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Record W2012972831 · doi:10.1080/13504622.2011.640750

Assessing students’ learning about fundamental concepts of climate change under two different conditions

2012· article· en· W2012972831 on OpenAlexaff
Dianna Porter, Andrew J. Weaver, Helen Raptis

Bibliographic record

VenueEnvironmental Education Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsClimate changePsychologyGlobal warmingMathematics educationScience educationKnowledge levelProfessional developmentIntervention (counseling)PedagogyMedical educationEcologyMedicine

Abstract

fetched live from OpenAlex

Students from three different British Columbia grade six classes were followed through two weeks of instruction on climate change. Pre, post, and follow-up surveys were used to determine the differences in knowledge gained and retained by students that received direct instruction from their science teacher, and by those who received equivalent content instruction from outside presenters. The teacher participant also completed a survey on her experience with the researcher-designed lesson plans. Students’ results on the surveys were compared to results from a control group with no intervention. The teacher-based setting resulted in significantly higher knowledge gain, although no difference was found between the groups’ rate of knowledge decline thereafter. Highest gains in knowledge were for the carbon cycle and the human impacts topic, followed by understanding the difference between climate and weather. The students and teacher alike appeared to struggle with the topic of global warming and the greenhouse effect. The research suggests that with the appropriate background information the classroom teacher is likely to be more effective at conveying the science of climate change, particularly when it is taught through an understanding of the carbon cycle and its human impacts. It also suggests that those non-governmental organizations engaged in climate change education might be better served by investing their limited resources in the development of learning materials and subsequent professional development for teachers rather than focusing on in-school presentations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.001

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 head0.072
GPT teacher head0.475
Teacher spread0.402 · 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

Citations61
Published2012
Admission routes1
Has abstractyes

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