The Employability Skills of Engineering Students': Assessment at the University
Bibliographic record
Abstract
Employability can be an alternative solution to increase individual chances of getting a job. The study aims to identify indicators that can measure students' employability skills and attributes. The research model, based on The Conference Board of Canada (Employability Skills 2000+), is divided into fundamental skills, personal management skills, and cooperative skills. The method used Confirmatory Factor Analysis (CFA) with primary data obtained from surveys of students through a questionnaire will be analyzed using the AMOS program. These samples included 528 respondents who had done the work practices of the industry. The research respondents were students of the Faculty of Engineering, Universitas Negeri Makassar, divided into several majors. The results of the study identified that the low value of communication indicators in the variable of fundamental skills compared to other indicators was due to the lack of foreign language communication activities in the learning process. Communication is a vital aspect possessed by students, especially in global level competition. The study results were used to measure educational institutions to develop and improve low work skills indicators so that new graduates will better be prepared for work.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".