Angxuan Chen & Jiyou Jia (2026) — arXiv:2606.00040.
Identifies interaction signatures of LLM literacy using Epistemic Network Analysis (ENA) on logs from 162 students. High-literacy students exhibit iterative, strategic refinement and dense cognitive networking, while low-literacy students rely on direct, linear commands. This work emphasizes that ai-literacy is a developmental capacity requiring structured scaffolding and prompt-engineering discipline. It connects to the need for curriculum-design that targets metacognition and agentic-workflows rather than just syntax mastery.
Related Pages
- ai-literacy — central theme of current research
- scaffolding — critical for effective AI interactions
- curriculum-design — institutional response to agentic shifts
- metacognition — the barrier to uncritical reliance
- agentic-workflows — the professional future of AI use