DEVELOPING FOR AND DEPLOYING WEBWORK ACROSS DISCIPLINES IN SECOND-YEAR ENGINEERING
Bibliographic record
Abstract
Online homework systems provide immediate feedback to students, enhancing student learning. However, paid online homework from textbook publishers or other sources systems can be costly and also raise concerns about student data privacy. WeBWorK is an open-source online homework system that can be setup on local servers, is free to students and has been in use since its development in the mid-1990s. Previous to this work around 200 engineering problems were openly shared on the WeBWorK platform, limiting opportunity for adoption. In order to address this, we have developed, deployed, and evaluated nearly 1000 new engineering problems across a wide range of engineering topics at the second-year level. 
 Student perceptions of WeBWorK have been evaluated using surveys at the start and end of courses where it is deployed. These surveys indicate that students generally prefer the WeBWorK system to other online homework systems they have used. Surveys also indicate that students were generally motivated to both attempt and complete all assigned problems that contributed to their grade, and believed WeBWorK enhanced their learning. The creation of error-free WeBWorK questions was difficult, however the hope is that the ability to re-use and share these questions ensures they provide a higher value over the long term than paper-based homework problems.
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".