A Sociological Lens on Linguistic Diversity: Implications for Writing Inclusive Multiple-Choice Assessments
Bibliographic record
Abstract
Multiple-choice questions (MCQs) are widely used in large introductory courses. Recent research focuses on MCQ reliability and validity and overlooks questions of accessibility. Yet, access to the norms of academic discourse embedded in MCQs differs between groups of first-year students. We theorize these norms as part of the institutionalized cultural symbols that reproduce social and cultural exclusion for linguistically diverse students. A sociological focus on linguistic diversity is necessary as the percentage of students who use English as an additional language (EAL), rather than English as a native language (ENL), has grown. Drawing on sociology as pedagogy, we problematize MCQs as a medium shaping linguistically diverse students’ ability to demonstrate disciplinary knowledge. Our multimethod research uses two-stage randomized exams and focus groups with EAL and ENL students to assess the effects of a modification in instructors’ MCQ writing practices in sociology and psychology courses. Findings show that students are more likely to answer a modified MCQ correctly, with greater improvement for EAL students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.072 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.011 | 0.078 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".