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Record W4393344511 · doi:10.5539/elt.v17n4p62

The Teaching Design of Introducing Chinese Culture into College English Classroom Teaching with Experiential Teaching Method

2024· article· en· W4393344511 on OpenAlexvenueno aff
Ni Panxige, Wang Min-xia

Bibliographic record

VenueEnglish Language Teaching · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Work Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsExperiential learningTeaching methodMathematics educationCollege EnglishTeaching and learning centerPedagogyTeaching englishPsychology

Abstract

fetched live from OpenAlex

This study discusses the application value and necessity of experiential teaching method in English classroom teaching in Chinese universities. Based on experiential teaching method, this study focuses on 40 non-English major sophomore students from a university in China. The translation section of the College English Test Band 4 (CET-4) is used as cultural input material to design specific teaching activities for introducing Chinese culture in English classroom teaching at the university level. Combining specific teaching designs, the advantages of applying experiential teaching method in university English classrooms are proposed, such as optimizing and innovating teaching modes, creating diverse teaching situations for teaching, exercising students’ language proficiency, enriching and optimizing teaching content, and breaking the traditional teaching mode of ‘spoon-feeding’ and increasing the frequency of interaction between teachers and students.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.006
GPT teacher head0.325
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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