面向高等教育教师的数据素养分析框架开发和评估:结构方程建模方法

Development and Assessment of a Data Literacy Analysis Framework for Higher Education Faculty:A Structural Equation Modeling Approach

随着信息和通信技术的快速发展,教师数据素养已成为现代教育领域的一个重要趋势.该文基于高等教育教师数据素养的现状和需求,提出一种基于结构方程建模方法的教师数据素养分析框架,旨在探索一种可行的方法来提高教师数据素养水平.通过研究教师的技术整合自我效能感、技术知识水平、对技术的态度以及使用社交网络的目的与他们数据素养水平之间的关系,阐明和分析了数据素养水平与这些变量之间的关系.使用结构方程模型对来自415名教师的数据进行分析,查看变量之间的相关性,并确定哪些预测因素对教师数据素养能力影响最大.同时,通过对定量数据结果进行分析,验证和评估该文所提出的分析框架.采用关系筛选模型,在研究结果审查的模型中检测到教师的技术整合自我效能感是最重要的变量,对数据素养水平的预测具有重要影响.该文结果有助于指导并提升教师数据素养水平,达到提高教育教学质量和效果的目的.

With the rapid development of information and communication technologies,data literacy of the teacher has become an important trend in modern education.Based on the current situation and needs of data literacy of teachers in higher education,this paper proposes a framework for analyzing teachers data literacy based on a structural equation modeling approach,aiming to explore a feasible method to improve the level of teachers data literacy.This paper clarifies and analyzes the relationship between the level of data literacy and these variables by examining the relationship between teachers technology integration self-efficacy,level of technology knowledge,attitudes toward technology,and purpose of using social networks and their level of data literacy.Data from 415 teachers were analyzed using structural equation modeling to examine correlations between variables and to determine which predictors had the greatest impact on teachers data literacy competencies.The quantitative data results were also analyzed to validate and evaluate the proposed analytical framework.A relational screening model was also used in this study.In the model reviewed based on the obtained findings,it was detected that the most important variable in the prediction of data literacy levels was teachers technology integration self-efficacy.These results can help guide and enhance teachers data literacy levels for the purpose of improving the quality and effectiveness of education and teaching.