The Development of Production-Based Learning Approach to Entrepreneurial Spirit for Engineering Students
Bibliographic record
Abstract
Vocational education aims to produce workforce. However, in reality there is a shift that the vocational graduates are not only prepared to work but also they are expected to open or create new work opportunity. To overcome the mentioned educated employment, we offer an alternative solution to integrate production based with the learning process; the outcome would be the entrepreneurial ability of the engineering students. The results of this study showed that the implementation of production based learning with entrepreneurship approach using workshop based lectures, qualitatively improved the quality and meaningfulness of the learning. The learning experience which connects the interns and the works or work products is indeed in line with the field specification and standard. The learning process has given impact to the entrepreneurial interest improvement assessed in the beginning and at the end of the semester. Besides that, the learning activity gives impacts to the cognitive discourse, psychomotor skill, and work attitude improvement build integrally. Thus, the model is deemed suitable to be utilized in the learning to improve the students’ entrepreneurial interest.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".