人类社会正加速迈向智能化时代，教育领域也将呈现教师与人工智能协作共存的教育新生态。教师面临着新一轮的技术改革与创新，在此模式下，有充足证据显示能够凸显核心价值观的教师信念问题对于改革成效具有较大影响。但教师信念是内隐性的，其系统构成也具有差异性、易变性的特征，由此本文欲采用质性研究的方法，基于教师教学实践开展教师信念系统的相关探索，进一步完善人工智能环境下的教师教育研究理论，丰富教师信念领域内的相关理论成果，并为驱动教师积极开展人工智能教学提供战略性建议，从教师专业发展的角度提供可行性路径，吸引更多学科的教师开展人工智能教学实践。

本研究以中小学一线教师为调查对象，关注教师个体视角，将教师信念作为研究内容。通过组织主题为“人工智能教学”的专题研讨会，挖掘教师讨论的主要热点，通过等比抽样与滚雪球抽样选取八位研究对象，对八位教师进行专门的一对一访谈，而后组织小组焦点访谈，收集其访谈数据。在研讨会文本分析及问卷调查的基础上，研究者按照态度与实践两维度将研究对象划分为四种类型：积极强实践型，积极弱实践型，消极强实践型以及消极弱实践型。使用内容分析法处理两次访谈数据，得到不同类型教师的信念系统构成情况以及不同话语情境下教师信念系统构成的变化。利用话语分析的三维框架“文本分析—话语实践—社会实践”对小组焦点访谈中的教师信念系统构成的变化过程进行阐释，挖掘话语背后的社会意识形态及其所反映出的社会现象。利用关键词提取挖掘教师信念的影响因素，最后尝试提出人工智能教学情境下教师专业发展策略。

综合研究发现，主要有以下三个方面：

第一，教师信念系统的构成中，关于“教师角色”的信念在教师信念系统中占比小，多数教师认为教师作为教学主导者这一现状是难以改变的，且教学效率优于其他方式。关于“自我”的信念在教师信念系统中占比小，教师普遍承认在职前拥有与智能技术相关的实践经验有利于入职后的人工智能教学开展，但会由于教学压力重，处理各种繁杂事务等多种因素而被迫搁置创新智能教学。在强实践型教师的信念系统中，关于“教师情感”信念的占比最大，反映在行为中，教师在多次使用智能教学软件的过程中，不自觉的加深其对智能技术的认知，以及处理师生关系等情感方面的特长之处。在弱实践型教师的信念系统中，关于“外部环境”的信念占比最大，反映在行为中，教师因政策要求，学校硬件配备、教师群体科研氛围等因素影响，能够开展人工智能教学的课堂频次受到控制。

第二，在不同话语情境下教师信念系统构成中，态度积极型教师在讨论中占据主要话语权，参与小组焦点访谈的所有教师关于教学的信念占比均增大，消极型教师信念系统构成在小组焦点访谈中更加丰富。

第三，在影响教师信念的因素中，社会环境对于教师信念的影响程度最大，智能教育产品性能也会对教师信念产生影响，教师普遍对自身教育技术能力重视程度低。

依据上述发现，本研究提出的人工智能教学培训策略建议包括：（1）将教师群体进行科学分组高效提升教师技术认知，态度积极型的教师在学习小组中倾向于输出，而态度消极型教师倾向于输入和反思，可助其拓宽思考维度，从宏观视角看待问题，并外化为其主动尝试创新人工智能教学模式的教学行为；（2）组建跨学科教师学习共同体，从不同学科的问题视角去看待人工智能教学，弥补单学科所具有的片面缺陷，有助于教师全面建构关于人工智能教学的个人认知。

Human society is acceleratingtowards the era of intelligence, and the field of education will also present anew education ecology in which teachers and artificial intelligence coexist. Teachersare facing a new round of technological reform and innovation. Under thismodel, there is sufficient evidence that teachers' beliefs that can highlightcore values have a great impact on the effectiveness of the reform. However,teacher belief is implicit, and its system composition also has the characteristicsof difference and variability. Therefore, this paper intends to use the methodof qualitative research to carry out the relevant exploration of teacher beliefsystem based on teachers' teaching practice, to further improve the researchtheory of teacher education in the artificial intelligence environment, enrichthe relevant theoretical achievements in the field of teacher belief, andprovide strategic suggestions for driving teachers to actively carry outartificial intelligence teaching, Provide a feasiblepath from the perspective of teacher professional development to attractteachers from more disciplines to carry out artificial intelligence teachingpractice.

