Date
Publisher
arXiv
The widespread availability of generative artificial intelligence tools poses new challenges for school mathematics education, particularly regarding the formative role of traditional mathematical tasks. In post-AI educational contexts, many activities can be solved automatically, without engaging students in interpretation, decision-making, or mathematical validation processes.
This study analyzes a secondary school classroom experience in which open mathematical tasks are implemented as a didactic response to this scenario, aiming to sustain students' mathematical activity. Adopting a qualitative and descriptive-interpretative approach, the study examines the forms of mathematical work that emerge during task resolution, mediated by the didactic regulation device COMPAS.
The analysis is structured around four analytical axes: open task design in post-AI contexts, students' mathematical agency, human-AI complementarity, and modeling and validation practices. The findings suggest that, under explicit didactic regulation, students retain epistemic control over mathematical activity, even in the presence of generative artificial intelligence.
Study at a glance
- Question: How do open math tasks and a regulatory framework shape students' mathematical work when generative AI is available?
- Setting and data: Secondary school math classroom, I.E. María Reiche in Peru; student written work, classroom interaction records, and teacher-researcher observations.
- Method: Qualitative descriptive-interpretative classroom study
Why it matters
Generative artificial intelligence can solve traditional math tasks automatically, threatening to displace students' sense-making, interpretation, and validation practices. Didactic regulation is needed to ensure students sustain active mathematical thinking in post-AI environments.
Key findings
- Open mathematical tasks without explicit numeric data prevented automatic AI solutions and required secondary students to formulate their own assumptions and mathematical models.
- Under explicit didactic regulation with the COMPAS device, students maintained epistemic control by using generative AI as a subordinate tool rather than accepting its outputs uncritically.
- Discrepancies between AI-generated answers and students' models created productive cognitive friction that stimulated collective argumentation, critical discussion, and mathematical validation.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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