Communication Skills and its Impact on the Marketability of UKM Graduates
Bibliographic record
Abstract
Organizations have always placed emphasis on the public’s voices as an effort to continue enhancing their service towards society. University’s performance and its relevance in a nation is highly dependent on the marketability of its students. The ability to widely distribute their students and to heighten their mobility in society and in the work field importantly reflects the overall performance of the University. The Universiti Kebangsaan Malaysia placed eight compulsory soft skills courses every student has to pass before they can graduate. This was done to ensure that all of Universiti Kebangsaan Malaysia’s students are exposed with all dimensions of soft skills throughout their studies as they play a crucial role in enhancing students’ marketability. Perceptions from 35 final year students, 2 lecturers, 3 Private Sector representative and 20 first year students towards the beneficial roles of these skills were conducted via interview. It’s agreeable that communication skills are the most favorable to determine the marketability of UKM students. Low command of both Bahasa Melayu and English are one of the contributing factors to this. UKM graduates are seen to be less sensitive towards recent issues around the world thus they’re not confident to participate in a group discussion. This article will reveal problems and strategic ways to encounter challenges, by enriching UKM students with different learning experiences of good communication skills and its impact towards their marketability after they graduate.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".