The Perception of Students towards the Community Colleges’ Courses That Offered in Malaysia
Bibliographic record
Abstract
Government has allocated funds to build and upgrade the present infrastructures to deal with the increasing capacity of students at community colleges. Among its reasons were the needs to strengthen the training and skills enhancement system and to encourage participation from SPM leavers. However, in fact not many of them interested to enroll and fill up the available quota. Therefore, this study was conducted to get views on SPM leaver’s perception towards community colleges and the courses offered. The quantitative survey designed which used questionnaires as an instrument. Samples of 105 respondents who were attending the National Service Training Program (NSTP) at Semberong Camp were chosen to represent the whole population of SPM leavers for the year of 2007. Findings showed that the perceptions of SPM leavers towards community colleges were at a moderate level, such as their acceptance towards the courses offered. At the same time, they were alert and informative pertaining to community colleges and the courses being offered. Others aspects have also taken into account such as participations, triggers, interest in courses and demographic factors. In summary, SPM leavers’ perception and acceptance towards community colleges and the courses offered were at a moderate level and it illustrated tendencies towards positive perception.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".