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Record W1604962874 · doi:10.22329/celt.v5i0.3432

3. Connecting Inquiry and Practice: Lessons Learned From a Multi-Year Professional Learning Partnership Initiative

2012· article· en· W1604962874 on OpenAlexaffvenueabout
Carol Rolheiser, Mark Evans, Mira Gambhir, Kathy Broad

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeneral partnershipProfessional learning communityProfessional developmentPedagogyFaculty developmentSociologyTeacher educationHigher educationMedical educationPsychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Since 2002 the Initial Teacher Education Program at the Ontario Institute for Studies in Education, University of Toronto, has run a series of professional learning partnership projects between university instructors and K-12 educators. The Inquiry Into Practice Series, based on a collaborative inquiry approach, has strengthened the commitment to program principles and benefited the participants by deepening understanding about a range of educational questions and issues and improving practice. In this article we review key features and principles of this multi-year initiative and discuss challenges, lessons learned, and outcomes. We also provide reflections regarding the importance of high quality professional learning models that support teaching and learning and that are responsive to changing and complex educational pressures and contexts both in higher education and K-12 education.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.044
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.010
Scholarly communication0.0150.012
Open science0.0030.016
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.157
GPT teacher head0.439
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2012
Admission routes3
Has abstractyes

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