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Record W2058994107 · doi:10.1080/146363102753535240

Knowledge Forum: altering the relationship between students and scientific knowledge

2002· article· en· W2058994107 on OpenAlexfundno aff
Beverly Caswell, Katerine Bielaczyc

Bibliographic record

VenueEducation Communication and Information · 2002
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsCurriculumScience learningSociology of scientific knowledgeMathematics educationPedagogyKnowledge managementScience educationComputer sciencePsychologySociologySocial science

Abstract

fetched live from OpenAlex

This paper explores the use of Knowledge Forum, a networked computer program designed to support knowledge building communication and to foster thinking and learning skills. The paper focuses on a Grade 5/6 classroom and looks at how students view scientific knowledge and what it means to learn science. A shift in pedagogy, along with the learning opportunities afforded by the communal database, impacted the learning environment and created changes in the structure of the learning activities, the ‘rules of the game’ of science and the sequencing of the curriculum. Specifically, the paper examines the knowledge transforming discourse that occurred both on and off the database as children worked to understand the evolution of the Komodo Dragon during an investigation of islands and island biogeography.

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)0.007
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.174
GPT teacher head0.460
Teacher spread0.286 · 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 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

Citations49
Published2002
Admission routes1
Has abstractyes

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