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Record W3174726287 · doi:10.1051/e3sconf/202127312087

Digital environment as effective pedagogical tool of socialization in the context of modern education

2021· article· en· W3174726287 on OpenAlexaboutno aff
Olga Gorbatkova, О А Кочергина, Olga Victorovna Kiryushina

Bibliographic record

VenueE3S Web of Conferences · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSocializationContext (archaeology)ComprehensionAdaptation (eye)Process (computing)CurriculumConceptual frameworkPedagogySociologyEngineering ethicsPsychologyMathematics educationComputer scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

Today, the modern educational paradigm is based on the organization of new forms of social education and training with new digital technologies introduction. In the article, the author sproceed from the main conceptual provisions of domestic and foreign the ories, which allow us as serting that the pedagogically justified use of the digital environment, aimed at solving the problems of social education, can contribute to the adaptation of students to life in the modern in formation society. The purpose of the study is to identify the problems and perspectives of the students’positive socialization formation under the conditions of modern education based on the theoretic alanalys is of domestic and English-speaking (the USA and Canada) scientific works that reflect the content of the digital technologies implementation. This article at tempts to: reveal the essence of the digital environment concept as a pedagogical tool for students’ positive socialization, where the digital environment represents an element of the information and educational environment, with in which socialization is revealed, where the cybers pacesocial process espotential comprehension is carried out; determine the social and educational effects, the main conceptual provisions of the digital environment use as the pedagogical tool for the students’ positives ocialization; based on the analysis, expand knowledge in the context of the theoretical and methodological aspects for domestic sciencein view of the research of scientific works in modern English-speaking countries (the USA, Canada).

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.201

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)0.0000.000

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 head0.054
GPT teacher head0.323
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations1
Published2021
Admission routes1
Has abstractyes

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