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Record W4367597572 · doi:10.3390/educsci13050462

Primary School Preservice Teachers’ Alternative Conceptions about Light Interaction with Matter (Reflection, Refraction, and Absorption) and Shadow Size Changes on Earth and Sun

2023· article· en· W4367597572 on OpenAlexaffabout
Abdeljalil Métioui

Bibliographic record

VenueEducation Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsShadow (psychology)Reflection (computer programming)Specular reflectionConceptual changeAbsorption (acoustics)Mathematics educationRefractionOpticsPsychologyPhysicsComputer science

Abstract

fetched live from OpenAlex

The present qualitative study investigates the conceptual representations of 132 preservice Quebec elementary teachers regarding matter–light interaction (reflection, refraction, and absorption) and the size of the shadow of an object on the Earth’s surface illuminated by sunlight. A paper-and-pencil questionnaire composed of six questions was constructed and managed. The data analyses demonstrate that most encounter several conceptual difficulties in explaining phenomena related to light, which are omnipresent in their immediate environment and with which they interact daily. The conceptual difficulties identified in analyzing the students’ explanations were as follows: (1) a black-colored body absorbs all light rays; (2) light travels rectilinearly and stops when it hits a white paper; (3) a mirror reflects light; it does not absorb it; (4) the glass surface of a mirror reflects light; (5) specular reflection and diffuse reflection are confused; and (6) the shadow varies during the day because the Sun moves around the Earth. These findings have implications for creating teaching strategies that confront preservice elementary teachers’ alternative conceptions and their corresponding scientifically accepted counterparts.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.164
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.045
GPT teacher head0.363
Teacher spread0.319 · 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 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

Citations6
Published2023
Admission routes2
Has abstractyes

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