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Record W2118588352

Kyoto Redoux: Assessment of an Environmental Science Collaborative Learning Project for Undergraduate, Non-Science Majors.

2000· article· en· W2118588352 on OpenAlexvenueno aff
Anastasia P. Samaras, Barbara J. Howard, Carolee M. Wende

Bibliographic record

VenueCanadian journal of environmental education · 2000
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsScience educationContext (archaeology)Environmental educationPedagogyMathematics educationPsychologyPolitical scienceSociologyGeography
DOInot available

Abstract

fetched live from OpenAlex

How can we present science in a format that will allow collegelevel undergraduates not majoring in the sciences, including elementary education preservice teachers, to grasp an understanding of, and to gain, an appreciation for science in terms of everyday life and in the context that science is important in their own fields of interest? It is with these assumptions that “Kyoto Redoux,” the major project for the course “Global Change,” was chosen to be a simulation of the Conference of the Parties-3 (COP-3), sponsored by the United Nations Framework Convention on Climate Change (UNFCCC) in Kyoto, Japan. The purpose of this study was to examine students’ perceptions of this collaborative course project as a component of a process evaluation of “Adventures in Science,” a pilot program of a newly designed, interdisciplinary environmental science program for undergraduate, non-science majors. Non-traditional evaluation tools, including portfolios, focus groups, and team and selfassessments were employed. The research led us to a better understanding of practical, pedagogical applications in applying science content to non-science majors’ career goals, promoting problem-solving skills in collaborative contexts, and structuring and assessing students’ environmental course experiences. Resume Comment presenter les sciences de facon a permettre a des etudiants universitaires de premier cycle non specialises en sciences, y compris des stagiaires en enseignement elementaire, de comprendre et d’apprecier la science quant a son applicabilite dans la vie de tous les jours et a son importance pour leur propre domaine d’interet? En se basant sur ce

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.839
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.375
Teacher spread0.360 · 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

Citations4
Published2000
Admission routes1
Has abstractyes

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