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从“数字孤岛”迈向拓展型“数据生态”:师范教育协同提质的数字化转型

Moving from a“Digital Island”to an Expanding“Data Ecosystem”:Digital Transformation of Teacher Education
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摘要 师范教育协同发展对提升薄弱院校的师范教育质量具有重要意义。已有研究基于生态系统理论和行动者网络探讨师范教育协同发展的理想样态,发现异质性主体、利益协商等因素必不可少。相较之下,近来采用的“组团模式”则指向主体的同质性、利益输出的单向性,这与协同发展的应然状态存在距离,或将限制帮扶主体范围、影响帮扶者持续参与的意愿。为转变现状,提出以“拓展型数据生态”扩大主体范围、促进主体间高效互动,且其能够适应“新师范建设”对教师素养的更高要求。为落实“拓展型数据生态”这一新设想,可基于动态匹配、条件性互惠扩展数据网络;依据协作追踪数据促进认知的持续拓展;基于协同提质的实时数据不断更新保障体系。 Collaborative teacher education development is important for improving the quality of teacher education in weak institutions.Some studies have explored the ideal model of collaborative teacher education development based on ecological systems theory and actor-network theory,and found that heterogeneous subjects and negotiation of interests are essential.In contrast,the recently adopted"group model"points to the homogeneity of subjects and the unidirectional nature of benefit export,which are distant from the desirable state of collaborative development and may limit the scope of helping subjects and affect the willingness of helpers to continue to participate.In order to change the current situation,this paper proposes to expand the scope of subjects and promote efficient interaction among them with the"expanded data ecology",which can adapt to the higher requirements of"new normal construction"for teachers'literacy.In order to implement the new vision of"expanded data ecology",the data network can be expanded based on dynamic matching and conditional reciprocity;the cognition can be continuously expanded based on collaborative tracking data;the guarantee system is constantly updated based on the real-time data of collaborative quality improvement.
作者 李阳杰 LI Yangjie(Hangzhou Normal University,Hangzhou 311121)
出处 《中国高教研究》 北大核心 2024年第9期26-31,共6页 China Higher Education Research
基金 国家社会科学基金教育学青年课题“教育数字化转型下中小学教师数字负担的系统治理研究”(CHA240272) 浙江省社科规划“高校思想政治工作研究”专项课题“生成式人工智能时代高校思政课教师话语权的挑战及对策研究”(25GXSZ035YB)的研究成果。
关键词 师范教育 协同提质 创新路径 数据生态 teacher education collaborative quality improvement innovation path data ecology
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