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Record W2964485055 · doi:10.22034/ijsc.2019.86922

A comparative study of technical and vocational curriculum with an emphasis on Entrepreneurship education in the countries of Canada and India with Iran

2019· article· en· W2964485055 on OpenAlexaboutno aff
Maryam Baniameryan, Mohammad Javadipour, Rezvan Hakimzadeh, Kamall Dorani, Ebrahim Khodaie, Mohhamad Hasan Mobaraki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationCurriculumPromotion (chess)EntrepreneurshipVariety (cybernetics)Political scienceMathematics educationSociologyPedagogyPsychologyComputer science

Abstract

fetched live from OpenAlex

Objectives: In today's world, entrepreneurship education has become one of the most important and extensive activities in the Technical & Vocational education system, especially at higher education level. This research has been conducted in the field of vocational education with the entrepreneurial approach and is a comparative study. The purpose of this study is to compare the curriculum of technical and vocational training (official and academic) of the two most prosperous countries in the field of entrepreneurship education with Iran (our country) Method: This applied-descriptive research has been carried out applying comparative study method of George Brody, and the main elements of the curriculum including purposes, content, teaching-learning activities and evaluation methods in technical and vocational education have been observed approaching the promotion of Entrepreneurship education. Results: The results of this study show that there is a high similarity between the chosen country with Iran in discussing the goals and content of the curriculum, but there is a great deal of difference in the discussion of teaching-learning activities and evaluation between selected countries and Iran. Iran continues to use traditional methods in teaching and teaching-learning activities, but the approach of the chosen countries is a new one based on goals and content as well as group methods. Moreover, in the evaluation methods, the selected countries use a variety and novel methods, but in Iran, oral and written tests are still employed traditionally. Conclusions: based on the study, it seems that Iran needs to review and change the approach to new and emerging approaches in the execution stage of the curriculum.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.334
Teacher spread0.314 · 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 designQualitative
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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