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Record W3015121760 · doi:10.3968/11420

Universal Reasons for Low Participation in Chinese and Western Undergraduate Classrooms

2019· article· en· W3015121760 on OpenAlexaffvenue
Keyuan Wang, Pingping Zhang, Zuo Bu-lei

Bibliographic record

VenueHigher education of social science · 2019
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChinaClass (philosophy)Mathematics educationPedagogyPsychologySociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study regards low classroom participation as a global issue and investigates the universal reasons for this problem shared by the undergraduate students in China and in the west. Participating in class discussions and asking questions are instrumental for effective learning. This study regards low classroom participation as the phenomenal where students do not ask or answer questions during a lesson. The research was conducted by combining profound experiences and insights developed as an undergraduate student in the University of Waterloo and a teaching assistant in Soochow University with the understanding of both Chinese academic articles and western academic articles about this topic. This study reveals the reason why Chinese and western undergraduate classrooms experience low classroom participation is that their stakeholders focus on the competing goals. This study defines the stakeholders as the instructors, students and the post-secondary institutions.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.035
GPT teacher head0.441
Teacher spread0.406 · 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
Published2019
Admission routes2
Has abstractyes

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