Integration of Artificial Intelligence and Data Literacy in Lower Secondary Education: Analysis of Perceptions and Conditions for Adoption

Abstract

The present study, through an explanatory sequential mixed-methods design, presents the results of the third phase of the IADE project, which focuses on analyzing Data Literacy (DL) for the use of Learning Analytics (LA) and the adoption of Artificial Intelligence (AI) among lower secondary education teachers in Catalonia. The quantitative phase included a validated questionnaire administered to teachers from different schools, yielding 372 responses. The results reveal low and homogeneous levels of LA use, as well as an emerging and uneven adoption of AI tools. The qualitative phase, conducted through a focus group with professionals representing diverse institutional profiles, made it possible to identify nine categories describing the barriers, needs, and conditions surrounding the use of data and AI in schools.

Findings indicate a predominantly reactive approach to data management, the absence of clear institutional frameworks, an exploratory and non-systematic use of AI, and a strong concern for privacy and procedural coherence. The triangulation of data reinforces the need for educational policies that strengthen teacher training, institutional leadership, and the ethical and contextualized adoption of AI. The study provides implications for the design of training strategies, regulatory frameworks, and support actions that foster a meaningful integration of AI and DL for the use of LA in lower secondary education.