AI Education — AI Ed Wiki

AI Education — the broad field encompassing both AI in education (using AI to teach) and AI literacy (teaching about AI). As the wiki's umbrella concept, AI education connects instructional technology, learning science, educational policy, and AI development.

Two dimensions of AI education

AI education research in the wiki spans two interconnected dimensions:

AI for education: Using AI to improve teaching and learning — AI tutoring, Automated Grading, Personalized Learning, Formative Assessment, and Learning Analytics.

Education about AI: Developing AI Literacy — teaching students and educators to understand, use, and critically evaluate AI. Prompt Engineering, Critical Thinking, and Ethics are core literacy components.

Cross-cutting themes

Evidence and evaluation: AI Ed Evaluation, randomized trials, and meta-analyses build the evidence base for what works.

Policy and governance: Educational Policy AI, Regulation, and AI Governance Education address the institutional frameworks needed for responsible AI adoption.

Equity and access: Equity and Bias Mitigation research examines whether AI education serves all learners.

Teacher preparation: Teacher AI Competency and Faculty Development ensure educators are prepared for AI-augmented classrooms.

Field maturity

The wiki reflects a field in rapid evolution — from early ITS research to LLM-driven tutoring, from detection-focused academic integrity to assessment redesign, from tool-centric studies to sociotechnical frameworks.