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Record W4316669070 · doi:10.1002/ece3.9747

Teach different: The <scp>CREATE</scp> pedagogy for ecology and evolution

2023· article· en· W4316669070 on OpenAlexafffund
Christopher J. Lortie

Bibliographic record

VenueEcology and Evolution · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReading (process)EcologyComputer scienceSociologyPedagogyMathematics educationPsychologyPolitical science

Abstract

fetched live from OpenAlex

Globally, teaching has changed and innovated profoundly in the last 3 years. With novel and more seamless opportunities to use technology and more actively teach visually online or in-person and to engage in inclusive dialogue within and between groups, we can teach very differently now. An innovation proposed a number of years ago and revisited anew in a recent and novel application to ecology and evolution course offerings, and the CREATE pedagogy or Consider, Read, Elucidate the hypothesis or purpose, Analyze and interpret data or evidence, and Think of the next Experiment is an inspiring framework for unique student work and teaching. CREATE proposes that students engage in active reading through specific exercises that are both creative and heavily anchored in critical thinking when working with publications. Here, the palette of CREATE exercises is expanded further for ecology and evolution and affirms that this approach to student engagement with literature can be highly effective in many courses. Furthermore, the application of this pedagogy dramatically influences and likely enhances how one teaches in a lecture setting as an educator making the content in all modalities more engaging and active.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
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 head0.041
GPT teacher head0.361
Teacher spread0.320 · 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 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
Published2023
Admission routes2
Has abstractyes

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