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Record W2973143178 · doi:10.11575/ajer.v65i3.56419

Conceptualizing a Personalized Identity-Focused Approach to Teacher Professional Development: Postulating the Realization of Reform

2017· article· en· W2973143178 on OpenAlexaff
Graham Passmore, Stephen R. Hart

Bibliographic record

VenueUniversity of Calgary · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsLakehead University
Fundersnot available
KeywordsIdentity (music)HumanitiesSociologyProfessional developmentPedagogyPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Identity structure analysis (ISA) reveals core and conflicted identity constructs, long-term aspirant goals for behaviours, behaviours one wishes to avoid, potential for behaviour change when moving from one life domain to another, and people that are the subject of identity conflicts. In this work, ISA is applied to a teacher’s identity to form a framework to guide professional development. A rationale for use of the ISA framework is developed that connects it to calls for reform in professional development. Keywords: teacher identity; identity structure analysis; professional development; mentoring; teacher education L’analyse de structure identitaire (ASI) révèle des constructions identitaires fondamentales et divergentes; des objectifs à long-terme relatifs au comportement; des comportements que l’individu désire éviter; le potentiel pour un changement comportemental lors du mouvement d’une sphère de la vie à une autre; et des gens qui vivent des conflits identitaires. Cet article porte sur l’application de l’ASI à l’identité d’un enseignant de sorte à fournir un cadre pour guider le développement professionnel. Nous développons un motif pour l’utilisation du cadre d’ASI qui le lie aux demandes pour des réformes dans le domaine du développement professionnel. Mots clés: identité d’enseignant; analyse de structure identitaire; développement professionnel; mentorat; formation des enseignants

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
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 studies0.0010.001
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 head0.124
GPT teacher head0.353
Teacher spread0.229 · 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 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
Published2017
Admission routes1
Has abstractyes

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