Toward Equitable Literacy Assessments: Development of a Clinically Informed Tool for Evaluating Early Reading Abilities of Bilingual Canadian Children
Bibliographic record
Abstract
Reading is essential for success, but difficulties are common. Early screening facilitates early identification and mitigates adverse outcomes. Current screeners are English-centric and biased against bi/multilingual children. They also assess acquired knowledge, causing floor effects, since children enter school with limited literacy knowledge. A screener that evaluates ability to learn and reduces linguistic bias addresses these issues. Engaging clinicians in tool development approach promotes clinical uptake. This dissertation aimed to develop a dynamic, linguistically quasi-universal, clinically informed reading screener, and to explore its performance with diverse Canadian kindergarteners.In Studies 1 and 2, extant literature on dynamic assessments (DAs) of word recognition skills was systematically reviewed following PRISMA guidelines, and results were used to (i) confirm that DA performance is associated with word reading, (ii) identify the target population for the novel tool in terms of age, language and reading status, and (iii) determine the characteristics of the novel tool in terms of skills assessed, format, administration method, and word and symbol type. Study 3 was a qualitative study, whereby Canadian speech-language pathologists (SLPs) were interviewed about their clinical-decision making and conceptualization of validity. Outcomes informed the tool’s clinical validity and how and why it should be used in practice. In Study 4, Canadian SLP students were surveyed about their demographic characteristics, including race, culture, and linguistic identity. Findings on students’ linguistic capacity supported creating a linguistically quasi-universal tool. In Study 5, the development of the novel tool, the Dynamic Omni-Language Literacy Screener (DOLLi), integrating results from Studies 1-4 was described. In a cross-sectional exploratory study, SLPs administered a DOLLi and a traditional English screener to diverse kindergarteners and provided feedback on the two tools. Student performance and clinical comments provided insights into DOLLi’s psychometric functionality and clinical utility. DOLLi is a promising new screener that has potential to reduce bias and provide clinically useful outcomes. Long term, tools like DOLLi can be used clinically as alternatives or supplements to traditional screeners to inform educational outcomes. In research, these types of tools are critical to support better understanding of literacy development, disorder manifestation, and impact of intervention for bi/multilingual children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".