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Record W1579737315 · doi:10.55016/ojs/ajer.v56i2.55398

Learning About Plate Tectonics Through Argument-Writing

2010· article· en· W1579737315 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueAlberta Journal of Educational Research · 2010
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsWestern University
Fundersnot available
KeywordsArgument (complex analysis)Plate tectonicsEpistemologyPsychologyMathematics educationPhilosophyTectonicsGeologyPaleontology

Abstract

fetched live from OpenAlex

In a quasi-experimental study (N=60), grade 7/8 teachers students were taught to write arguments in content-area subjects. After instruction, students drew on document portfolios to write on a new topic: “Do the continents drift?” In a MANCOVA, students who participated in argument instruction scored significantly higher than a control class on the combination of dependent variables. A stepwise discriminant analysis indicated that instruction most strongly affected argument genre knowledge, which in turn accounted for variance in the other dependent variables. The features of argument texts that were most strongly associated with science learning were: the number of argument moves, the number of science propositions taken up from source documents, text length, and text coherence. These results support a constructivist model of writing to learn in which students use genre knowledge to select information from source documents and construct genre-specific relationships among ideas.

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)0.008
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0340.001

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 head0.111
GPT teacher head0.507
Teacher spread0.396 · 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