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Record W2228012699 · doi:10.1007/s40751-015-0010-4

Enactivism, Spatial Reasoning and Coding

2015· article· en· W2228012699 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDigital Experiences in Mathematics Education · 2015
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsBrock UniversityUniversity of Calgary
Fundersnot available
KeywordsEnactivismSpatial intelligenceCoding (social sciences)Perspective (graphical)Computer scienceCognitive scienceCurriculumTypologyHuman–computer interactionArtificial intelligencePsychologyAutopoiesisSociologyPedagogy

Abstract

fetched live from OpenAlex

Drawing on an enactivist perspective in order to gain insight into how spatial reasoning develops and can be fostered, this article describes a study of how children engaged in spatial reasoning as they learned to program LEGO Mindstorms EV3 robots. Digital technologies afforded multiple opportunities for accumulating experiences for developing spatial reasoning that are difficult to come by in other contexts. Our video-recorded observations of children (aged 9 to 10) suggest that Bruner’s enactive–iconic–symbolic typology of representations develop simultaneously rather than sequentially – the commonly held assumption. Furthermore, these same video observations provided insight into children’s development of spatial reasoning through computer programming. Our findings have implications for how curriculum is designed and implemented in classrooms.

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.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.295

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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