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Record W1982744178 · doi:10.3115/1599600.1599641

Making thinking visible

2007· article· en· W1982744178 on OpenAlexaff
Yongcheng Gan, Marlene Scardamalia, Huang‐Yao Hong, Jianwei Zhang

Bibliographic record

VenueComputer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference · 2007
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGraphicsComputer scienceCoding (social sciences)LiteracyMultimediaMathematics educationComputational thinkingGraphical user interfaceScheme (mathematics)PedagogyComputer graphics (images)PsychologyArtificial intelligenceProgramming languageSociologySocial science

Abstract

fetched live from OpenAlex

This study provides a new coding scheme to analyze growth in seven components of graphical literacy for 22 students who used an online multimedia environment--Knowledge Forum®--across two years (grades 3 and 4) to advance their theories in science and history. Students received no instruction in graphical literacy and were free to express their ideas in text or graphics. Results show increases in all components of graphical literacy over this time span.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.041
GPT teacher head0.363
Teacher spread0.322 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations201
Published2007
Admission routes1
Has abstractyes

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