(Dis)Inclination of Iraqi Medical Students Towards Creative Thinking: A Quasi-Experimental Study
Bibliographic record
Abstract
BACKGROUND: There have been several attempts in the past centuries to quantify the human intelligence, many of these attempts were successful. On the other hand, there have been parallel trials to identify and quantify an individual’s creativity. To date, there is no universal definition of creativity nor a quantifying system to measure it with a reliable accuracy.MATERIALS & METHODS: This is a quasi-experimental study in an Iraqi population of undergraduate medical students aged 18-20 years; the male-to-female ratio is 3 to 10. The total number of participants was 195 (n=195) who were allocated into three groups; A, B, and C (nA=67, nB=61, nC=67). Each group was interviewed separately, and the participants were given a choice to either correspond to a quiz on an already taught medical subject or write down ideas (one or more) with creative-innovative potentials. There was no restriction on time, language, or the theme of the topics to be written.RESULTS: There was a significant difference in between the three groups’ tendency to take the quiz (p-value=0.040). However, inter-group and intra-group analyses failed to detect any significant difference in students’ tendencies towards either a creative or a classical form of thinking. Besides, gender was not found to be of a determinant effect on an individual’s tendency towards creativity (p=0.633) or traditional thinking based on an already taught medical knowledge (0.905).CONCLUSION: There were no statistically significant differences in the tendencies of students towards either an original (creative) or a standard pattern of thinking. However, inter-group analyses indicated some substantial differences in students’ affinity towards exploring an already taught medical knowledge.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".