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Record W2169096544 · doi:10.1108/14676370310485401

SEEDing sustainability

2003· article· en· W2169096544 on OpenAlexafffund
Anthony Brunetti, Royann J. Petrell, Brenda Sawada

Bibliographic record

VenueInternational Journal of Sustainability in Higher Education · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsSustainabilityProcess (computing)Subject matterEnvironmental educationProject-based learningTeaching methodSubject (documents)Engineering ethicsEngineeringSociologyEngineering managementPedagogyComputer scienceEcologyCurriculum

Abstract

fetched live from OpenAlex

The University of British Columbia's campus sustainability office, through the “Social, ecological, and economic development studies” (SEEDS) program, gave a team of students in a bio‐environmental engineering design course an environmental problem to resolve for their term project. The students did not resolve the problem, but the project‐based learning approach was effective in teaching them about social, economic and environmental sustainability issues. It also provided the campus with a new sense of direction concerning the solution to the particular problem. The teaching process required that the instructors change their teaching approaches as well as subject matter. Changes in individual engineering‐related skill levels were difficult to assess and, due to this, corrective actions were undertaken to address team project‐based assessment in the future. The teaching approach can be adapted to other educational settings. This paper will describe the overall learning and teaching process.

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)0.006
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.028
GPT teacher head0.398
Teacher spread0.370 · 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.

Study designTheoretical or conceptual
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

Citations40
Published2003
Admission routes2
Has abstractyes

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