Hybrid intelligence in the classroom: teachers’ perspectives on eye-tracking data-driven AI systems to support students during reading tasks

Artificial intelligence (AI) can act as a valuable partner for teachers. A particularly promising application is the use of AI as a hybrid-intelligence partner, leveraging eye-tracking data, to support students’ reading comprehension. This study examines the perceived preparedness and willingness of primary and secondary school teachers to adopt such technologies. Twenty teachers participated in semi-structured interviews. Vignettes were used to elicit reflections on system setups with different levels of human–AI collaboration. Participants expressed interest in technology that augments rather than replaces their professional role. Perceived benefits included visualising reading processes, supporting differentiation, enabling more independent student work, and providing feedback to adjust instruction. Ease of use was linked to intuitive dashboards and feasible classroom integration. Teachers emphasised the need for technological, pedagogical, subject-specific, and ethical knowledge, and identified trust and transparency as crucial. They also voiced concerns about reduced social interaction, screen-based reading, and possible erosion of human involvement. The exploratory findings point to the importance of hybrid-intelligence system designs that respect teachers’ autonomy and foreground usability, transparency, and pedagogical relevance. More broadly, the study offers insights for the design of hybrid-intelligent tools that respond to teachers’ needs and for a meaningful integration of technology into learning environments.