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Record W2140317172 · doi:10.5539/ies.v5n6p90

The Peculiarities of Forming Rural School Students’ Healthy Living Skills after Shool and in Extracurricular Work by the Use of Information Innovation Technology

2012· article· en· W2140317172 on OpenAlexvenueno aff
Daniarov Talgat, Bazarbaev Kanat, Nyshnova Saltanat, Myrzakhanova Akbota

Bibliographic record

VenueInternational Education Studies · 2012
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPaceIdeologyMeaning (existential)Function (biology)Quality (philosophy)SociologySocial changeMathematics educationPedagogyPsychologyPolitical scienceEconomic growthEconomicsPoliticsEpistemology

Abstract

fetched live from OpenAlex

If we turn to the educational views and ideas in the history of education, we see that the goals of education have an active and changeable specific historical characteristics. Specifying its state policy and ideology determine the social needs, based on natural, social and human development of objective laws. In this structure, there is a need complies with the requirements of society development level of productive forces and relations of production quality, the pace of scientific and technical progress, economic opportunity society, the level of development of educational theory and practice of educational opportunities, the level of development of educators and teachers. Analysis of different definitions lead to the conclusion that innovation is a substantial change, and the main feature of innovative change - this is a function of the change. The innovation comes at a time when educational problems can not be solved by traditional forms, creating the need for new technologies in line with new goals and objectives. Despite the fact that the traditional and innovative educational technologies have differences, it does not mean that their unity should be considered separately. They have some inherent characteristics, but objectively they have common characteristics that bind them together. In order the teacher could effectively carry out the objectives and tasks of education and training, it must be based on the characteristics of each use of educational technology and adequately understand the meaning and essence of their relationship with each other.

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)0.001
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 score0.223
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.036
GPT teacher head0.358
Teacher spread0.322 · 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
Published2012
Admission routes1
Has abstractyes

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