Enhancements needed for more viable electronics technologist education
Bibliographic record
Abstract
A study was conducted in 1990 of the needs and opportunities for enhancing electronics technologist education programs in Montreal, Canada. Managers in eight high-technology companies, university professors, and teachers in three colleges were interviewed. A survey of graduate technologists (90 replied) was also conducted. Further discussion with technologist educators enabled a number of critical enhancements to be identified. Some of the enhancements which were found to be most desired and needed are: (1) more and better use of computer-aided design (e.g., Orcad-Spice) and simulation study packages in college laboratories to develop a deeper understanding of system and circuit behaviors, and to undergird troubleshooting skills: (2) better interpersonal communications and team-working skills training; (3) more industrial experience, e.g. internships/co-op programs; (4) more mathematics courses to enable technologists to enter university electrical engineering programs when the opportunity occurs and to enable them better to understand industrial quality control work; and (5) reframing of electrotechnology programs to make them more attractive and more accessible to female students.>
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".