Bias Mitigation

Bias mitigation in educational AI requires auditing models across the pipeline: Gender Bias Transfer LLM Writing, AI Scoring Language Bias Physics, LLM Cultural Relevance K12, and Equity (merged into Equity) document bias sources and mitigation strategies from data curation to prompt design.

Bias mitigation in AIED concerns identifying and reducing unfair, identity-patterned behavior in AI tutors and educational systems (e.g., differential refusals or softening of answers for marginalized students). Surfaced by recent auditing work on LLM history tutors.

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