Evaluation of software tools supporting outcomes-based continuous program improvement processes: Part 3
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 accreditationboard (CEAB) mandate tasked each engineering programto assess student outcomes in the form of graduateattributes and develop a data-informed continuousprogram improvement stemming from those assessments.Administering, collecting and organizing the breadthassessment data is an extensive process, typicallycentralized through the use of software tools such aslearning management systems (LMS), contentmanagement systems (CMS), Assessment Platforms (AP)and Curriculum Planning & Mapping tools. Thesesystems serve a variety of roles, ranging from coursecontent delivery, e-learning, distance education, learningoutcomes assessment, outcomes data management andlearning outcomes analytics. Vendors have beendeveloping various solutions to accommodate the shifttowards outcomes based assessment as part of acontinuous improvement process.This paper will continue from the first and secondpapers presented at previous CEEA meetings. It willgauge how well each tool aligns with the EGAD(Engineering Graduate Attribute Development) project 5-step process and compare and contrast software toolssupporting outcomes based assessment as part of acontinuous improvement process.
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 | 0.002 | 0.005 |
| 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