Academic Press and Student Engagement: Can Academic Psychological Capital Intervene? Test of a Mediated Model on Business Graduates
Bibliographic record
Abstract
Psychological wellbeing has gained much prominence over the recent years. Parallel to organizational domains, empirical attention is also being paid across the academics as well. The present study attempted to examine the much important role and relationship between academic press and student engagement and to what length academic psychological capital can potentially mediate in the relationship. A total of 371 undergraduate students were sampled for the present study from a private university in Bahrain. Through using structural equation modelling using Smart PLS 3 the results of the mediated model reported significant relationship between academic press and academic psychological capital (i-e academic efficacy and resilience). Though the study did not find any support for academic press and student engagement relationship, nonetheless, found a significant mediation of academic psychological capital in the relationship between academic press and student engagement. The findings have suggested that students’ perceptions about how much their teacher presses them to do thoughtful work, facilitation in explaining and motivating for full efforts can act as a key ingredient for nurturing students` connectivity with the studies in general and views about their own learning. Accordingly, the study has also underlined that students with positive academic press from their teachers tend to be higher in engagement due to enhanced efficacy and resilience. The present study has attempted to address a major research gap with acute empirical findings for academicians to enhance their students` wellbeing.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".