Accounting Skills in Practice and Their Impact on Employability: A Curriculum Review in an Autonomous Philippine University
Bibliographic record
Abstract
As competition for graduate jobs increases, students need to consider new ways to differentiate from equally qualified and skilled candidates. The investigation determined the significance of a curriculum in the working environment and graduates' employability. The examination contrived a sum of 169 respondents on a snowball testing strategy. Frequency and simple percentage, weighted mean, Chi-Square Test of Independence, and One way ANOVA was utilized to treat the data. The findings revealed that communication skills, basic accounting skills, & financial reporting skills are among the essential skills to acquire to serve a spot on the labor market. The investigation further revealed a significant association on civil status, length of time to get a job after graduation, Nature of work on the first and current job, work status, graduate studies, and the degree of enhancement the graduates suggested to meet the demands of the profession. It also revealed a statistically significant distinction following the respondents' profile when grouped by its influence on the proposed program enhancement suggested by the graduates. The study concluded that maximizing graduates' employability, the viability of curriculum enhancement and teaching methodologies, and necessary facilities must be concentrated to depict the utmost realization of objectives and goals of the program. It further concludes that a strong partnership with an internship program can increase alignment between educators, students, and industries.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".