Entrepreneurship Education and Venture Intention of Female Engineering Students in A Nigerian University
Bibliographic record
Abstract
The significant changes taking place in the world have offered new opportunities for male and female-owned businesses. This study investigated the impact of entrepreneurship education and venture intention of female engineering students in Nigeria. A descriptive research design was used. Copies of the questionnaire were distributed to collect quantitative data on the link between entrepreneurship education and venture intentions of Landmark university female engineering students. The sample size for this study was determined based on the entire population of 32. This study used purposive random sampling techniques for the selection of the respondent. Hence, each participant was given an equal chance of being chosen from the population in no particular order. Regression analysis was used to analyse the stated hypotheses through a statistical package for social science (SPSS). The findings revealed that effective implementation of entrepreneurship education elements stimulate students’ entrepreneurial activities, particularly among female engineering students. This study advanced knowledge and concluded that entrepreneurship education elements such as pedagogy, educators’ competence, and learning environment have a significant impact on venture intention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".