LLM feedback for students marked by race, language, disability, gender, or motivation shows positive feedback bias and feedback withholding bias — more praise and less substantive critique than for unmarked counterparts¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · no dated study recorded · checked against its sources 2026-10-17 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? Students identified as Black, Hispanic, Asian, female, unmotivated, and learning-disabled received less constructive criticism and more praise than their counterparts, reflecting feedback withholding and positive feedback biases. → Tan et al. 2026

Evidence¶

Tan et al. 2026¶

Mei Tan, Lena Phalen, and Dorottya Demszky. 2026. Marked Pedagogies: Examining Linguistic Biases in Personalized Automated Writing Feedback. In LAK 2026: 16th International Learning Analytics and Knowledge Conference (LAK 2026). ACM, New York, NY, USA. doi:10.1145/3785022.3785113

q2 · i? · causal · r2

Cross-condition lexical comparison of feedback generated for the same 600 essays under marked versus comparative prompts; the article reports the praise asymmetry as a qualitative pattern across conditions with no printed effect size. In some cases praise took stereotyped forms, with "love" used disproportionately with female students and "powerful" appearing only for Black students.

"students identified as Black, Hispanic, Asian, female, unmotivated, and learning-disabled received less constructive criticism and more praise, reflecting both feedback withholding [ 11] and positive feedback biases [ 20]."

Studies bearing on this claim¶

Does automated feedback on student work substitute praise for critique, and for whom? This table gathers the studies behind this claim and the 4 narrower claims that bear on it: 3 distinct studies (2 associational, 1 causal), q2, 0 of 3 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

Related Claims¶

• Gender prompts shift feedback stance: female students receive affective, first-person, empathy-oriented feedback while male students receive objective, task-oriented critique — related
• Race prompts elicit culturally stereotyped feedback: Black, Hispanic, and Asian students are positioned through cultural or linguistic stereotypes while White students receive argument-structure feedback — related
• Motivation prompts shift feedback tone: unmotivated students receive enthusiastic, collaborative encouragement while motivated students receive direct, higher-level critique — a narrower finding that bears on this claim
• Names alone elicit weaker, less consistent identity-marked feedback language than explicit attribute prompts — related
• Explicitly prompting a student attribute produces large, systematic increases in the concentration of stereotype-aligned marked words in LLM-generated writing feedback — related
• LLM feedback sentiment tracks assigned scores: low scores come with more criticism, high scores with more praise — related
• Feedback alerts orienting children to upcoming feedback appear in about half of feedback conditions and are least frequent for ages 10-11 — related