The Development of Students’ Creative Problem-Solving Skills Through Learning Model in Gamification Environment Together with Cartoon Animation Media
Bibliographic record
Abstract
The aims of this study were to synthesize and evaluate the learning model in gamification environment together with cartoon animation media to promote students’ creative problem-solving skills. This study was divided into three phases, (i) synthesized and evaluated the appropriateness of learning model (ii) developed cartoon animation and (iii) assessed creative problem-solving skills. The results show that the learning model consisted of three main components: teaching component, gamification environment, and activities to promote creative problem-solving. The overall suitability assessment of the developed learning model was averaged at 4.69 (SD = 0.46) out of 5, being at the most appropriate level and the scores of the students’ post-learn creative problem-solving skills assessment were significantly higher than the criteria at the level .05. These results lead to a conclusion that the learning model in gamification environment together with cartoon animation media can significantly promote students’ creative problem-solving skills and can be applied to develop desired learners’ achievements and skills.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".