{
  "abstract": "Generative artificial intelligence (AI) can produce apparently complete mathematics lesson plans within seconds, raising a central question for teacher education: how can pre-service teachers use AI-generated resources while remaining responsible for mathematical and pedagogical design? This qualitative study investigates AI-supported lesson design during an 11-week course at a Chinese university. Data comprised AI dialogues, reports, three lessonplan versions, microteaching videos, and evaluation reports from 20 participants; three focal cases were examined through follow-up interviews. Drawing on the Documentational Approach to Didactics and Teacher Design Capacity, we propose AI-supported Teacher Design Capacity (AI-TDC) as an analytical construct characterising five interrelated dimensions of knowledge-in-action: Orienting, Verifying, Transforming, Regulating, and Collectivising. The focal cases revealed contrasting configurations in which AI became a mediating hub, a task-specific mediator, or a supplementary reviewing resource; these configurations could not be reduced to interaction volume. AI-generated resources became components of teaching documents through mathematical and didactical transformation: participants reorganised conceptual relations, constructed problem sequences, and selectively retained or rejected proposals according to intended mathematical trajectories for students. The course created opportunities for such work through cycles of individual design, collective scrutiny, enactment, and redesign. AI-TDC thus offers a framework for analysing and supporting documentational work with AI in mathematics teacher education.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "Chongyang Wang"
    },
    {
      "name": "Luc Trouche"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c2s9h1papnn70.bib",
  "cited_by": 0,
  "doi": null,
  "fulltext_url": null,
  "id": "c2s9h1papnn70",
  "issns": [],
  "landing_url": "https://hal.science/hal-05740229v1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.math"
    ],
    [
      "hal",
      "0.shs"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://hal.science/hal-05740229/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c2s9h1papnn70.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:29Z",
      "native_id": "hal-05740229",
      "source": "hal",
      "url": "https://hal.science/hal-05740229v1"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "hal:0.math",
      "subfield": "general"
    }
  ],
  "title": "When AI Becomes a Resource: AI-Supported Teacher Design Capacity in Mathematics Teacher Education",
  "title_text": "When AI Becomes a Resource: AI-Supported Teacher Design Capacity in Mathematics Teacher Education",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:29Z",
  "url": "https://research.draconitic.com/paper/c2s9h1papnn70",
  "venue": "HAL",
  "versions": []
}