Authentic Assessment of Executive Functions in Early Childhood: A Scoping Review
Bibliographic record
Abstract
Executive functions (EFs) are cognitive skills that begin developing in early life and are crucial for children’s overall development and daily task performance. Generally, EFs are assessed through standardized neuropsychological tests, which may not always accurately capture real-world application. To overcome this limitation, alternative methods such as authentic assessment have emerged. A scoping review was conducted to map the information available regarding the authentic assessment of EFs in children under 6 years of age from 2010 to 2021. Out of 790 documents, 32 met the eligibility criteria after full-text revision. Two rating scales emerged as the most used EFs assessment instruments. The documents did not explicitly mention the term “authentic assessment.” Four commonly assessed EFs were identified. Findings highlight the need to develop multidimensional authentic assessment instruments to assess early EFs skills in all children. This includes children at risk or with developmental disabilities, and children from families with incomes below the poverty threshold.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".