Open Mathematical Tasks as a Didactic Response to Generative Artificial Intelligence in Post-AI Contexts

TL;DR

This paper explores how open mathematical tasks, supported by didactic regulation, can maintain student engagement and epistemic control in classrooms affected by the rise of generative AI tools.

Contribution

It introduces a didactic approach using open tasks and regulation devices to sustain mathematical activity and agency amid AI automation in education.

Findings

Students retain epistemic control with explicit regulation.

Open tasks promote mathematical agency in AI-affected contexts.

Didactic regulation supports human-AI complementarity.

Abstract

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.