The Professional Science Master’s (Psm) Degree In Engineering Technology
Bibliographic record
Abstract
The Professional Science Master's (PSM) Degree in Engineering Technology (ET) is a new degree option created to meet growing industry needs for technologists with broad background and experience to provide rewarding career and academic opportunities for undergraduates in science, technology, business and health majors.According to the Council of Graduate Schools (CGS), this program involves not only advanced disciplinary study in engineering and technology, but also an appropriate array of professional skill-development activities to produce graduates highly valued by employers and fully prepared to progress toward leadership roles.These additional interdisciplinary professional skills include legal, communication, marketing, finance, and business training which are in demand by industry to complement the students' engineering technology expertise.The nontechnical courses are often developed in collaboration with appropriate academic departments outside engineering technologies and are often taught by qualified adjunct faculty from the appropriate areas of industry.The main objective of this proposed program is to graduate high caliber technologists with multiple talents who can effectively participate and directly contribute to the improvement of the U.S. industrial competitiveness in the current global economy.This paper portrays an actual program model that describes the method of tailoring this new master's degree program to respond to current industrial needs, both locally and nationally.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.358 | 0.317 |
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".