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Record W2574585885 · doi:10.1080/00405841.2016.1260402

My Teaching Partner-Secondary: A Video-Based Coaching Model

2017· article· en· W2574585885 on OpenAlexaff
Anne Gregory, Erik Ruzek, Christopher A. Hafen, Amori Yee Mikami, Joseph P. Allen, Robert C. Pianta

Bibliographic record

VenueTheory Into Practice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthInstitute of Education Sciences
KeywordsCoachingPsychologyPedagogyMathematics educationSchool teachersKey (lock)Computer science

Abstract

fetched live from OpenAlex

program, coaches engage teachers in six to nine coaching cycles across a school year. Guided by the program's theory, coaches help teachers reflect on the emotional, organizational, and instructional features of classrooms. MTP was originally developed for Pre-K and early elementary classrooms (MTP Pre-K), but the current paper focuses on the secondary school version of this program, MTP-Secondary (MTP-S), given the need for coaching models with middle and high school teachers. The paper presents the guiding theory of MTP-S and how it relates to key components of the coaching cycle. We then offer a brief synthesis of research demonstrating its effectiveness in raising achievement, promoting positive peer interactions, and reducing racial disparities in teachers' discipline practices. We provide ideas for future research that would help advance theory on the essential components of effective coaching programs in secondary schools.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.072
GPT teacher head0.432
Teacher spread0.360 · 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 designNot applicable
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

Citations47
Published2017
Admission routes1
Has abstractyes

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