Curriculum-Based Dynamic Assessment of Narratives: Benefits for Bilingual Filipino Children
Bibliographic record
Abstract
In 2021, people of Filipino origin arriving in Canada reached nearly one million, leading to rising numbers of Filipino children in Canadian schools (Statistics Canada, 2022). Filipino-speaking children who display challenges in learning the language of instruction may be referred for language assessment. However, standardized assessments are often not suited to children acquiring a second language, leading to inaccurate conclusions regarding their abilities. This set of studies examines the benefits of a novel curriculum-based dynamic assessment (CBDA) developed to assess the narrative abilities of children acquiring English as a second language. \nStudy 1 examined the accuracy of the CBDA in distinguishing typical language development (TD) from language difficulties (LD) for 34 bilingual Filipino children and compared the classification accuracy to the Test of Narrative Language – Second Edition (TNL-2; Gillam & Pearson, 2017). The results showed that the CDBA was an excellent predictor of language ability. \nStudy 2 examined narrative microstructure for children from Study 1 at pretest and posttest. Children in the TD group scored higher than the LD group on productivity measures at both pretest and posttest and on complexity measures at pretest. The TD group also improved on the productivity measures, while the LD group did not change on either the productivity or complexity measures. \nStudy 3 explored the modifiability ratings and performance on the TNL-2 of four kindergarten children with LD who participated in the first two studies, using a multiple case-study design. All four children showed difficulties answering wh-questions appropriately and warranted high examiner effort. They displayed differences in their learning preferences and potential and performed differently from one another on the TNL-2. \nStudy 4 explored Filipino-Canadian parents’ views on Filipino children’s narratives and on the usefulness of the CBDA through focus groups. They indicated that the story content was influenced by personal experiences common in the Filipino culture and described “good” stories as elaborated and structured in keeping with story grammar models. Lastly, parents appreciated the CBDA's focus on individual capabilities and its cultural sensitivity. \nTogether, the studies provide evidence that the CBDA of narratives is valuable for assessing Filipino- and English-speaking children and contributes to research on dynamic assessment for bilingual 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".