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Record W2808198455

An Investigation of the Relationship between Professional Learning Community Practices and Student Achievement in an Eastern Canadian School Board.

2018· article· en· W2808198455 on OpenAlexaffvenueabout
Noel Hurley, Tim Seifert, David Sheppard

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMathematics educationLikert scaleStudent achievementAcademic achievementReading (process)PsychologyProfessional learning communityPerceptionMedical educationPedagogyExperiential learningMedicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Abstract The participants in this study were teachers and students of a large school district located on the east coast of Canada. We distributed surveys to 1514 teachers across 84 schools with1423 usable surveys having been completed for a return rate of 94%. At the time of the second data collection, three years later, 78 schools with a total of 1574 teachers agreed to participate. Teachers’ perceptions of their schools as professional learning communities were assessed using 32 items in a 5-point Likert format. The responses to the 2006 survey were factor analyzed using ML estimation. A number of different factor structures were tested, including a single factor model and a second-order factor analysis. In spite of a heavy emphasis by school board leaders and the collaborative development, introduction, and implementation of PLC practices before and during the study period, no significant measurable effect on student learning was identified. While this particular study reports only the relationship between PLC practice usage and reading achievement, Hurley, Sheppard, and Seifert are also investigating two other areas of efficacy in this line of study; one that investigates the relationship with high school Mathematics achievement and one that examines school size and student achievement as mediated by PLC practice

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)0.002
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 score0.550
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.243
GPT teacher head0.488
Teacher spread0.244 · 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

Citations6
Published2018
Admission routes3
Has abstractyes

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