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Record W7068058379

The Nature of the Teacher Knowledge Constructed in a Multimodal Professional Learning Community

2017· dissertation· en· W7068058379 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsProfessional learning communityProfessional developmentTechneScope (computer science)Action researchAction (physics)Professional studiesGrounded theoryTeacher education
DOInot available

Abstract

fetched live from OpenAlex

This research explores the nature of teacher knowledge constructed over four years in a multi-modal environment. Fourteen K-12 teachers, from Ontario, Canada and Michigan, USA, met online for two hours during a monthly research release day, participated in online chats, a forum site called Virtual Professional Learning Community, as well as participated in four three-day summer institutes. The teachers used these times to engage in knowledge building, creating research for their specific schools/classes in a recurring cycle of learning. \nThe data consist of multiple forms, including the online meetings, the forum, and the summer institute discussions. The research investigated what types of knowledge teachers developed and how those knowledges informed their professional learning. Grounded Theory informed the data gathering and an hermeneutical approach was used for the analyses. Three types of professional knowledge emerged, associated with the classical Aristotelian intellectual virtues: episteme, techne and phronesis. Teachersâ discourse revealed the complexity of their professional knowledge and the wide range of scope of their action â a finding that goes beyond many neoliberal conceptions of the profession. Findings provide ways to develop models of professional development with teachers leading to their sustained journey for meaningful professional learning.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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