基于大数据的大学师范生二次选拔机制模型研究与应用

Normal education is related to the national economy and people's livelihood. For a long time, the normal students are selected through the college entrance examination voluntary and college entrance examination scores, and lack of attention to the qualities of normal students. As a result, there is a lack of preferred talents in the training phase and there is a lack of professional interest in the career choice phase, resulting in a waste of educational resources. In 2018, the Central Committee of the Chinese Communist Party and the State Council specially issued the Opinions on Deepening the Reform of the Teaching Staff in the New Era. It explicitly proposed that teachers’ universities should be encouraged to adopt secondary selection methods after entering the school to select normal students. The main goal of this research is to establish a model of secondary selection mechanism for normal university students and test it in practice. In the strategy, relying on the data of the normal school students collected by the Jiangsu Normal University, we construct the independent variables of the supply of the students, the adjustment variables of the growth mechanism, and the dependent variables of the career development to explore the relationship among the three factors. Try to use neural network technology and data mining analysis methods to explore the relationship between the students' source supply and career development, and the intrinsic relationship and mechanism between the system and the environment. Explore key variables that influence career development, so as to provide decision-making reference for institutional design of follow-up student selection and training process.

师范教育关乎着国计民生。长期以来师范生生源依赖于高考志愿和高考分数甄别，缺乏对师范生素质特质的关注。以至于在培养阶段缺乏优选之才，择业阶段缺失职业兴趣，造成教育资源的浪费。2018年中共中央、国务院专门下发了《关于全面深化新时代教师队伍建设改革的意见》明确提出了鼓励师范院校采取入校后二次选拔方式遴选师范生，这为师范生的精细化培养提供了制度保障。本研究核心目标是建立大学师范生二次选拔机制模型并在实践中予以检验。在策略上依托项目所在学校采集的三届师范生数据，构建生源供给的自变量、培养机制的调节变量以及生涯发展的因变量，探究三者之间的关系。尝试运用神经网络技术和数据挖掘分析方法探索大学师范生生源供给与生涯发展两者间的关联机制以及其与相关制度、环境之间的内在关系与机理。探求影响生涯发展的关键变量，从而为后续生源遴选与培养过程的制度设计提供决策参考。

2018年，中共中央、国务院发布《关于全面深化新时代教师队伍建设改革的意见》，明确提出了鼓励师范院校采取入学后二次选拔方式遴选师范生，在集中优势教育资源的过程中提升师范生选拔和培养的精准化和实效性。本课题正是在此背景下开展了相关研究工作，以期建构科学的模型遴选乐学善教的师范生。课题组主要聚焦大学师范生的生源供给、成长机制、生涯发展以及培养的关联机制展开研究。在研究路径上依托大数据、神经网络算法等工具探究了数据之间的逻辑关系，建构了基于实践成效的大学师范生二次选拔模型。通过大量数据的交叉分析，探究出不同变量对潜在优秀教师的影响。课题组探讨了师范生候选人的身体素质、专业能力、心理素养、性格特征、生涯发展等诸多因素之间的交叉关联。我们发现师范生候选人的选择倾向、专业能力、心理素养、性格特征、教育效能感、职业认同、职业定向是构建大学生师范生二次选拔模型的关键指标。在数据探索过程中，研究发现在文理艺体等不同学科师范生中又存在指标程度的差异。依托数据的探索分析，课题组建构完成了大学师范生二次选拔模型，并对不同生源供给自变量和成长机制调节变量的取值进行了模拟，预测其生涯发展因变量的程度，较好的验证了模型的科学性。

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