Fostering equity, accessibility and academic integrity within an LMS module
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
A mandatory learning management system (LMS) module informing students studying English as a second language (ESL) about academic integrity and university guidelines was implemented at a program level and was a success for several years. However, following a shift to online learning using both synchronous and asynchronous formats, there was an increase of reported cases of academic infractions. The LMS module previously incorporated principles of Universal Design for Learning (UDL) to target the diverse needs of language learners. The current paper reports on an analysis of the module’s compliance to research recommendations related to UDL guidelines for improving student comprehension of academic integrity and the application of Web Content Accessibility Guidelines (WCAG) within the LMS module are explored. Furthermore, the introduction and ubiquitous as well as unregulated use of AI has added another concern, as the limited resources and insufficient guidelines about this type of academic infraction present a new challenge for both teachers and students. The presentation includes the impact of previous modifications and discusses potential outcomes in light of the current analysis. The results of the most recent modifications are forthcoming.
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 | 0.001 | 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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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