Preparing Students for AI-Powered Materials Discovery: A Workflow-Aligned Framework for AI Literacy, Equity, and Scientific Judgment

Dongming Mei, Katherine Moore, Ben Sayler (2026) — Framework for integrating AI literacy with materials science education.

📄 Full text (arXiv)

Key Findings

This paper presents a workflow-aligned framework for preparing students to use AI in materials discovery. The authors argue that in materials science, the limiting factor is no longer only algorithmic capability but human-AI collaboration competence. Students need to develop scientific judgment about when to trust AI predictions and how to integrate them into research workflows.^[raw/papers/2605.09624.md]

The framework connects AI literacy to equity and scientific judgment, emphasizing that students from under-resourced backgrounds may lack exposure to AI-powered research workflows. This intersects with broader equity-in-ai-education and stem-education concerns.^[raw/papers/2605.09624.md]

Connections to AIED

The materials discovery context offers a model for how AI literacy should be taught across STEM disciplines: not as abstract knowledge, but as embedded workflow competence. This connects to agentic-workflows-education where students learn to use AI tools as part of authentic research practice rather than as separate subjects.^[raw/papers/2605.09624.md]

The framework also touches on metacognition — students need to develop judgment about AI outputs, which requires meta-awareness of their own reasoning processes when evaluating AI-generated predictions.

Related Pages

• ai-literacy — AI literacy as embedded workflow competence, not abstract knowledge

• equity-in-ai-education — Under-resourced students lack exposure to AI-powered research workflows

• stem-education — Materials science as a domain for AI integration in STEM curricula

• metacognition — Developing judgment about AI outputs requires metacognitive awareness

• agentic-workflows-education — AI tools as part of authentic research practice

Citation

APA: Mei, D., Moore, K., & Sayler, B. (2026). Preparing students for AI-powered materials discovery: A workflow-aligned framework for AI literacy, equity, and scientific judgment. arXiv:2605.09624.