DESIGNING RUBRICS FOR COMMUNICATION COURSES IN ENGINEERING: A Work in Progress
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper will focus on the rubrics that we have developed for the technical communication course and the senior (capstone) design projects. As part of the C.E.A.B.’s and our own Faculty of Engineering’s mandate to more clearly define the goals of each course, the learning attributes associated with course content, and how these are assessed, we first developed rubrics that would help us track and assess students’ communicative competence. However, we soon learned that our presentation of the information impacts how well students assimilate it. Consequently, in our rubrics for the senior (capstone) design courses, we began to phrase the assignment requirements as action items, as something that must be done; for example, a document’s “layout and document design” must use “clear markers to create a visually appealing document,” and the illustrations must “communicate design elements and results.” In this way, students are encouraged to reflect on their individual performance, and one outcome for them is the opportunity to engage in a meaningful dialogue with the professor. One outcome for the professor is having the means to indicate a student’s position on a spectrum of performance. Finally, although linking attributes to learning objectives and determining “competency levels” can be very challenging, we hope to show how the rubrics we have designed may indeed make the task less daunting and more manageable for all stakeholders in the education of our engineering students.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it