Hiding in Plain Sight: Identifying Computational Thinking in the Ontario Elementary School Curriculum
Bibliographic record
Abstract
Given a growing digital economy with complex problems, demands are being made for education to addresscomputational thinking (CT) – an approach to problem solving that draws on the tenets of computer science. Weconducted a comprehensive content analysis of the Ontario elementary school curriculum documents for 44 CT-relatedterms to examine the extent to which CT may already be considered within the curriculum. The quantitative analysisstrategy provided frequencies of terms, and a qualitative analysis provided information about how and where termswere being used. As predicted, results showed that while CT terms appeared mostly in Mathematics, and concepts andperspectives were more frequently cited than practices, related terms appeared across almost all disciplines and grades.Findings suggest that CT is already a relevant consideration for educators in terms of concepts and perspectives;however, CT practices should be more widely incorporated to promote 21st century skills across disciplines. Futureresearch would benefit from continued examination of the implementation and assessment of CT and its relatedconcepts, practices, and perspectives.
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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 | 0.006 | 0.000 |
| 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 | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".