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Record W4413903809 · doi:10.5539/jel.v15n1p66

Strategies for Developing Entrepreneurial Skills in Automobile Major Students of Higher Vocational Colleges in Fujian

2025· article· en· W4413903809 on OpenAlex
Xian Liao, Pacharawit Chansirisira, Suwat Julsuwan

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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Education and Learning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Work Dynamics
Canadian institutionsnot available
FundersMahasarakham University
KeywordsVocational educationMathematics educationPsychologyHigher educationPedagogyEconomic growth

Abstract

fetched live from OpenAlex

The objectives of this research were to: 1) investigate the components and indicators of entrepreneurial skills among students majoring in automobiles. 2) explore the current situation, expectation state of entrepreneurial skills among automotive students, and 3) develop and evaluate training strategies for entrepreneurial skills among automotive students in higher vocational colleges in Fujian. The research consisted of three phases: 1) conducting a theoretical study that involved reviewing relevant literature, documents, and interviewing five experts, 2) exploring the current situation, expectation state, and priority need with a sample of 330 automotive teachers by multi-stage random sampling. Data was collected through questionnaires. The discrimination index ranges from 0.349 to 0.864, and the reliability measures at 0.969. Expert interviews were conducted and analyzed using mean value, standard deviation, and the modified Priority Need Index. 3) Develop and evaluate training strategies by inviting 10 experts as key information providers and using draft strategies and evaluation tables as instruments. the data were analyzed through summarization, mean, and standard deviation. The findings of the study revealed the following: 1. There were 4 components, and 21 indicators included: Teaching level (5 indicators), Curriculum (6 indicators), Entrepreneurial skills (5 indicators), and Entrepreneurship policy (6 indicators). The appropriateness of all these possibilities which were very appropriate. 2. The current situation regarding entrepreneurial skills showed that they were generally at a medium level, and their expectation was generally at a high level. The priority needs from high to low were: Entrepreneurial skills, Curriculum, Entrepreneurial policy, and Teaching level. 3. The results of formulating entrepreneurial skills strategies for automotive students in vocational colleges revealed that the correction and applicability of the verification results included 1 vision, 5 goals, 4 large strategies, and 20 specific measures. The results of the evaluation were at a very high level of appropriateness, accuracy, and feasibility.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.390
Teacher spread0.380 · 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