Empowering Educators: A Mixed-Methods Exploration for Data Intelligence Literacy

Abstract

In the era of digital transformation, the development of data intelligence literacy (DIL) among university foreign language teachers is crucial for enhancing the quality and efficiency of language education. This study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews, to assess the current state of DIL competence among university foreign language instructors. Through the analysis of teachers’ self-reported data literacy skills, practices, and challenges, the study identifies significant gaps in knowledge and application, particularly in areas such as data ethics, AI integration, and data-driven teaching strategies. Based on the findings, the paper proposes a comprehensive set of development strategies for enhancing DIL, including the establishment of targeted training programs, institutional support structures, and policy frameworks. The study provides actionable insights for educators, administrators, and policymakers aiming to foster a more data-literate teaching workforce in higher education.