Engineering graphics in the new millennium: integrating the strengths of sketching and CAD
Bibliographic record
Abstract
Engineering graphics has always been viewed as one of the cornerstones of an engineering education. It is important, indeed critical, to engineering since it is the basis for communicating all (engineered) designs. It is the language by which engineers communicate and think. There has been a revolution in engineering graphics. Gone is the T-square, the symbol for engineers everywhere, replaced first by AutoCAD and more recently by "three-dimensional parametric solid modelling" software. While this advanced computer software may be a better way to learn graphics, the same problem remains: how do we effectively teach this language of engineering to undergraduate students? Sketching is a useful tool in teaching engineering graphics theory and standards to undergraduate students since it allows the student to concentrate on learning the material with less distraction. CAD is also extremely useful for teaching students about design, in particular how constraints are handled and ideas worked out. The question remains as to how to integrate these two tools into a useful whole? The author briefly discusses these two questions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".