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Record W1584060135

Cohort Based Learning: Application to Learning Organizations and Student Academic Success.

2004· article· en· W1584060135 on OpenAlexaboutno aff
Kristine Fenning

Bibliographic record

VenueThe College Quarterly · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCooperative learningExperiential learningSocial learningActive learning (machine learning)CohortHigher educationCollaborative learningLearning sciencesOpen learningPedagogyMathematics educationAdult educationProfessional learning communityTeaching methodComputer scienceArtificial intelligencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Learning is a natural process shared by its members in most social and educational institutions, and is seen as both the primary vehicle and foundation for the building and achievement of one’s career and /or personal goals. This research offers critical insight into the dimensions of cohort based learning communities and the implications it presents for adult learners and learning organizations in Canada. Supported by constructivist and socio-cultural adult learning theories, cohort based learning is a valued learning option encapsulating a pedagogical approach for its adult participants. Research infers this learning venue has both merits and limitations in higher education, and concludes with the recommendation for further research concerning the advantages and disadvantages posed by such a curricular approach.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0030.003
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.010
GPT teacher head0.343
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2004
Admission routes1
Has abstractyes

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