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The Specificity of Preparing Students at Pedagogical Universities for Educational Activity in the Digital Epoch

2020· article· en· W3088510614 on OpenAlex
Оксана Петренко, Тетяна Ціпан, Жанна Стельмашук, Nadiia M. Hrynkova

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2020
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Minority Health and Health DisparitiesNational Institutes of Health
KeywordsEpoch (astronomy)Mathematics educationPsychologyMedical educationAstronomyMedicinePhysicsStars

Abstract

fetched live from OpenAlex

Objective: the study is aimed at analysing the problems of forming the skills of educational activities of an individual, leading approaches that outline the range of solutions to education problems, features, and possibilities of these approaches to elucidate the totality of effective methods and techniques for special education pedagogical specialties in students. Background: education in higher education institutions (HEI) or another educational institution is based on the formation of an individual who has achieved the basic characteristics of his development in the process of professional development and in the framework of cooperation. Method: the experimental method was used in work during 2014-2019, in which 219 students of experimental groups and 213 students of control groups participated. Results: The authors determined the possibility of using student training tools as a specialist and a socially responsible person using pedagogical tools implemented in a digital educational environment. Conclusion: Students can be trained in pedagogical higher education directly using digital technologies. Thus, working with similar technologies will not require additional training in the implementation of practical work in further professional activities

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.

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 score0.367
Threshold uncertainty score0.170

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 head0.152
GPT teacher head0.377
Teacher spread0.225 · 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