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Record W141394521

CHILDREN'S CONCEPTIONS OF ELECTRIC CIRCUITS: THE ROLE OF CAUSALITY

2012· article· en· W141394521 on OpenAlexaffabout
Abdeljalil Métioui

Bibliographic record

VenueEDULEARN12 Proceedings · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsElectronic circuitCausality (physics)Simple (philosophy)Computer sciencePsychologyElectrical engineeringEngineeringPhysicsEpistemology
DOInot available

Abstract

fetched live from OpenAlex

Research on the misconceptions that children hold about simple electric circuits indicates a difficulty to conceive an electric circuit as a system where elements are acting concurrently rather than sequentially. In this paper we present the results of a study conducted, on the nature of causal factors involved in children's explanatory models about electric circuits. 104 elementary children from Nova Scotia in Canada were asked to solve simple problems and provide an explanation of their reasoning. The findings reveal that these children used causal rules with various levels of complexity: a simple linear model where a battery causes a bulb to light up, a complex linear model where two wires departing from a battery, meet in the bulb to create light and a cyclic model where the current moves around the circuit to keep the bulb lit up. Understanding the underlying causal assumptions of children's models for electric circuits may help teachers design activities to reduce children's difficulty in conceiving the systemic nature of electric circuits.

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)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.010
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.340
Teacher spread0.311 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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