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Record W3147374043 · doi:10.29173/iasl7993

Connecting and making coherent teachers' knowledge: Building a knowledge-oriented culture

2021· article· en· W3147374043 on OpenAlexvenueno aff
Linda C. Langford

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge managementKnowledge sharingPersonal knowledge managementKnowledge buildingCore KnowledgeCommunity of practiceOrganizational learningSociologyBody of knowledgeKnowledge value chainPedagogyComputer science

Abstract

fetched live from OpenAlex

This paper is partly based on a doctoral thesis entitled Knowledge creation, knowledge sharing and knowledge use: A case study. The paper challenges teacher librarians to view themselves as knowledge architects in the designing and sustaining of a teachers' learning community - one which values teachers' knowledge as core business in the school. This paper builds a case for teacher librarians to realign their role by focusing on their colleagues' knowledge and asking: "How can teachers' knowledge be shared, and captured and disseminated to better enable a knowledge-oriented culture?"' and "What are the structures and processes that bring teachers' knowledge out into the open to be shared?" Part A of this paper presents a synopsis of the study's purpose, rationale and key issues. It brings together the theories of learning community and knowledge management in establishing a discourse that is centred on valuing, connecting and making coherent teachers' knowledge as essential in enabling a knowledge-oriented culture to grow and to flourish. Part B presents an overview of the study with a focus on one of its three themes: knowledge sharing. Part C concludes with a brief discussion on how this research can contribute to the role of school libraries and teacher librarians in the emerging discourse on professional learning and knowledge sharing within and across work place units.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.033
GPT teacher head0.339
Teacher spread0.307 · 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.

Study designQualitative
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

Citations0
Published2021
Admission routes1
Has abstractyes

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