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Framed within the Theory of Mathematical Working Space, this exploratory study analysed the types of mathematical activities displayed by university students when formulating questions and requests to ChatGPT to solve a task involving real functions. To achieve this, the students’ personal working space that emerged from these interactions was characterised. The methodology was qualitative and interpretative, based on analysing the types of questions and requests addressed by the students to ChatGPT. A typology of questions was constructed, linked to the discovery, communication and reasoning planes, and an implicative analysis was applied to identify functional patterns. The results indicated that ChatGPT acted as a didactic artefact that reorganised students’ mathematical work, promoting processes of exploration, validation and argumentation. Among the conclusions, the study contributes to the understanding of the use of generative technologies in mathematics education.
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Tapia et al. (2026) studied this question.
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