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Record W3048400351 · doi:10.5430/ijhe.v9n7p279

Formation of Students’ Competence of Tertiary Educational Institutions by Practical Training Aids

2020· article· en· W3048400351 on OpenAlex

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

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldComputer Science
TopicInnovative Educational Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsTertiary institutionMathematics educationCompetence (human resources)Higher educationMedical educationPsychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

The purpose of the scientific article is aimed at studying the features of students’ competenceformation at tertiary educational institutions by practical training aids. To reveal the purpose of a scientific article, methods of theoretical analysis and synthesis have been used (to study the theoretical framework of students’ competence formation at tertiary educational institutions by practical training aids) and methods of comparison, grouping and concretization (to analyze and assess the practical results of students’ competence formation at tertiary educational institutions by practical training aids). The practical results of the study are presented through: the results of assessing students’ knowledge of Mathematics, Reading and Science, according to the PISA program; dynamics and structure of the number of students enrolled in tertiary education; the proportion of undergraduate students in% of the population at the age of 20-24 years old. According to the results of the PISA program, developed by the Organization for Economic Cooperation and Development (OECD), it has been found that Austria, Belgium and Germany have the highest average scores in Mathematics, Reading and Science, compared to the average scores in OECD countries. It has been established that in Ukraine the average students’score in Mathematics in 2018 is lower than the average score in OECD countries by 21 points, in Reading - by 36 points, and in Science - by 20 points. In the course of the study it hasbeenestablished that currentlyeducators use the following practical training aids for the formation of students’ competence in the learning process, namely: introduction of a modular academic program in the educational process, providing the necessary level of theoretical basis, implementation of introductory,educational, training, undergraduate practices, work experience internship in the educational process of students’ training, application of information, innovation and interactive technologies in the educational process, teaching and training of students in accordance with the requirements of the labor market and employers, ensuring cooperation between tertiary educational institutionsin the framework of student exchange programs.

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)0.001
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 score0.760
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.075
GPT teacher head0.406
Teacher spread0.331 · 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