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Organization of scientific and research activities of higher education students in the context of modern educational technologies

2025· article· en· W4409869938 on OpenAlexaboutno aff
Olena Kosaruk

Bibliographic record

VenueHealth and Safety Pedagogy · 2025
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Engineering ethicsMathematics educationSociologyPedagogyEngineeringPsychologyHistory

Abstract

fetched live from OpenAlex

The article explores the theoretical and practical aspects of organizing research activities among higher education students in the context of modern educational technologies. It highlights that research activity is a key mechanism for developing critical thinking, as it involves not only the acquisition of new knowledge but also its verification, systematic analysis, and synthesis. The effectiveness of employing educational technologies such as group discussions, case studies, debates, game-based simulations, and flipped learning in facilitating research work is substantiated. The study analyzes international experience in organizing student research in universities across the USA, Canada, and Western Europe, where particular emphasis is placed on the integration of theory and practice and the use of interactive methods that foster the development of students’own scientific perspectives. The article underscores that research activity plays a crucial role in individualizing the educational process and cultivating students' ability to conduct independent inquiry. It concludes that a well-organized research process is not only an effective means of developing professional competencies but also a vital tool in preparing specialists for lifelong self-directed learning.

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)0.000
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 score0.847
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.079
GPT teacher head0.455
Teacher spread0.376 · 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
Published2025
Admission routes1
Has abstractyes

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