Improving Learning in First‐Year Engineering Courses through Interdisciplinary Collaborative Assessment
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
Abstract This paper describes a feedback process that assessed first‐year engineering student learning using a mastery exam. The results were used to improve learning and teaching in first‐year courses. To design the initial exam, basic knowledge and concepts were identified by instructors from each of the host departments (Chemistry, Math, Physics and Computer Science). In 2004, the 45‐item exam was administered to 191 second‐year engineering students, and in September 2005, the revised exam was administered to the next class of second‐year engineering students. The exam was analyzed using Item Response Theory (IRT) to determine student abilities in each subject area tested. Between exam administrations, workshops were conducted with the four department instructor groups to present exam results and discuss teaching issues. The exam provided a learning assessment mechanism that can be used to engage faculty in science, mathematics, and engineering in productive linkages for continual improvement to curriculum.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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