ASSESSING PHYSICAL LITERACY OF PRE-SCHOOL CHILDREN – A SYSTEMATIC LITERATURE REVIEW
Bibliographic record
Abstract
In recent years, it has become topical to study the concept of physical literacy in early childhood, based on empirical evidence of how the formation of skills takes place at this stage. The question remains open for the researchers - how to standardize and simply assess the physical literacy given its broad framework. One of the definitions of physical literacy explains the essence and importance of this concept in a person's life as internal motivation, confidence, competence in physical activities, knowledge and the person's own responsibility for applying it in practice. The systematic literature review was conducted with the aim of identifying a safe, sustainable and easy-to-apply physical literacy assessment tool for preschool children aged 3 to 7 years. Methodology. The systematic literature review protocol includes sources from such databases as EBSCO host (MEDLINE, Eric), Google Scholar, Science Direct, ERIH PLUS, Scopus and Web of Science for the period 2018 – 2024, which title, summary and keywords meets the certain criteria and content includes information on physical literacy assessment tools for the age specified. The content analysis was performed for the identified tools to find out their relevance for the assessment of physical, affective, cognitive, and participatory domains of physical literacy. Results. As a result of the content analysis, 26 different tools for assessing physical literacy in pre-school age were identified. The most commonly used instrument is the Test of Gross Motor Development by Ulrich. For the assessment of all four domains of physical literacy at preschool age, three tools were identified – Pre -PLAy, a set of tools based on the guidelines of Canadian Assessment of Physical Literacy, and the Nine-Step Assessment Approach based on Australian Physical Literacy Framework. Conclusions. The content analysis led to the conclusion that there is a small number of unified universal tools that can be applied at preschool age and would include four domains of physical literacy. The research directions of physical literacy assessment tools at pre-school age are the following: development and validation of a universal tool or tool sets, application of smart technologies, virtual reality and remote assessment possibilities in the evaluation process.
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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 | 0.016 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".