Filling the gap in K-12 data literacy competence assessment: Design and initial validation of a questionnaire

Abstract

As the integration of AI-powered technologies in education grows, data literacy has become a key competence for educators, shaping their ability to navigate and utilize vast amounts of educational data. This study details the development of the Educators Data Literacy Self-Assessment (EDLSA), a questionnaire designed to assess perceived data literacy among K-12 teachers, focusing on its behavioural implications. The development of the EDLSA was rigorous. It involved an exhaustive qualitative review of frameworks and a pilot test in a teachers' Spanish sample (n = 66) provided relevant insights for refining the instrument. Finally, we conducted a comprehensive statistical analysis, which confirmed the instrument's robust reliability (α = 0.976) in measuring teachers' data management competence. The results of the factorial analysis in piloting primary and secondary education samples led to the readjustment of the proposed dimensions into three categories: comprehensive educational analytics, educational problem-solving through data, and promoting meta-learning students through data and ethical implications. Stemmed from the assessed competencies, the EDLSA instrument provides a comprehensive understanding of the human-computer interaction over data in educational settings. Overall, this self-assessment tool presents robust psychometric properties and a framework definition that paves the way for further development among teachers and researchers