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Record W3045788755 · doi:10.14738/assrj.76.7882

Epistemic Beliefs Moderate Mediations Among Attitudes, Prior Misconceptions, and Conceptual Change

2020· article· en· W3045788755 on OpenAlexaff
James Vivian, Krista R. Muis

Bibliographic record

VenueAdvances in Social Sciences Research Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsModerationMediationPsychologyConceptual changeTest (biology)Reading (process)Variance (accounting)Social psychologyMathematics educationSociologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

We investigated the mediating and moderating roles of attitudes and epistemic beliefs in conceptual change during learning about genetically modified foods (GMFs). One hundred twenty undergraduate students participated. To measure misconceptions about GMFs, students first completed a prior knowledge test. Students then completed self-report inventories to measure their attitudes and topic-specific epistemic beliefs regarding GMFs. Students were then randomly assigned to read a refutation or expository text about GMFs. Following reading, students completed a test to assess conceptual change. Results of a repeated measures ANOVA revealed participants who read a refutation text changed more misconceptions at post-test than participants who read an expository text. A moderation mediation analysis revealed attitudes toward GMFs significantly mediated the relationship between prior misconceptions and conceptual change, and that this relationship was moderated by learners’ beliefs regarding the source and justification of GMFs knowledge. Theoretical and educational implications are discussed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.186
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.340
GPT teacher head0.524
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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