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Neuropedagogy for Improving the Educational Process in Universities

2021· article· en· W3167503464 on OpenAlexvenueno aff
Dina E. Nurmakhanova, Aiman K. Rakhmetova, Dinara A. Kassymbekova, Gulzhamila Meiirova, Gaukhar Rakhimzhanova

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
Fundersnot available
KeywordsPopularitySubject matterProcess (computing)Context (archaeology)Subject (documents)Computer scienceEngineering ethicsPolitical sciencePedagogySociologyEngineeringLibrary scienceCurriculum

Abstract

fetched live from OpenAlex

Objective: This study aims to investigate the problems that neuropedagogy can solve in the context of the educational process.
 Background: Research in neuropedagogy has been gaining popularity in recent years. This has been driven by advances in technology and the social sciences. Every year more and more scientists approach the subject of neuropedagogy to modernise the educational system and improve the educational process.
 Method: The main research methods in this scientific article are the comparative method, methods of analysis and data synthesis, the historical method, as well as the theoretical analysis of scientific literature related to the subject matter.
 Results: The study explored the concept of neuropedagogy and the principles on which it is based. Practical recommendations for teachers of Kazakhstan have been developed. Scientific articles on the subject matter are analysed, the degree of research and the effectiveness of the implementation of neuropedagogy in the educational process is assessed.
 Conclusion: It was concluded that the use of neuropedagogy would provide an opportunity to improve and modernise the education system.

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)0.000
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 score0.569
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.067
GPT teacher head0.338
Teacher spread0.270 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Intellectual Disability - Diagnosis and TreatmentSame topicNeuroscience, Education and Cognitive FunctionFrench-language works237,207