Learning management systems : a case study of the implementation of a web-based competency and training management program at Bell Canada
Bibliographic record
Abstract
Systemic models of essential roles, processes, products and factors involved in implementations of web-based competency and training management programs are important guidance tools to organizations integrating learning management systems (LMS) to support human performance improvement goals. In order to leverage the potential of LMS, strategies to use a LMS to align e-learning and classroom-based training with competency requirements need to be delineated. This thesis applies the grounded theory (Strauss & Corbin, 1990) approach to develop a holistic understanding of the implementation of a web-based competency and training management program at Bell Canada, and generate a descriptive, systemic model of the steps performed. The findings suggest that the process of implementing a web-based competency and training management program involves different phases, and success is highly dependent on the change management approach, the level of granularity of competency definitions, the types of competencies models used and the instructional design strategy employed for content development. A set of recommendations for the evolution of research on effective management of competency and training systems technology is made
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".