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Record W1759138832 · doi:10.5539/jedp.v5n2p51

How Flexible Is the Visuospatial Reference System in Children Aged 4 to 12?

2015· article· en· W1759138832 on OpenAlexvenueno aff
Julie Heiz, Koviljka Barisnikov

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2015
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyObject (grammar)Task (project management)Cognitive psychologyFrame of referenceReference frameFrame (networking)Developmental psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The ability to correctly process spatial information largely depends on the capacity to either use a viewpoint according to a visual scene or a Frame Of Reference (FOR) and to flexibly shift between them. Literature indicates 2 types of FOR mainly used to represent the location of an object. The egocentric FOR uses the location of an object relative to oneself and develops earlier than the allocentric FOR, which uses the location of an object relative to other external objects. This study examined the spontaneous use of different FOR as well as their use following explicit task instructions. One hundred and thirty-five children (aged 4-12) were assessed with an adapted version of Taylor and Rapp’s (2004) spatial reference task. In the spontaneous instructions condition, most of the children aged 7 and above used an allocentric FOR. While in the allocentric instructions condition, children aged 4, 5 and 6 gave significantly more allocentric responses. In the egocentric instructions condition, all participants showed more egocentric responses, independently of their age group. The present study is the first to demonstrate that simple instructions enable children to use allocentric and egocentric FOR earlier, more effectively and more flexibly than do their spontaneous use. These findings also demonstrate that specific instructions could help children use a viewpoint in accordance to a situation. This could help improve academic performances and overcome the difficulties of some young children in developing the use of an allocentric FOR.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.303
Teacher spread0.262 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of Educational and Developmental PsychologySame topicSpatial Cognition and NavigationFrench-language works237,207