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Record W7112987620

Exploration and analysis of the interactions between physical literacy domains in school contexts

2025· dissertation· en· W7112987620 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of Digital Objects for Teaching Research and Culture (University of Valencia) · 2025
Typedissertation
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionCompetence (human resources)Construct (python library)LiteracyMotor skillProtocol analysisCognitive developmentAffect (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

Physical Literacy (PL) has become consolidated over the past decade as a key construct for understanding comprehensive child development, by integrating physical, cognitive, psychological, and social dimensions. From a holistic perspective, PL is not limited to the acquisition of motor skills, but encompasses motivational, emotional, social, and cognitive aspects that directly influence active participation in movement contexts and, by extension, in students’ global development. Within this framework, the main objective of this doctoral thesis is to analyze the interaction between the different domains that constitute PL and their relationship with relevant educational variables, such as cognitive and academic performance, in real school settings. The thesis is structured around three complementary empirical studies, designed to advance the theoretical and applied understanding of PL and its connection with learning. The first study addresses a major methodological gap identified in the literature: the lack of tools that enable the simultaneous assessment of motor competence (MC) and cognitive performance in ecological conditions. To address this limitation, an innovative instrument was designed and validated based on the dual-task paradigm, adapting the Canadian Agility and Movement Skill Assessment (CAMSA) to include cognitive demands. This new test, called the Cognitive CAMSA (CAMSA-C), makes it possible to observe students’ joint performance when simultaneously facing motor and cognitive demands. The results show a significant decrease in motor performance under dual-task conditions (e.g., execution time and total score), compared to the single-task motor condition. Additionally, differentiated student profiles with varying performance patterns were identified, demonstrating that cognitive interference does not affect all students equally. While some maintain stable performance across conditions, others show improvements or declines depending on the nature of the task. These conclusions reinforce the value of CAMSA-C as a tool for integrated assessment of MC and cognitive performance, with strong potential for tailoring educational interventions to students’ specific performance profiles. The second study adopts a person-centered approach with the aim of identifying PL profiles among primary school students. Based on representative variables from the physical (e.g., MC, cardiorespiratory fitness [CRF]), psychological (e.g., perception of MC, perceived PL), and social (e.g., social identity, perceived social support) domains, six distinct profiles were identified using cluster analysis. These profiles were subsequently analyzed in relation to academic and cognitive performance. The results show that students with more balanced profiles—characterized by high levels across all three domains—also achieve better school performance (i.e., academic grades) and cognitive outcomes (i.e., math fluency and Stroop test performance). Conversely, students with lower levels in these domains presented the weakest cognitive outcomes, highlighting the combined influence of these factors on children’s development. This approach provides a richer and more complex understanding of development and reinforces the explanatory value of PL as a multidimensional construct that goes beyond fragmented views of physical and cognitive domains. The third study focuses on the psychological and motivational mechanisms that may mediate the relationship between MC, CRF and academic performance. A multiple mediation model was proposed and tested, incorporating variables such as self-determined motivation for physical activity, perceived MC, perceived physical fitness, academic self-perception, and perceived PL. The results confirm that both perceived PL and academic self-perception play a key mediating role in this relationship, explaining how physical capacities translate into better school outcomes through processes of self-perception and motivation. Additionally, the study examines the predictive role of physical activity. It was observed that its influence varies depending on the type of measurement used: self-reported physical activity predicts academic performance only when MC acts as the first mediator, while objectively measured moderate-to-vigorous physical activity predicts performance only when CRF occupies that position. These findings suggest differentiated pathways of influence, in which perceived physical activity reflects qualitative aspects related to self-perception and activity diversity, whereas objectively measured physical activity reflects effort intensity and duration, more closely related to physiological adaptations. Overall, this thesis provides robust, rigorous, and up-to-date empirical evidence on the explanatory value of PL in school contexts. The findings from the three studies highlight the need to adopt an interdisciplinary perspective that integrates physical, cognitive, psychological, and social factors involved in child development and learning. Furthermore, they position PL as a valuable conceptual and practical framework for designing more inclusive and contextualized educational interventions aimed not only at improving MC, but also at promoting students’ emotional well-being, motivation, and academic success throughout their schooling years.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.341
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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