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Record W2111644878 · doi:10.1177/1356336x06069274

A school-based movement programme for children with motor learning difficulty

2006· article· en· W2111644878 on OpenAlexaff
Juha-Pekka Männistö, Marja Cantell, Tommi Huovinen, Libbe Kooistra, Dawne Larkin

Bibliographic record

VenueEuropean Physical Education Review · 2006
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMotor skillMotor learningPsychologyMovement assessmentSession (web analytics)Intervention (counseling)PopulationMovement (music)Psychomotor learningRelaxation (psychology)Task (project management)Physical medicine and rehabilitationPhysical therapyDevelopmental psychologyMedicineCognitionComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

The study investigated the effectiveness of a school-based movement programme for a population of 5 to 7 year old children. Performance profiles on the Movement ABC were used to classify the children and to assess skill changes over time. Children were assigned to four different groups: motor learning difficulty (n = 10), borderline motor learning difficulty ( n = 5), trained controls ( n = 9), untrained controls ( n = 9). The total programme consisted of 26 weekly sessions. Each one-hour session comprised of structured group play, individualized skill training, and relaxation. The results showed that children with motor learning difficulty improved consistently in the targeted skills. Most importantly, the obtained effects persisted beyond the actual intervention. The findings emphasize the effectiveness of task-oriented approaches in a school-based setting for children with motor learning difficulty.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.835

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)0.0000.001

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.

Opus teacher head0.014
GPT teacher head0.288
Teacher spread0.274 · 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 designOther design
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".

Quick stats

Citations15
Published2006
Admission routes1
Has abstractyes

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