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Record W4399918262 · doi:10.1080/00220671.2024.2362164

Reported and observed engagement in handwriting and keyboarding activities in elementary school: Are students as engaged as they say they are?

2024· article· en· W4399918262 on OpenAlexaff
Joane Deneault, Natalie Lavoie

Bibliographic record

VenueThe Journal of Educational Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsHandwritingPsychologyChecklistLikert scaleObservational studyStudent engagementScale (ratio)Mathematics educationDevelopmental psychologyCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

Little is known about students’ engagement in school writing tasks and the methods that should be used by the researchers to assess this engagement. This exploratory study examines the relationship between the engagement reported by elementary school students (N = 136) in a handwriting and keyboarding activity (Likert scale questionnaire) and their actual behaviors in such situations. An observational checklist was created to capture engagement behaviors in these writing contexts. Correlational analyses showed that, overall, self-reported engagement scores were positively correlated with the frequency of the behaviors observed in both contexts. The discussion focuses on the relevance of observational checklists and questionnaires for capturing students’ engagement in writing tasks, and opens to the conceptual links between engagement and motivation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.210
GPT teacher head0.487
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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