DrawSim-PD: Simulating Student Science Drawings to Support NGSS-Aligned Teacher Diagnostic Reasoning
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Abstract (arXiv)
Developing expertise in diagnostic reasoning requires practice with diverse student artifacts, yet privacy regulations prohibit sharing authentic student work for teacher professional development (PD) at scale. We present DrawSim-PD, the first generative framework that simulates NGSS-aligned, student-like science drawings exhibiting controllable pedagogical imperfections to support teacher training. Central to our approach are apability profiles--structured cognitive states encoding what students at each performance level can and cannot yet demonstrate. These profiles ensure cross-modal coherence across generated outputs: (i) a student-like drawing, (ii) a first-person reasoning narrative, and (iii) a teacher-facing diagnostic concept map. Using 100 curated NGSS topics spanning K-12, we construct a corpus of 10,000 systematically structured artifacts. Through an expert-based feasibility evaluation, K--12 science educators verified the artifacts' alignment with NGSS expectations (>84% positive on core items) and utility for interpreting student thinking, while identifying refinement opportunities for grade-band extremes. We release this open infrastructure to overcome data scarcity barriers in visual assessment research.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 39 references that are in the map. First posted on arXiv 2 Feb 2026.
Builds on
13 of 39 references.
References · 13
- 2023GPT-4 Technical Reportcited by 18,132
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- 2023DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planningcited by 28
- 2024TeachTune: Reviewing Pedagogical Agents Against Diverse Student Profiles with Simulated Studentscited by 25
- 2025Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based Agentscited by 19
- 2024Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analyticscited by 18
- 2025TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learningcited by 11
- 2024MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasetscited by 10
- 2022Privacy-Preserving Synthetic Educational Data Generationcited by 9
- 2024Synthetic Multimodal Question Generationcited by 8
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