A Qualitative Research Study on the Importance of Life Skills on Undergraduate Students’ Personal and Social Competencies
Bibliographic record
Abstract
Recently, it is more demanding to enter job market since current employers hire staff with some life skills such as leadership, communication skills, time management, problem solving skills, and teamwork. The current study aimed to identify the relationship between life skills program, student's personal efficacy and competencies. Moreover, this study investigated eight students’ perceptions of their personal efficacy after understanding life skills program. This study employs a qualitative research approach using an in-depth interview and self-reporting of the life skills module. The participants were randomly selected among freshman undergraduate students who have passed the life skill modules at Taylor’s University, Malaysia. This study aimed to identify students’ perceptions, competencies after completing life skills modules. It also elaborates on how life skills considered as a technical requirement for hard skills and employees’ future. The results of thematic analysis indicated that embedding the life-skills program in the university curriculum plays a key role in shaping students' personal and social competencies. This finding has important implications for educators and educational policy makers to integrate students’ life skills into curriculum so as to influence students’ professional and interpersonal skills such as team working, communication, leadership, time management, decision making and problem-solving.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".