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Record W2162675059 · doi:10.5539/res.v7n1p161

Features of Formation of Future Educational Psychologists’ Professional Identity during Their Retraining

2014· article· en· W2162675059 on OpenAlexvenueno aff
Svetlana E. Chirkina

Bibliographic record

VenueReview of European Studies · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsRetrainingPossession (linguistics)PsychologyProfessional developmentIdentity (music)Humanistic psychologyValue (mathematics)Identity crisisProfessional studiesHumanismPedagogyEngineering ethicsMedical educationSocial psychologyPolitical sciencePersonalityLawMedicine

Abstract

fetched live from OpenAlex

The actuality of the problem’s research is caused by conditions of three kinds: firstly, the increasing demand for the profession and humanistic values of the practical psychologist in education; secondly, the special circumstances of the accelerated training of psychologists (from former teachers), who are actually taking possession of a new profession; thirdly, the lack of research, where the impact of training on professional identity is studied. The purpose of the article is to uncover the structure of future educational psychologists’ professional notions, identifying the occurrence period of their basic elements (“standard frame”) of professional-psychological picture of the world, establishing the peculiarities of professional outlook. The leading method of study of this problem is ascertaining experiment. As a result the structure and genesis of professional psychological image of the world of the future educational psychologists was revealed. The materials of the article are of great value to the organizers of professional retraining of educational psychologists, academics, as well as valuable in the development of recommendations regarding formation of policies in the sphere of additional education in “Practical Psychology in 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.390

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 studies0.0000.000
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 head0.064
GPT teacher head0.412
Teacher spread0.348 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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