Bibliographic record
Abstract
Over the last few decades the Accreditation Board for Engineering and Technology (ABET) has emphasized the importance of science, technology, engineering and mathematics (STEM) for the undergraduate engineering curricula.In the recent years, however, another component has been added to it, and that is, the Arts, thus transforming STEM to STEAM.The present paper addresses the positive aspects of adding arts to the STEM program, especially in engineering design as well as for engineering practitioners working on a global context.The arts, including literature, music and fine arts, improve our engineering 'reasoning'(left brain) by engaging the intelligence of our emotions (right brain), and hence add that extra touch to our engineering design that customers from different global cultures appreciate.Product design that engages emotions motivate customers to make the final purchase.For the engineers of today, understanding and appreciating another culture is not anymore a choice but a necessity.The slogan of the 1960s, 'think globally but act locally' is changed today to 'think globally and act globally'.The transition from STEM to STEAM can have that global impact by leveraging the arts as a way to communicate and connect globally.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".