Acquiring Skills for Academic Success through Project-Based Learning in First-year Engineering
Bibliographic record
Abstract
This paper presents the development of a ballista-themed project that comprises part of the pilot of a redeveloped first-year engineering course at Memorial University. The course aims to teach students to “think like an engineer” and provide them with skills and tools to support them throughout their engineering education. Students learn to use tools such as Microsoft Excel and Matlab through the use of meaningful, yet accessible, technical assignments.Students are acquiring requisite engineering knowledge while developing a skill set that will support further learning. The ballista project requires students to design a simple numerical computer model linking the launch and trajectory of a projectile in order to calculate the launch settings required to hit a series of targets. In preparation for the project, instruction is offered on topics including the conservation of mechanical energy, projectile motion and numerical integration. Students compete using an assembled, moderately sized ballista prototype to launch wooden spheres at a castle-like structure. Student use their computer models along with experiment-based model corrections to account for discrepancies in theoretical and actual trajectories.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".