Conference Program

In recent decades, educational systems have faced increasing tension between standardized teaching models and the need to address the diversity of students’ trajectories, interests, and sociocultural contexts (Matosas López, 2019). In this scenario, personalized learning has emerged as a relevant educational approach aimed at adapting learning experiences to the characteristics, motivations, and needs of learners (Gunawardena et al., 2024). At the same time, digital technologies have expanded the possibilities for designing, implementing, and scaling personalized learning processes through virtual platforms, adaptive systems, learning analytics, and artificial intelligence.

Despite these opportunities, literature highlights significant conceptual, pedagogical, and ethical tensions associated with technology-mediated personalization. In many cases, technological proposals reduce personalization to algorithmic adaptation mechanisms detached from strong pedagogical frameworks and the participation of educational actors (Bartolomé et al., 2018; Vanbecelaere & Benton, 2021). This situation has generated concerns regarding the autonomy of learners and the evolving role of teachers in highly technologized learning environments (Salazar et al., 2024).

From this perspective, we seek the most relevant strategies to incorporate artificial intelligence and learning analytics in secondary school classrooms. We approach it from a critical perspective on the incorporation of digital technologies in education (Macgilchrist, 2021), as well as from a pedagogical perspective far from techno-solutionism (Morozov, 2013) and the submission of classrooms to the logic of techno-feudalism (Durand, 2020). At the same time, we recognize that several countries have incorporated AI into their curricula (UNESCO, 2023), in a transnational framework that promotes digital teaching competence (Punie, 2017), expanded with AI competence for teachers (Miao & Cukurova, 2024) and students (Miao et al., 2024). We give teachers the role of mediator in the incorporation of educational technology with pedagogical meaning (Puentedura, 2013), with the possibility of designing learning scenarios.

In this context, co-design has gained increasing relevance in educational research as a participatory methodology that enables collaborative processes among teachers, students, and other stakeholders in the design of curricula, learning environments, and technological solutions (Westbroek et al., 2019; Zeivots et al., 2024). Codesign emphasizes horizontal collaboration, contextual relevance, and shared ownership of educational innovation. From this perspective, co-design may represent a promising strategy for developing more participatory and pedagogically grounded approaches to technology-mediated personalized learning.

This study analyzes the challenges and possibilities that codesign initiatives may represent for strengthening teachers’ agency and pedagogical mediation in implementing personalized learning strategies supported by artificial intelligence and learning analytics. The research was conducted in four educational centers where teachers participated in structured co-design processes aimed at developing strategies for personalized learning supported by digital technologies. Three collaborative sessions were planned in which teachers identified pedagogical needs, explored technological possibilities, and designed strategies for personalization within their institutional contexts.

Among other findings, the results show tensions regarding the appropriation of the IA and AA by teacher communities. Lack of technical knowledge about the functioning of these digital tools, as well as a perceived lack of clarity in institutional policy and school organization regarding the integration of AI and AA, may explain this scenario.