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Record W2202781397 · doi:10.5617/nordina.538

Global Climate Exchange: Peer collaboration in a “Global classroom”

2014· article· en· W2202781397 on OpenAlexafffundabout
Majken Korsager, James D. Slotta, Doris Jorde

Bibliographic record

VenueNordic Studies in Science Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsUniversity of Toronto
FundersUniversitetet i OsloUniversity of TorontoNanjing Normal University
KeywordsChinaConstructivePsychologyInformation exchangeGlobal warmingCurriculumPolitical scienceGlobal climateConceptual frameworkPublic relationsPedagogyClimate changeSociologyComputer scienceEcologySocial science

Abstract

fetched live from OpenAlex

This paper reports on student peer collaboration in an online environment in an international shared curriculum, the Global Climate Exchange. Four cohorts of students (age 16 -19) from Canada, China, Norway and Sweden (n=157) were engaged in four wiki-based activities where they collaborated with peers locally and internationally. Previously, impact from Global Climate Exchange on students’ conceptual understanding was analysed, indicating a positive impact which might be explained by the amount of interactions with peers and international peer collaboration. This paper looks further into the details of the students’ peer interactions in terms of how they communicate in the online Global Climate Exchange learning environment. The study revealed that communication between international peers might be more constructive than when communication is limited to national peers. This might be a possible explanation for our previously findings indicating that international peer collaboration may well be an approach to enhance students’ conceptual understanding of climate change.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.008
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.035
GPT teacher head0.452
Teacher spread0.417 · 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 teacher head, 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

Citations11
Published2014
Admission routes3
Has abstractyes

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