This research takes front-lineteachers in primary and secondary schools as the survey object, pays attentionto the individual perspective of teachers, and takes teachers' beliefs as theresearch content. By organizing a symposium withthe theme of "artificial intelligence teaching", the main points ofteachers' discussion were explored, eight research subjects were selectedthrough proportional sampling and snowball sampling, and eight teachers werespecially interviewed one-on-one, and then group focus interviews to collecttheir interview data. On the basis of the textanalysis of the seminar, the researchers divided the research objects into fourtypes according to the two dimensions of cognition and practice: Activeand strong practice type teachers, Active weak practice type teachers, negativestrong practice type teachers and Negative and weak practice type teachers. Thecontent analysis method was used to process the data of the two interviews, andthe composition of the belief system of different types of teachers and thechanges in the composition of the belief system of teachers in differentdiscourse situations were obtained. Using thethree-dimensional framework of discourse analysis "text analysis-discoursepractice-social practice", this paper interprets the changing process ofteachers' belief system in group focus interviews, and explores the socialideology behind discourse and the social phenomenon it reflects. Finally, weuse keyword extraction to mine the influencing factors of teachers' beliefs,and try to propose teachers' professional development strategies in the contextof artificial intelligence teaching.

The comprehensive research foundthat there are three main aspects:

First, in the composition of theteacher's belief system, "teacher role" accounts for a smallproportion of teachers' belief system Most teachers believe that the status quoof teachers as teaching leaders is difficult to change, and the teachingefficiency is better than other methods. The belief of "self-knowledge"accounts for a small proportion of teachers' beliefs. Teachers generally admitthat having practical experience related to intelligent technology beforeemployment is beneficial to the development of artificial intelligence teachingafter entry, but due to the heavy teaching pressure, they will deal withvarious complicated affairs and other various Because of this factor, it isforced to shelve innovative intelligent teaching. Among the beliefs of strongpractice teachers, "teacher emotion" accounts for the largestproportion, which is reflected in behavior. In the process of using intelligentteaching software for many times, teachers unconsciously deepen their cognitionof technology and deal with teachers and students. Relationship strengths.Among the beliefs of weak practice teachers, the "externalenvironment" accounts for the largest proportion, which is reflected inthe behavior. Due to the influence of factors such as policy requirements,school hardware equipment, and teacher group scientific research atmosphere,the frequency of classrooms that can carry out artificial intelligence teachingis controlled.

Second, in the composition ofteachers' belief systems in different discourse situations, teachers withpositive attitudes occupy the main discourse power in discussions, and theproportion of all teachers' beliefs about teaching in group focus interviewsincreases. The composition of negative teachers' belief system is more abundantin group focus interviews.

Third, among the factors thataffect teachers' beliefs, the social environment has the greatest impact on thegroup of teachers, and the performance of intelligent educational products willalso affect teachers' beliefs. Teachers generally pay less attention to theirown educational technology capabilities.

Based on the above findings, theartificial intelligence teaching and training strategies proposed in this studyinclude: (1) Group teachers into groups to effectively improve teachers'technical cognition. Teachers with positive attitudes tend to output in thelearning community, while teachers with negative attitudes tend to output.Input and reflection can help them broaden their thinking dimensions, look atproblems from a macro perspective, and externalize their teaching behaviors toactively try to innovate artificial intelligence teaching models; (2) To form aninterdisciplinary teacher learning community, from the perspective of problemsin different disciplines Looking at artificial intelligence teaching and makingup for the one-sided defects of a single subject will help teachers to fullyconstruct their personal cognition about artificial intelligence teaching.