACK scale developed in this study aims to guide and standardize teachers’ development and teaching transformation from different development stages of intelligent teaching, and provide monitoring and early warning for the practice of integrating AI with subject teaching.

The third study investigates the professional development needs of regional teachers in the intelligent era, constructs the AI-TPACK development A4C model for K-12 teachers, and innovatively develops the transformative professional development theory of teachers under the intelligent environment. In November 2020, this study conducted structured written interviews with 163 middle school English teachers and group interviews with 15 teachers to gain an in-depth understanding of the internal development needs and external support needs of front-line teachers in intelligent teaching. Based on the theory of transformative professional development of teachers, The A4C model of teachers’ transformative professional development for AI-TPACK is summarized and refined, where A refers to Action Research that emphasizes AI teaching research consumption and research production activities as bottom-up at the individual level. The 4C refers to Catalytic Technology, Cooperative Multi-Institution, Constructed community, and Continuous Span of the external environment, which responds to the development needs of regional large-scale teachers to realize normal intelligent teaching from a systematic perspective. In order to verify the effect of the model, this study designed a detailed action plan. 147 middle school English teachers (comprising 28 action research communities) in Dongcheng District of Beijing were recruited as the experimental group, and teachers who did not participate in the experiment in Dongcheng District were selected as the control group. A quasi-experimental study was conducted for more than two years from May 2021 to December 2023. According to the test of valid sample data, teachers in the experimental group in Dongcheng district achieved better AI-TPACK development than teachers in the control group, and teacher development can effectively promote the improvement of students’ self-efficacy in English learning. At the same time, cross-regional comparison results show that teachers in Dongcheng District have higher AI-TPACK level than teachers in other three regions in China (all AI-assisted teacher development regions). After long-term empirical test, this model can provide a reliable implementation path and system innovation basis for the professional development of K-12 teachers in the intelligent era, and provide reference and guidance for the deeply application of intelligent technology in the teaching of a wider range, a wider range of fields and more subjects.

Based on the AI-TPACK development model, the fourth study uses structural equation modeling and qualitative interviews to reveal the key factors and mechanisms that predict the development of AI-TPACK for K-12 teachers. In order to further improve the AI-TPACK transformative professional development A4C model, 285 effective teacher samples were collected in December 2022 and 200 in December 2023 for structural equation model analysis. Starting from individual action research activity elements (consumption and production of AI teaching and research) and external environment elements (4C), the key elements and internal mechanism of predicting teacher AI-TPACK development were excavated, and the quantitative data results were explained and supplemented through interviews. The research results show that from the individual level, both research consumption and research production activities in teacher action research can positively predict their AI-TPACK development, and the correlation of various elements at different stages can correspond with the action plan design of this study. From the perspective of external factors, the Catalytic Technology environment stimulating teachers’ intention to use AI and the Collaborative Multi-institute environment are the direct factors in predicting AI-TPACK, while Constructed Community and Continuous Span are the indirect factors in predicting AI-TPACK. Finally, this study refines and summarizes the key elements and mechanism of teacher AI-TPACK development, further improves the A4C model of teacher AI-TPACK development based on empirical data, and provides a more detailed and clear theoretical framework for teachers’ transformative professional development towards AI-TPACK.

In general, this research has achieved innovation in theory, tools and practice. At the theoretical level, this study constructs the A4C theoretical model for teacher professional development in the intelligent era, and carries out new development of the transformative teacher professional development theory and TPACK theory in the intelligent era, highlighting the professional development needs of teachers in the intelligent era that combine bottom-up and top-down. It emphasizes the elements of Action Research, Catalytic Technology, Cooperative Multi-Institution, Constructed community, and Continuous Span, which can guide the professional development of front-line teachers in the intelligent era. At the tool level, this study innovatively develops the conceptual framework of teacher AI-TPACK theory in the value level, role level and integration level, and builds a three-stage assessment tool for teacher AI-TPACK development level, which is in-depth in specific disciplines and close to the real needs of front-line teachers, and can provide assessment basis and value guidance for current teacher development. In practice, this study promoted the development of AI-TPACK for K-12 teachers through long-term experiments in the experimental area, promoted the construction of regional teacher professional development models and new systems, and promoted the development of more teachers through the demonstration and leading role of the national smart education demonstration zone and AI social governance experimental base. The results can serve the new process of teacher professional development in the AI era.