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¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · no dated study recorded · checked against its sources 2026-10-16 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? Feedback for Black-prompted essays invoked collective identity, systemic contexts, and social change; Hispanic-prompted feedback emphasized English corrections and cultural frames; Asian-prompted feedback emphasized education, respect, and academic English; White-prompted feedback focused on argument structure and evidence. → 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

Qualitative and lexical analysis (Table 4, words with |z| > 1.96 shared across models) of feedback generated under Black, Hispanic, Asian, and White prompt conditions for the same essays. Distinctive words included systemic, stereotype, culture, family, and formal. No effect size is printed for the pattern.

"These patterns suggest a Marked Pedagogy in which Black, Hispanic, and Asian students are positioned through cultural or linguistic stereotypes, while White students are positioned as competent writers invited to refine argument structure and reasoning."

Discussion¶

Learner Variables¶

• Identity — moderator: an instructional effect differs with it

Related Claims¶

• AI systems are non-neutral socio-technical artifacts embedding cultural assumptions and power relations — the general claim this finding bears on, with the studies behind it

• Teacher expectation bias predicted Dutch secondary students' performance up to five years later, after controls for prior achievement, IQ and motivation, in one large correlational cohort study — the general claim this finding bears on, with the studies behind it

• Feedback prompted with ELL status narrows to surface-level grammar and mechanics corrections, assuming limited language competency rather than addressing argument and reasoning — related
• 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 — related
• 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
• In the analyzed school ethnography, stereotyping operates as a rationalization process that constructs uniformities, and the ghetto label privileges white culture's standards and evaluation networks — related
• In the analyzed school setting, black girls experience testimonial injustice as direct discrimination and hermeneutical injustice as indirect, structural discrimination that personal effort cannot erode — related
• Cultural processes and forms of epistemic injustice should be taken into account in understanding how inequalities in education are produced and maintained — related
• In the ethnography the article analyzes, black girls bussed to an affluent suburban school were unpopular and socially excluded for being seen as loud and ghetto, while black boys were classified as incapable of academic achievement — related
• Automated grading systems may produce systematically inequitable outcomes for international and non-Western students — a broader claim this one bears on
• Educators cautiously support AI for culturally responsive content generation while fearing cultural biases and stereotypes in AI output — related