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Abstract As use of artificial intelligence (AI) has increased, concerns about AI bias and discrimination have been growing. This paper discusses an application called PyrEval in which natural language processing (NLP) was used to automate assessment and provide feedback on middle school science writing without linguistic discrimination. Linguistic discrimination in this study was operationalized as unfair assessment of scientific essays based on writing features that are not considered normative such as subject‐verb disagreement. Such unfair assessment is especially problematic when the purpose of assessment is not assessing English writing but rather assessing the content of scientific explanations. PyrEval was implemented in middle school science classrooms. Students explained their roller coaster design by stating relationships among such science concepts as potential energy, kinetic energy and law of conservation of energy. Initial and revised versions of scientific essays written by 307 eighth‐grade students were analyzed. Our manual and NLP assessment comparison analysis showed that PyrEval did not penalize student essays that contained non‐normative writing features. Repeated measures ANOVAs and GLMM analysis results revealed that essay quality significantly improved from initial to revised essays after receiving the NLP feedback, regardless of non‐normative writing features. Findings and implications are discussed. Practitioner notesWhat is already known about this topicAdvancement in AI has created a variety of opportunities in education, including automated assessment, but AI is not bias‐free.Automated writing assessment designed to improve students' scientific explanations has been studied.While limited, some studies reported biased performance of automated writing assessment tools, but without looking into actual linguistic features about which the tools may have discriminated.What this paper addsThis study conducted an actual examination of non‐normative linguistic features in essays written by middle school students to uncover how our NLP tool called PyrEval worked to assess them.PyrEval did not penalize essays containing non‐normative linguistic features.Regardless of non‐normative linguistic features, students' essay quality scores significantly improved from initial to revised essays after receiving feedback from PyrEval. Essay quality improvement was observed regardless of students' prior knowledge, school district and teacher variables.Implications for practice and/or policyThis paper inspires practitioners to attend to linguistic discrimination (re)produced by AI.This paper offers possibilities of using PyrEval as a reflection tool, to which human assessors compare their assessment and discover implicit bias against non‐normative linguistic features.PyrEval is available for use ongithub.com/psunlpgroup/PyrEvalv2.
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This content will become publicly available on November 26, 2025
Epistemic Marginalization and Methodology 50 Years after The Death of White Sociology
In its original form, the following essay was the closing keynote address of the annual meeting of the Sociology of Education Association (SEA), held in Monterey, California on February 20, 2023. That year was the 50th anniversary of both the founding of SEA and the publication of the landmark volume, The Death of White Sociology. In commemorating these events and assessing how the field of sociology has changed 50 years later, this essay juxtaposes the promise of critical quantitative and computational methods (CritQCM) with the problems of epistemic marginalization highlighted in the volume. After describing the rich theoretical diversity foregrounding the critical quantitative and computational movement, the discussion elaborates on three epistemic threats to the aim of the movement to develop and practice counter-hegemonic methodologies. These threats include (1) the qualitative-quantitative divide, (2) White norms and Black epistemic rigor, and (3) normative theory privileging. The essay concludes by contextualizing these epistemic threats with the nation’s current challenge of anomie, which has destabilized normative processes of knowledge recognition, and considers ways CritQCM might respond.
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- Award ID(s):
- 2321179
- PAR ID:
- 10556896
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Sociology of Race and Ethnicity
- Volume:
- 11
- Issue:
- 1
- ISSN:
- 2332-6492
- Format(s):
- Medium: X Size: p. 1-16
- Size(s):
- p. 1-16
- Sponsoring Org:
- National Science Foundation
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