Ability or Access-ability: Differential Item Functioning of Items on Alternate Performance-Based Assessment Tests for Students with Visual Impairments
Bibliographic record
Abstract
Introduction This study investigated differential item functioning (DIF) of test items on Pennsylvania's Alternate System of Assessment (PASA) for students with visual impairments and severe cognitive disabilities and what the reasons for the differences may be. Methods The Wilcoxon signed ranks test was used to analyze differences in the scores of the students with visual impairments and severe cognitive disabilities who took the Grade 3–4 or 7–8 Level A PASA compared to matched peers without visual impairments. The students with visual impairments were analyzed as a group and by level of functional vision. Logical analyses of videotaped assessments of the students with visual impairments were conducted to identify potential sources of DIF. Results Among the functional vision groups, 17 instances in reading and 22 instances in math were flagged for DIF, with 14 skills in reading and 13 in math emerging as harder for students with visual impairments. The types of items that were significantly different included those involving money, matching, and selecting the smallest. Potential reasons for the differences included students needing a better orientation to test materials; the influence of lucky guesses based on distractor characteristics; and the influence of accommodations, such as the substitution of objects. Discussion The results demonstrate the complexity and importance of evaluating the validity of alternate performance-based assessments for students with visual impairments and severe cognitive disabilities. The themes that emerged suggest the need to structure alternate assessment tasks for consistent orientation to materials and to consider closely how accommodations affect the difficulty of the tasks. Implications for practitioners Practitioners should consider how the reading progression for their students with visual impairments and severe cognitive disabilities is related to alternate standards and the instruction that is in place to learn concepts that were missed incidentally. Practitioners can help improve alternate assessments by communicating with their states about the types of tasks that are difficult to accommodate in their current format or by requesting guidance in making meaningful accommodations that maintain the intent of the items.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".