Educational Game Design as Gateway for Operationalizing Computational Thinking Skills among Middle School Students
Bibliographic record
Abstract
This qualitative case study reports descriptive findings of digital game-based learning involving 15 Taiwanese middle school students’ use of computational thinking skills elicited through programmed activities in a game design workshop. Situated learning theory is utilized as framework to evaluate novice game designers’ individual advancement in developing a designer language, mindset, and use of computational thinking skills. Three strands of findings were extrapolated from analyzing observational data, participant-generated written responses and artifacts: Understanding games as systems and how components work together in meaningful relationships in game design; Developing growing sophistication in communicating with other novice game designers using language germane to game design; Improving understanding and application of computational thinking skills through game design activities. Extended discussions on three focal cases revealed that using design pedagogy, participants operationalized computational thinking skills in design tasks. Promises and pitfalls of using game design to facilitate computational thinking skills are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".