Abstract
Large language models (LLMs) are quickly being adopted in educational contexts. In this editorial, we draw attention to three technically-oriented challenges educators may face using LLMs in educational settings when considering student-facing deployment: trust, privacy, and context dependence. Although these challenges are not as well-known as others, such as hallucination and interpretability, they pose significant concerns in educational settings if they are not understood and mitigated before implementation. We discuss practical challenges, risks, and research opportunities associated with each of these technical challenges.
| Original language | English (US) |
|---|---|
| Journal | Journal of Educational Computing Research |
| DOIs | |
| State | Accepted/In press - 2026 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Education
- Computer Science Applications
Keywords
- LLM
- benchmark
- large language model
- privacy
- small language model
- sycophancy
- trust
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