Exploring student satisfaction and future employment intentions
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the factors that affect higher education student satisfaction and to understand students’ perceptions of their academic success and future employment expectations at a particular institution. Design/methodology/approach This study analyzes institutional performance related to students’ satisfaction and their preparedness for future employment endeavours. The questionnaire is designed specifically for students who are eligible to graduate, and the survey is implemented over the institutional website via the student portal and a total of 750°-seeking undergraduate students (target population) are invited to participate. Findings The descriptive results of this study suggest that while student satisfaction may be relatively similar for all academic programmes, there are differences in the perception of career expectations based on chosen academic programme. Most notably, the results also indicate students’ expectations for employment did not have a negative effect on their satisfaction with the higher education institution (HEI). In contrast, they were mostly satisfied with their academic and personal development. In essence, they felt prepared for the workplace and satisfied with the skills and knowledge developed at a university, regardless of job expectations. This paper suggests that institutions may wish to heighten their focus on academic factors in their efforts to retain students and improve their student academic experience. Originality/value This study is conducted at a small-sized (less than 5,000 students) higher institution in Canada that primarily provides undergraduate courses and focusses on students’ employment expectations and their rating of the academic experiences. This study can assist HEIs in developing policies related to student retention and success. HEIs may find this study useful in developing policies and programmes related to transitioning from undergraduate studies to the workplace.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.006 | 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".