Implementing Specialized Management Information Systems in the Post-Secondary Program
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
Undergraduate students are computer-literate and learn to use software quickly but may not grasp the underlying concepts of cross-departmental problem solving, integration, communication, and collaboration, without actual industry experience. When implemented properly and assignments well thought out, MIS systems may help overcome these hurdles. Larger ERP systems such as SAP are taught through business schools. Curriculum support is provided by the large ERP vendors who have created modules specifically for the university curriculum. Vendors of smaller systems are not usually afforded this "luxury." As a result, smaller systems are not usually taught in the post-secondary curriculum. This paper identifies some of the challenges, critical success factors and lessons learned from implementing a smaller second-tier system tailored for a specific industry, within an undergraduate course. This study is valuable because of the applicability to other similar school programs and challenges.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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