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Record W2800355571 · doi:10.1187/cbe.17-02-0037

EcoEvo-MAPS: An Ecology and Evolution Assessment for Introductory through Advanced Undergraduates

2018· article· en· W2800355571 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCBE—Life Sciences Education · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsUniversity of Calgary
FundersMcGill UniversityNational Science Foundation
KeywordsBachelorCurriculumEcologyProcess (computing)Mathematics educationPerspective (graphical)PsychologyComputer sciencePedagogyBiologyGeographyArtificial intelligence

Abstract

fetched live from OpenAlex

A new assessment tool, Ecology and Evolution-Measuring Achievement and Progression in Science or EcoEvo-MAPS, measures student thinking in ecology and evolution during an undergraduate course of study. EcoEvo-MAPS targets foundational concepts in ecology and evolution and uses a novel approach that asks students to evaluate a series of predictions, conclusions, or interpretations as likely or unlikely to be true given a specific scenario. We collected evidence of validity and reliability for EcoEvo-MAPS through an iterative process of faculty review, student interviews, and analyses of assessment data from more than 3000 students at 34 associate's-, bachelor's-, master's-, and doctoral-granting institutions. The 63 likely/unlikely statements range in difficulty and target student understanding of key concepts aligned with the Vision and Change report. This assessment provides departments with a tool to measure student thinking at different time points in the curriculum and provides data that can be used to inform curricular and instructional modifications.

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.

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 categoriesnone
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 score0.635
Threshold uncertainty score0.528

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 science0.0000.000
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 head0.052
GPT teacher head0.427
Teacher spread0.375 · 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