Perceived Social Support and Well Being: First-Year Student Experience in University
Bibliographic record
Abstract
The current study explored first-year student experience in receiving social support and its relation to their ability to adapt with university ethos. It also explored how social support on academic adjustment, social adjustment and emotional adjustment among students were significantly associated with student well-being. This qualitative research utilized individual semi-structured interview protocols to gather narrative data from 16 university students. All students were interviewed twice in order to see changes and developments in receiving social support from university community, peers and family members. Data were tape-recorded, transcribed and analyzed by using thematic approach. It was then coded by independent coders. It has been found in this study that academic adjustments, social adjustment and emotional among new students are dependent on their abilities in receiving socio-educational support from friends (supportive friendship) and families. Results also revealed the powerful influence of parents and the importance of socio-relationship for student wellbeing. This study suggests that the concept of social support should go further than simply identifying it within the context of a university. Findings of this study also indicate the importance of student community, senior students and family-networks in adapting to a new learning environment. There are cumulative evidences from this research to suggest different types of networks in a multicultural university. Students’ self-management skills are found to be vital for smoothness of transition to universities.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".