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Record W7132964817

Chinese students' participation in asynchronous educational computer conferencing

2005· dissertation· W7132964817 on OpenAlexaboutno aff
Naxin Zhao

Bibliographic record

VenueTSpace · 2005
Typedissertation
Language
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationMandarin ChinesePerceptionComputer-mediated communicationCultural diversityTeleconferenceVideoconferencingGraduate students
DOInot available

Abstract

fetched live from OpenAlex

Research has inadequately explored Chinese students' participation in asynchronous computer conferencing in Western universities. Systematic theory on these issues is likewise lacking. This study explores the influences of cultural factors on Chinese students' participation in asynchronous educational computer conferencing in Western schools. It involved six Chinese graduate students in a large urban Canadian university. Semi-structured interviews in Mandarin elicited these students' perceptions about participation in on-line courses, on-line instructors' roles, sense of on-line community and its effects on learning, and the cultural factors involved. These findings prompt some suggestions for Chinese students and Western instructors in on-line courses. They also suggest some directions for future research. Generally, the participants had positive attitude towards on-line courses. They found on-line courses compatible with some of their Chinese cultural patterns of teaching, learning and social interaction, while capable of countering cultural aspects (e.g. language, reticence) that posed problems to their 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.480
Teacher spread0.451 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2005
Admission routes1
Has abstractyes

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