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Record W3214398109 · doi:10.15460/eder.5.2.1658

Adapting to a Design-Based Professional Learning Intervention

2021· article· en· W3214398109 on OpenAlexaff
Barbara Brown, Sharon Friesen, Ronna Mosher, Man-Wai Chu, Kirk Robert Linton

Bibliographic record

VenueEDeR Educational Design Research · 2021
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProfessional learning communityGeneral partnershipProfessional developmentResearch designPsychologyLearning designIntervention (counseling)Medical educationInstructional designPedagogyMathematics educationSociologyMedicine

Abstract

fetched live from OpenAlex

Designing a systematic inquiry-based, and knowledge-building experience through continuous professional learning for teachers is a key challenge for school authorities. A total of 26 teachers, five principals, three researchers, one graduate student, and two contract professionals from a university were involved in a research-practice partnership. The partners engaged in a yearlong design-based professional learning series. In this study, design-based research was used as the methodology to understand the participant responses to professional learning during the design, enactment, and refinement phases used to design the professional learning series. Open-ended survey responses, researcher field notes and documents from the professional learning sessions were analyzed throughout the study and during three phases of the learning design. The results indicated there were four key shifts and corresponding adaptations made by the participants as they responded to and engaged in a continuous model of 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)0.018
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.421
GPT teacher head0.597
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations5
Published2021
Admission routes1
Has abstractyes

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