Perception towards Development of Employability Skills by Students: A Module Analysis
Bibliographic record
Abstract
For some time, engineering education literature has suggested that the employability capability of engineering graduates does not meet the expectations of many local modern industries.The need to enhance their employability skills is critical because employability has been a challenging national concern and agenda.Thus, gauging student's satisfactory level is a central concern especially in ensuring engineering graduates are able to bridge between their acquired skills and the elementary demands of the labour market.The study entails a review of established research to understand the views and perceptions of engineering undergraduate students in harnessing their employability skills through Barrie's teaching content approach in the Engineering Product Development module.The study described in this paper used 55 responses from engineering students to a standardized student feedback questionnaire over 3 years, to gauge their overall satisfaction with the module as well as to explore perception associated with students' learning experiences, including a two-fold study on collaborative learning experience and satisfactory development of ten important attributes that are closely aligned towards adapting to work environment.The findings indicate that 67.3% of the students are satisfied with the module in terms of nurturing them with crucial employability skills desirable for the workforce.Besides, the result provides a significant impact of adoption of teaching content mode in the effort of enhancing the teaching and learning process towards producing graduates with broader employability skills.
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 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".