A STUDENT-DESIGNED LABORATORY COMPANION BOARD FOR A COURSE ON MICROPROCESSOR INTERFACING AND EMBEDDED SYSTEMS
Bibliographic record
Abstract
Abstract – This paper describes the production and usage of a student-designed laboratory companion board for a core course on microprocessor interfacing and em-bedded systems in the Department of Electrical and Com-puter Engineering at Queen’s University. The companion board connects to existing digital-only hardware in order to provide analog-digital conversion and other features. The design and prototype implementation of the compan-ion board was pursued as a capstone design project by three students during the 2014-2015 academic session. The student designers had agreed from the outset to allow their intellectual property to be used for educational pur-poses. In mid-2015, a production run of 30 boards was completed. A total of more than 300 students then used the companion board in laboratory activity during the Fall 2015 and Fall 2016 terms. The introduction of this student-designed equipment into the laboratory has been a positive development that provides an example to stu-dents of how material learned in multiple courses can be integrated together to produce a valuable outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.012 |
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".