The influence of Organizational Image on Academic Success for International Students
Bibliographic record
Abstract
Image as a concept that develops through personal, environmental, cultural, and organizational factors throughout history. Organizational image is the overall evaluation of people’s views regarding an organization or system. The purpose of present study was to determine the relationship between international university students’ academic achievement and perceived organizational image. As this is a descriptive research for it measures the image perceptions of the participants at a single time, quantative research methods were used. The population of the research was 2208 international students at Uludag University in Bursa. Randomly selected 1718 students (%77.8) who provided anonymous responses were the sample of the study. To examine the relation between organizational image and academic achievement, correlation analysis was used. To control the effect of the organizational image on the academic achievement regression analysis was used. Students’ academic achievement was mostly affected by reputation and recognition, provided services and general view and physical infrastucture at moderate level. As the students' image perception towards the university increases, their acdemic success also increase. Perceived organizational image affected students’ academic achievement significantly and explained 16% of the variance of academic achievement. General view &physical infrastructure provided services, reputation and recognition, and extra curricular activities from the sub-dimensions of organizational image perception have a meaningful effect on the academic success of students. Key findings are discussed and recommendations offered to address issues related to organizational image.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".