Evaluation of software tools supporting outcomes-based continuous program improvement processes
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
The Canadian engineering accreditation board (CEAB) mandate tasked each engineering programto assess student outcomes in the form of graduate attributes and develop a data-informed continuous program improvement stemming from those assessments. Administering, collecting and organizing the breadth assessment data is an extensive process, typically centralized through the use of software tools such as learning management systems (LMS), content management systems (CMS), continuous program improvement systems (CPI). These systems serve av ariety of roles, ranging from course content delivery, elearning, distance education, learning outcomes assessment, outcomes data management and learning outcomes analytics. Vendors have been developing various solutions to accommodate the shift towards outcomes based assessment as part of a continuous improvement processes.This paper will compare and contrast software tools supporting outcomes based assessment as part of acontinuous improvement process such as eLumen, Canvas, Moodle, WaypointOutcomes, Desire2Learn and LiveText.
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 | 0.003 |
| 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 | 0.000 |
| 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 it