Developing Communities of Practice Around E-learning and Project Management
Bibliographic record
Abstract
In 2007-8 the Australian Catholic University (ACU), undertook a project to develop new resources to provide training and support in eLearning for staff and students. The project was undertaken by a multidisciplinary team drawn from all six campuses and was led by an externally contracted Project Manager/eLearning specialist. This reflective case study reports on how the use of ACU’s project management methodology and the selection of a matrix organisation for the project, resulted in the nurturing of existing communities of practice (CoPs) around both eLearning and project management at ACU. Key recommendations are that effective project management practice and a matrix project organisation can promote and nurture knowledge sharing amongst CoPs in a university setting. Resume En 2007-8 la Australian Catholic University (ACU), a mis sur pied un projet visant a developper des nouvelles ressources aux fins de fournir de la formation et du soutien a l’apprentissage en ligne pour les enseignants et les etudiants. Le projet a ete realise par une equipe multidisciplinaire tiree des six campus et a ete mene par un Gestionnaire de projet/specialiste en apprentissage en ligne externe. Cette etude de cas reflective rapporte comment l’utilisation de la methodologie de gestion de projet d’ACU et le choix d’une organisation matricielle pour le projet, ont eu pour effet d’alimenter les communautes de pratique (CdPs) existantes en lien avec l’apprentissage en ligne et la gestion de projet chez ACY. Les recommandations cles sont que les pratiques de gestion efficaces et une organisation matricielle du projet peuvent promouvoir et alimenter le partage des connaissances parmi les CdPs dans un cadre universitaire.
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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 | 0.069 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".