Bibliographic record
Abstract
This work focuses on embedding ethics topics in electrical and biomedical engineering courses. A dedicated course titled Engineering Ethics that existed in the curriculum has been replaced in the department recently by embedding ethics topics into several courses. This work focuses on including topics in the area of environmental ethics into two courses, Electric circuits and Biosensors. It is very relevant as it introduces students to current consumerism and its environmental impact. The global world relies on handheld devices that use rechargeable batteries. There is a need to educate public on the proper disposal of them. Some engineering students are unaware of environmental impact of the improper disposal of batteries and other electronic products and discard them as normal waste. The first course on electric circuits is taken by all engineering majors. Energy from mobile device batteries is discussed at the start of the course along with the need for safe disposal. A project to research on safe disposal regionally and internationally is assigned. The project includes students to survey family members and friends on disposal practices and on the need for advocacy and social responsibility. A survey of students on impact of this assignment will be presented here. Similarly, topics relevant to the study of environmental contamination are covered in the Biosensors course. Students are assigned a project on the use of biosensors to study environmental toxins and to survey family and friends on practices of hazardous waste disposal. A survey of the students on its impact will be presented.
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".