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Record W4406714234 · doi:10.32370/ia_2024_04_8

Methodological Principles of Diagnostic Level Testing for the Instrumental Preparation of Students-Violinists

2025· article· en· W4406714234 on OpenAlexvenueno aff
Олеся Ігорівна Пилип

Bibliographic record

VenueIntellectual Archive · 2025
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyInstrumental musicMedical educationMedicineArtLiterature

Abstract

fetched live from OpenAlex

The article presents the content-structural characteristics of the instrumental learning the bachelors of Music in Violin in the institutions of higher education, which is reflected in the unity of four components: motivational-volitional; information- technological; communicative-regulatory; implementing-creative. Developed a criterion apparatus for conducting a diagnostic experiment and scientifically substantiated; outlined its two stages. The first stage is a mass survey of respondents in the form of a questionnaire and testing to determine their levels of violinists' motivation forming regarding the mastery of a high level of instrumental training and the degree of mastery of theoretical competencies. The second stage is laboratory diagnostics of the level of violin students’ instrumental training according to the indicator "quality of complex operation of special skills", during which a methodology is proposed and named "Analysis of the content of pedagogical documentation". According to the indicators "the degree of mastery of communicative skills and the ability to self-regulate in the performance process", it is proposed to use the "Situational Crisis" methodology. Recommended for the indicator “ability to engage in independent musical research activities” to check the level of development of the specified quality using the "My performing ideal" method. Proposed for the indicator "desire to create one’s own interpretation of a musical work" to use the “Performing image" method.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.531
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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 head0.194
GPT teacher head0.398
Teacher spread0.204 · 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 designOther design
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
Published2025
Admission routes1
Has abstractyes

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