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Record W2381833852

Analysis and Reflection of the Higher Vocational Education Courses in Canada

2010· article· en· W2381833852 on OpenAlexaboutno aff
Tao Yi-yi

Bibliographic record

VenueJournal of Suzhou College of Education · 2010
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumVocational educationCompetence (human resources)Reflection (computer programming)Mathematics educationProcess (computing)Curriculum theoryCurriculum mappingEngineering ethicsTask (project management)Higher educationEngineering managementCurriculum developmentPedagogyEngineeringComputer scienceSociologyPsychologyPolitical scienceSystems engineering
DOInot available

Abstract

fetched live from OpenAlex

Higher vocational education in Canada features the reduction of theory,emphasis of practice and the focus on ability.Its curriculum setup meets the professional demands,course development is based on job requirements,course design focuses on practical ability,and teaching programs center around the application competence.Based on the learnings from their experience,this paper proposes that the working process of professional activities should be used to determine the curriculum system,task objectives or actual solutions to a problem should be applied to design the curriculum,the implementation of the project-oriented methods should be used as the teaching carrier,and curriculum practice should possess the characteristics of being true,higher,open and through.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.523

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.316
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2010
Admission routes1
Has abstractyes

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