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Record W2886613867

A Study of Chinese International Students’ Classroom Participation in an International M.Ed. Program

2019· article· en· W2886613867 on OpenAlexaffabout
George Zhou, Zonrong Yu

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPsychologyPedagogyPersonalitySubject (documents)Character (mathematics)Mathematics educationSocial psychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

This study focuses on the classroom participation performance of Chinese international graduate students (CIGSs) at a Canadian university. Because CIGSs are coming from an education system that employs a teacher-centered pedagogy, they often struggle to acclimate to the student-centered pedagogy employed in Canadians schools. However, there is limited research on the subject. The current study explores how CIGSs participate in Canadian classrooms, what factors promote and inhibit their participation, and what approaches can help to improve their participation. The researcher recruited eight CIGSs and three of their instructors. Data were collected through one-on-one interviews. The analysis of the data showed that CIGSs struggle with eight key factors that shape their classroom participation: language proficiency, working experience, personality or character, part-time job commitments, self-motivation, personal interest, emotional state, and instructor’s likeableness. Therefore, it is critical for instructors to distinguish and observe why their students participate less, then adjust due to different situations to improve that participation level.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.047
GPT teacher head0.361
Teacher spread0.314 · 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
Published2019
Admission routes2
Has abstractyes

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