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Record W7046932250

Enhancing Knowledge Management Practices: A Multiple Holistic Case Study with Principals and Teachers in a Western Canadian Province

2023· article· en· W7046932250 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Crossing (Liberty University) · 2023
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge levelQualitative researchData collectionQualitative propertyPersonal knowledge managementQualitative analysisEducational attainmentBody of knowledge
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this multiple holistic case study was to understand how principals and teachers in a school division in a western Canadian province enhance their knowledge management practices. Knowledge management was generally defined as the organization, capture, use, and analysis of the impact of a group’s collective knowledge. The theory guiding this study was Davenport and Prusak’s theory of knowledge management as it explained the relationship between principals and teachers and how they use knowledge management. This qualitative research study was a multiple holistic case study which involved six principals and six teachers in a school division in a western Canadian province. Data were collected using individual interviews, document analysis, and journal prompt reflections. Data analysis included transcription by me, cross-case synthesis, various cycles of codes, categories, sub-categories, and themes. Although the six principals and six teachers were already using knowledge management to move the learning of students forward, the findings indicated what would enhance their knowledge management practices. The findings indicated that the participants used knowledge management practices for goal attainment through connections. Goal attainment was through effectiveness and efficiency while connections were through relationships, involvement, and engagement.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.266
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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