Development of an Academic Well-being Model for Gifted Students: A Grounded Theory Study
Bibliographic record
Abstract
Objective: This study aimed to identify the factors influencing the academic well-being of gifted students to develop a model. Methods and Materials: The research method used in this study was qualitative, utilizing a grounded theory approach. Data were collected through semi-structured interviews. The data were examined and analyzed based on Strauss and Corbin's (1998) grounded theory methodology. The study population consisted of all male and female gifted sixth-grade students in the city of Isfahan in 2022. The research sample was selected through purposive sampling, and after conducting interviews with 23 students, the factors influencing academic well-being were identified. It should be noted that data analysis was conducted using three stages of open, axial, and selective coding. Findings: Based on the results of the study, open codes were organized around 57 concepts, axial codes included 8 concepts, and selective codes were identified and extracted into 4 concepts under the titles of school context, family context, social context, and individual resources. Conclusion: The findings of the research suggest that by recognizing and understanding the factors influencing academic well-being, it is possible to create conditions that enhance the academic well-being of gifted students.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".