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Taking into Account the Individual Characteristics of Those Entering Primary School

2021· article· en· W4200573777 on OpenAlexaboutno aff
В.С. Гаппоева, Zinaida G. Khabaeva, Tatiana A. Bekoeva

Bibliographic record

VenueVestnik of North-Ossetian State University · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPsychosocialDevelopmental psychologyMaturity (psychological)Test (biology)PerceptionQuarter (Canadian coin)Mathematics educationGeography

Abstract

fetched live from OpenAlex

School readiness is one of the key components that ensure the success of education. The factors determining a child’s readiness for school include parameters reflecting indicators of physical, psychosocial and psychophysiological development. Morpho-functional immaturity of brain systems that provide the possibility of mental and motor activity, perception and processing of information causes various difficulties in learning. There are various methodological approaches that determine the level of readiness of children for systematic schooling. In the work, Kern-Irasek tests for visual activity (drawing on a given topic), logical and categorical thinking were used to assess readiness for school, an analysis of general awareness and the degree of psychosocial maturity was carried out. The work was carried out on students of the 1st grade of a small rural school and a kindergarten preparatory group. Among the 1st grade students at the end of the 2nd quarter, only girls were prepared for school according to all the analyzed indicators. There were no “immature” children among them, whereas for boys the figure was more than 60%. Overall, the number of “immature children” in the whole class was 33.3%. It is significant that the children belonging to the “immature” group were, as a rule, from large families, where they were not given due attention. Among the children of the kindergarten preparatory group, a larger percentage of those belonging to the category of “mature” and “middle-aged” (90%) were identified. At the same time, the test results again revealed the best results among girls. The data obtained should be considered as evidence of earlier psychofunctional development of girls in relation to boys, which is manifested in their more conscious attitude to learning, better abilities to implement conditional reflex activity, cognitive learning, performance indicators in the first years of training. The high percentage of “immature” children among 1st grade students emphasizes the need for mandatory testing of preschool children and the creation of optimal conditions for their physiological and psychosocial development. Keywords: school maturity, preschool children, psychophysiological factors, school readiness. For citation: Gappoeva V.S., Habaeva Z.G. Taking into Account the Individual Characteristics of Those Entering Primary School // Bulletin of the North Ossetian State University named after K.L. Khetagurov. 2021; 4. DOI: 10.29025/1994-7720-2021-4-103-111 (In Russ.).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.032
GPT teacher head0.271
Teacher spread0.240 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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