MétaCan
Menu
Back to cohort
Record W3040283398 · doi:10.17759/psyedu.2020120201

How Results are Created: Methodological Approaches to the Design of Educational Outcomes

2020· article· en· W3040283398 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePsychological-Educational Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsTerminologyCurriculumCompetence (human resources)Subject (documents)Outcome-based educationOutcome (game theory)National curriculumMathematics educationManagement scienceComputer scienceMedical educationPedagogyEngineering ethicsPsychologyEngineeringMedicineLibrary science

Abstract

fetched live from OpenAlex

The authors make retrospective analyze of "outcome-based education" and “competence-based education” concepts evolution. National educational standards and curricula all around the world have gone through dramatic transformation over the last 20 years. New education models require new methodology for designing educational outcomes. In the paper, based on the analysis of international experience, a framework for designing outcomes is proposed. Authors analyze Canada, UK, Finland, Australia, USA experience. Also terminology of meta-subject and subject outcomes are discusses in the paper. The framework presented by the authors is applicable both for school and teacher curricula, and at the national level, when formulating standards or example currucula.

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)0.003
metaresearch head score (Gemma)0.058
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.857
GPT teacher head0.555
Teacher spread0.302 · 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