The Level of High-Order Thinking and Its Relation to Quality of Life among Students at Ajloun University College
Bibliographic record
Abstract
The study was designed to identify the effect of high-order thinking on the quality of life among Ajloun University students. The study used the associative method. The randomly selected sample consisted of 147 students from Ajloun University College. The study used two tools: The two measures were applied to the sample of the current study after extracting the psychometric properties of the two scales in terms of validity and reliability.The results indicated that the high-order thinking among the students was moderate. The students also achieved a medium degree according to the quality of life scale. There was a statistically significant correlation between both the high-order thinking and the quality of life. There were statistically significant differences in quality of life and the level of high-order thinking due to gender variable in favor of males and academic specialization in favor of students of scientific colleges, the study recommended the need for further research and studies on the relationship between quality of life and other variables such as self-efficacy, self-learning, and other variables, and to train students in skills that raise their high-order thinking skills because of their close relationship with quality of life and training programs and semi-empirical studies to improve students’ perception of level of life and its quality and satisfaction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".