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Methodological Guidelines for the Deontological Adaptation of Future Teachers in the Education Process

2020· article· en· W4250842435 on OpenAlexvenueno aff
Kasenov Khanat, Urazbayeva Gulsara, Tusupbekova Madina, Zhusupova Roza, Tugelbayeva Gulmira

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)Volume (thermodynamics)PsychologyPhysicsThermodynamicsNeuroscience

Abstract

fetched live from OpenAlex

The methodological guidelines of deontological adaptation of future teachers in the education process are considered: the main vectors of adaptation processes to learning, the mechanisms of professional semantic generation, and adaptation algorithms. This article presents the research of a pedagogical experience of teacher training on the subject of Deontology adaptation, a curricular unit which is part of the education degrees taught at Eurasian National University named after Gumilev (Kazakhstan). The foundation of the curricular unit and its characteristics are presented, as well as the analysis of the students' evaluation of its teaching effects as perceived by them. The data analysis, based on some contents of a portfolio, shows a considerable positive perception of those effects. The purpose of the research is to determine and substantiate the study's methodology and develop the organizational and methodological support for the deontological training of bachelor's education as the basis for the formation of their deontological competence and personal and professional development.

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)0.003
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 score0.613
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.516
GPT teacher head0.506
Teacher spread0.010 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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