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Record W3033628866 · doi:10.30775/kmes.49.2.69

A Comparative Study on Music Teacher Training Programs of Ontario, Quebec, British Columbia in Canada

2020· article· en· W3033628866 on OpenAlexaboutno aff
Sunmie Kim, Jheehyeon Kim, Young Joo Park

Bibliographic record

VenueKorean Music Education Society · 2020
Typearticle
Languageen
FieldComputer Science
TopicEducational Systems and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsCertificateTraining (meteorology)Music educationMathematics educationTeacher educationCertificate in EducationPedagogyMedical educationTraining systemDual (grammatical number)PsychologyPolitical scienceComputer scienceHigher educationGeographyMedicineEducationEducation policyArt

Abstract

fetched live from OpenAlex

본 연구는 캐나다의 온타리오, 퀘벡, 브리티시컬럼비아 주의 교사 자격제도와 음악교사 양성과정의 특징을 조사하고, 각 주를 대표하는 대학을 선정하여 음악교사 교육 프로그램을 분석하였다. 연구결과 각 주는 교육체계, 교사 자격 및 양성제도를 각각 다르게 운영하였으며, 교사자격증은 취득 요건의 충족 정도에 따라 다양한 종류로 발행하였다. 각 주를 대표하는 대학에서는 교과목 및 학점조건에 따라 초·중등 음악교사를 복수자격으로 준비할 수 있었으며, 다양한 주제의 강의와 현장중심의 연계성 있는 실습 프로그램을 동시형 및 복수학위 프로그램으로 운영하고 있었다. 본 연구는 캐나다를 대표하는 3개의 주에 대한 음악교사 양성과정에 대한 연구로서 그 의의를 두는 것은 물론 향후 우리나라 음악교사 양성과정 프로그램 개발 및 개편에 기초 자료로서 역할을 하길 기대한다.The purpose of this study was to compare the teacher qualification system and the characteristics of music teachers training of Ontario, Quebec, British Columbia in Canada as well as the music teacher programs of these representing universities. The result was that the teacher qualification system in each state was operated to obtain a teacher’s certificate and showed differences based on the education system, teacher qualifications, training systems, and types of teacher’s certificate. Each university provided music teacher programs for elementary and middle school with enough time for practical programs and projects in a concurrent program and a dual degree. This study expects to play a role as basic data for the training system of music education in Korea.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.071
GPT teacher head0.273
Teacher spread0.202 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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