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Record W1818970564 · doi:10.1002/sce.21135

Inquiry, Engagement, and Literacy in Science: A Retrospective, Cross‐National Analysis Using PISA 2006

2014· article· en· W1818970564 on OpenAlex
A. McConney, Mary Oliver, Amanda Woods‐McConney, Renato Schibeci, Dorit Maor

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScience Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsScience educationScience learningScientific literacyMathematics educationLiteracyPsychologyAffect (linguistics)Pedagogy

Abstract

fetched live from OpenAlex

ABSTRACT In this study, we examine patterns of students’ literacy and engagement in science associated with different levels of “inquiry‐oriented” learning reported by students in Australia, Canada, and New Zealand. To achieve this, we analyzed data from the Organisation for Economic Co‐operation and Development's 2006 Programme for International Student Assessment, which had science as its focus. Consistently, our findings show that science students who report experiencing low levels of inquiry‐oriented learning activities are found to have above‐average levels of science literacy, but below‐average levels of interest in science, and below‐average levels on six variables that reflect students’ engagement in science. Our findings show that the corollary is also true. Across the three countries, students who report high levels of inquiry‐oriented learning activities in science are observed to have below‐average levels of science literacy, but above‐average levels of interest in learning science, and above‐average engagement in science. These findings appear to run counter to science education orthodoxy that the more students experience inquiry‑oriented teaching and learning, the more likely they are to have stronger science literacy, as well as more positive affect toward science. We discuss the implications of these findings for science educators and researchers.

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)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.012
Science and technology studies0.0030.005
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.091
GPT teacher head0.499
Teacher spread0.408 · 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