Engaging in Integrity: A Case Study on Leveraging the LMS for Faculty Education
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
Expedited by the onset of the COVID-19 pandemic, the learning management system (LMS) has become a fixture in the infrastructure of the post-secondary classroom. This paper presents a case study describing the actions of a centralized Academic Integrity Office (AIO) at a Canadian community college that aimed to promote faculty engagement and support academic integrity education through the LMS. Specifically, we narrate the development and evolution of an LMS-based repository, examining its impacts and offering recommendations for enhancing social learning and community building. Over time, this repository was transformed into a more robust, centralized portal that improved access to academic integrity resources. Viewership increased to approximately 100 daily visitors, highlighting how platform selection influences access, which in turn supports faculty engagement and participation. This work seeks to address a gap in practice and scholarship by exploring how LMS functionalities and institutional portals can be leveraged to foster communication, build community engagement, and support the development of faculty and student academic integrity literacy while also strengthening faculty-practitioner partnerships.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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