Toward measuring data literacy for higher education: Developing and validating a data literacy self‐efficacy scale
Jeonghyun Kim, Lingzi Hong, Sarah Evans
Abstract
Abstract Data literacy, a multifaceted competency in working with data, has emerged as an essential skill that holds significance in both personal and professional lives. Nonetheless, there is a lack of a precise definition of data literacy, and individuals' perceptions of their data literacy have not been thoroughly investigated. This study aims to develop and validate a scale designed for measuring self‐efficacy in data literacy within the context of higher education. Both exploratory and confirmatory factor analyses were conducted to determine construct validity and reliability. The resulting data literacy self‐efficacy scale comprises 31 items organized into three factors: data identification, data processing, and data management and sharing. These factors represent distinct yet interconnected dimensions, highlighting the multifaceted nature of data literacy.