Kim Jeonghyun, Hong Lingzi, Yoon Ayoung
Department of Information Science, University of North Texas, Denton, TX, United States of America.
Anuradha and Vikas Sinha Department of Data Science, University of North Texas, Denton, TX, United States of America.
PLoS One. 2025 Apr 28;20(4):e0322104. doi: 10.1371/journal.pone.0322104. eCollection 2025.
As data literacy has emerged as a critical skill for professionals across industries, educators in higher education have incorporated it into their curricula and instruction. Understanding and evaluating the factors that shape an individual's data literacy is important for benchmarking proficiency and tailoring curricula, yet the underlying components and structure of data literacy for students in four-year institutions are unknown. This study validated the Data Literacy Self-Efficacy Scale (DLSES) with 1,816 students enrolled in two four-year institutions. Exploratory and confirmatory factor analyses were conducted to determine the construct of the scale, and the item analysis was used to address the validity of the items on the scale. The exploratory factor analysis identified eight distinct factors comprising 29 items. The results of confirmatory factor analysis showed a good model fit, CFI = 0.994, TLI = 0.994, RMSEA = 0.053, SRMR = 0.044. This study demonstrated the 29-item refined version of the DLSES to be a reliable and valid tool for measuring individuals' self-efficacy levels for data literacy. Furthermore, the scale could form the basis for curriculum development and help educators design targeted interventions that address specific learning needs.
随着数据素养已成为各行各业专业人士的一项关键技能，高等教育领域的教育工作者已将其纳入课程和教学中。了解和评估影响个人数据素养的因素对于衡量能力水平和量身定制课程很重要，但四年制院校学生数据素养的潜在组成部分和结构尚不清楚。本研究对1816名就读于两所四年制院校的学生进行了数据素养自我效能量表（DLSES）的验证。进行了探索性和验证性因素分析以确定该量表的结构，并使用项目分析来检验量表上各项目的有效性。探索性因素分析确定了由29个项目组成的八个不同因素。验证性因素分析结果显示模型拟合良好，CFI = 0.994，TLI = 0.994，RMSEA = 0.053，SRMR = 0.044。本研究表明，DLSES的29个项目精炼版是测量个人数据素养自我效能水平的可靠且有效的工具。此外，该量表可为课程开发奠定基础，并帮助教育工作者设计针对特定学习需求的有针对性的干预措施。
