A review Assessing the role of Communities of Practice as a tool for managing knowledge in Indian higher education
Bibliographic record
Abstract
Knowledge and information transfer have become important ingredients for an organization’s competitive advantage. Knowledge management has emerged as an overarching strategy to enhance organizational performance and promote innovation. This strategy is implemented in most organizations through the creation of Communities of Practice (CoP). These are networks of individuals with a common, shared purpose grouped together to facilitate knowledge building, idea creation and information exchange. Actively engaged CoPs can greatly help in collectively constructing new knowledge and transferring it to new members. Using the readily available online tools today, new knowledge networks can be created quickly and knowledge can be disseminated effectively beyond the community boundary. Educational institutions in India have grown in quantity, however they grossly lack in the quality. Quality plays an important role in higher education in today‘s globalized economy and in the need to build a knowledge society. With India poised to becoming a global superpower the quality of higher education in general and technical education in particular needs to be greatly improved. The purpose of this paper is to discuss knowledge management (KM) as a solution to enhance the organizational knowledge. More specifically, CoPs can assist in developing the faculty and improving the teaching and research practices in higher education in India.
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How this classification was reachedexpand
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".