Engaging High School Students in an Engineering Thermodynamics Project
Bibliographic record
Abstract
Efforts for recruiting and retaining students in engineering programs are evident in many postsecondary institutions around the world. These efforts include outreach programs at both elementary and secondary school level, as well as projects that develop capacities beyond technical content—often taught as declarative and procedural knowledge. The mandate of the Galileo Education Network Association includes the design of rich learning environments engaging K – 12 students in authentic tasks: tasks that resemble the real work of professionals such as engineers. We describe the experience of enacting a seven-session engineering project in thermodynamics with Grade Ten students. Special attention is paid to formative assessment as an essential support for students' learning along the project. The initial project resulted from the collaboration—as a means for teacher professional development—between this network association and the mathematics and science teachers in a western Canadian high school. We propose that programs for teacher professional development in mathematics and science should include a focus on tasks that resemble the work of engineering in order to design authentic, engaging learning tasks, and assessing strategies that support and enhance student learning.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".