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Record W3110870520

A Comparative Study of Technical and Vocational Curriculum with an Emphasis on Entrepreneurial Intention in Canada, Germany, India and Iran

2017· article· en· W3110870520 on OpenAlexaboutno aff
Maryam Baniameryan, Mohhamad Javadipur, Rezvan Hakimzadeh, Kamal Dorani, Ebrahim Khodaee, Mohhamad Hasan Mobaraki

Bibliographic record

VenueJournal of Curriculum Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumVocational educationTeamworkEntrepreneurshipWork (physics)Developing countryPsychologyMedical educationSociologyPedagogyPolitical scienceEngineeringEconomic growthMedicine
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this research to compare vocational curriculum in three successful countries in education of vocational skills and entrepreneurship in comparison with Iran. In this study, the practical descriptive research was performed within comparative-study method of George Brody. The purposes, contents, and methods of teaching and assessment were investigated by though the approach of developing the learners’ motivations for entrepreneurship. The results of this study showed that curriculum purposes and contents in Iran and the three chosen countries are similar and they move toward cultivating motivations and skills for entrepreneurship. In Canada and Germany, education of international work force is one of the purposes of the curriculum. The surveyed content of the curriculum of Iran and the three chosen countries are similar and they focus on technology and information, science of communication, acquiring international languages with environment as the complementary contents in three countries’ curriculum. Courses such as management of business and knowledge of entrepreneurship between are common the three countries and Iran, but a big gap was detected between acquisition-education activities and evaluation in the three chosen countries and Iran. In Iran, the traditional methods are used, while in the three chosen countries the main method is based on teamwork. Regarding assessment, various methods is employed the three chosen countries use (such as assessment teams, self-evaluation and evaluation of learners’ research-based projects), whereas, in Iran the written and verbal tests are widely implemented

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 score0.853

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 head0.055
GPT teacher head0.393
Teacher spread0.338 · 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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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