The Relationships between the Resilience Quotient of Undergraduate Students in the Educational Psychology and Guidance for Teachers Course and Their Achievement of the Course Learning Outcomes: A Qualitative Study
Bibliographic record
Abstract
The purpose of this qualitative research was to examine the relationships between the resilience quotient (RQ) of undergraduate students in the Educational Psychology and Guidance for Teachers course and their achievement of the course learning outcomes. The sample comprised 38 second-year students from the Faculty of Education of Kasetsart University enrolled in the course during the second semester of the 2023 academic year. The data were collected through in-depth structured interviews consisting of seven open-ended questions and analyzed using a content analysis approach. It was found that the subjects employed various RO-related strategies to achieve the learning goals according to the course learning outcomes, including adopting relaxation techniques, engaging in enjoyable activities and hobbies, and sustaining self-management by prioritizing tasks and making decisions carefully. When faced with academic challenges, especially when the learning outcomes were not met, the subjects mindfully analyzed the problems, set goals for dealing with them, planned accordingly, and took corrective actions. They also sought guidance from instructors and used the feedback in the problem-solving process while maintaining resilience. From the subjects’ perspectives, the skills in maintaining RQ during a scholastic journey involved accepting reality, reviewing and addressing problems, and continuously improving oneself. The present study underlines the importance of psychological well-being and effective guidance in students’ academic success and personal development.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".