Creation of Open-Source Course Materials for Engineering Economics Course with Help from a Team of Students—Lessons Learned
Bibliographic record
Abstract
Abstract All engineering students in Canada must take an Engineering Economics course as part of program accreditation requirements. These courses mainly focus on the evaluation of monetary profits and direct financial costs incurred during the design, operation and decommissioning phases of projects. Instructors commonly use textbooks as the primary tool to guide the students through the content of this course, which tend cost around $100 US each student. Like many courses, the materials in this course does not change much over time resulting in many students opting to not buy the required textbook and instead rely on free sources of information found online, in older editions of textbooks or simply rely on course notes. The patchwork of sources creates problems in this course in particular, because of the variation of notation used across sources, which can easily cause confusion. It was this problem that inspired the creation of a set of open-source materials that students and instructors can use for free, enabling the instructor to have control over notation and concepts to focus on while saving the students money. This paper discusses the lessons learned during the creation of these materials, and in first-time use of these materials in a class of 200 fourth-year undergraduate civil engineering students, as well as dissemination challenges after the project ended.
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".