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Record W3186104075 · doi:10.36315/2021end145

A MOTOR INTERVENTION TO PREPARE LEARNING TO WRITE

2021· article· en· W3186104075 on OpenAlexaff
Natalie Lavoie, Émile Lebel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsCégep de RimouskiUniversité du Québec à Rimouski
Fundersnot available
KeywordsHandwritingReadabilityMotor skillTest (biology)PsychologyIntervention (counseling)Gross motor skillComputer scienceMathematics educationDevelopmental psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Writing is a complex activity that requires the automation of graphomotor skills. Unfortunately, 10 to 30% of primary school students have difficulty at this level, which impairs the development of writing skills. It therefore seems judicious to intervene in kindergarten to support motor precision as well as visuomotor capacities, considered as prerequisites for writing by many researchers. The purpose of this study was to investigate the effect of motor training on visuomotor integration, motor precision and handwriting performance (speed and readability) in 5-year-old children. According to a quasi-experimental design (pretest, post-test with control group), 34 children participated in an intervention in subgroups, twice a week for 6 weeks. The mean and standard deviation were calculated for each of the tasks performed. Statistical tests (t test) were then carried out. The results show that the children in the experimental group improved their motor precision as well as their graphomotor skills compared to those in the control group. This project provides new insights into the benefits of working on basic skills in preparation for learning to write and will equip teachers on how to guide and support graphomotor skills before entering first grade.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.025
GPT teacher head0.370
Teacher spread0.345 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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