Receptive and expressive English language assessments used for young children: a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: The majority of a child's language development occurs in the first 5 years of life when brain development is most rapid. There are significant long-term benefits to supporting all children's language and literacy development such as maximizing their developmental potential (i.e., cognitive, linguistic, social-emotional), when children are experiencing a critical period of development (i.e., early childhood to 9 years of age). A variety of people play a significant role in supporting children's language development, including parents, guardians, family members, educators, and/or speech-language pathologists. Speech-language pathologists and educators are the professionals who predominantly support children's language development in order for them to become effective communicators and lay the foundation for later developing literacy skills (i.e., reading and writing skills). Therefore, these professionals need formal and informal assessments that provide them information on a child's understanding and/or use of the increasingly complex aspects of language in order to identify and support the receptive and expressive language learning needs of diverse children during their early learning experiences (i.e., aged 1.5 to 9 years). However, evidence on what methods and tools are being used is lacking. METHODS: The authors will carry out a scoping review of the literature to identify studies and map the receptive and expressive English language assessment methods and tools that have been published and used since 1980. Arksey and O'Malley's (2005) six-stage approach to conducting a scoping review was drawn upon to design the protocol for this investigation: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and (6) consultation. DISCUSSION: This information will help these professionals identify and select appropriate assessment methods or tools that can be used to support development and/or identify areas of delay or difficulty and plan, implement, and monitor the progress of interventions supporting the development of receptive and expressive language skills in individuals with diverse language needs (e.g., typically developing children, children with language delays and disorders, children learning English as a second or additional language, Indigenous children who may be speaking dialects of English). Researchers plan to evaluate the effectiveness of the assessment methods or tools identified in the scoping review as an extension of this study.
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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 | 0.123 | 0.107 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.032 | 0.020 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.036 | 0.008 |
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".