教师数据素养评价指标体系研究

Research on Evaluation Index System of Teacher's Data Literacy

近年来,大数据在教育领域的应用将教育推向了实证时代,使得教育活动不再仅依靠理念和经验来展开。使用数据促进教学管理和优化决策成为时代要求,而大数据应用于教学过程的关键在于培养具备数据素养的教师。研究旨在构建一个教师数据素养评价指标体系,采用文献分析法、德尔菲法和层次分析法等方法进行研究,分析了教师数据素养及其能力的构成要素,设计了评价指标集,包括数据知识、数据技能、教学应用、意识道德4个一级指标,数据获取、数据管理等10个二级指标,以及涉及具体能力的26个三级指标。12位专家参与了指标体系的修订,基于专家打分计算出指标项的权重,形成完整的教师数据素养评价指标体系。最终,对指标体系进行了小规模的试用,评估了16位教师的数据素养,验证了指标体系的科学性和可用性。

In recent years, because of the application of big data in the field of education, education has stepped into empirical era, and as a result, educational activities no longer only rely on ideas and experience. It has become a requirement to use data to promote teaching management and optimized decisions, while the key to the application of big data in teaching is to cultivate teachers with data literacy. In order to construct an evaluation index system of teacher＇s data literacy, this research adopts literature analysis, Delphi method and AHP method to analyze the components of teacher＇s data literacy and their abilities, and designs an evaluation index set, including 4 first-level indicators （data knowledge, data skills, teaching applications, and ethical awareness）, 10 secondary-level indicators such as data acquisition, data management, and 26 third-level indicators involving specific skills. 12 experts participate in the revision of the indicator system. The weight of the index item is calculated based on experts＂ scores to form a complete evaluation index system. Finally, the evaluation index system is tested on a small scale, and the data literacy of 16 teachers is evaluated for the verification of the scientific and usability of it.