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Record W2572915688 · doi:10.5539/elt.v10n2p94

An Empirical Study on the Application of Cooperative Learning to Comprehensive English Classes in a Chinese Independent College

2017· article· en· W2572915688 on OpenAlexvenueno aff
Ji Meng

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationCooperative learningCompetence (human resources)Class (philosophy)Empirical researchCollege EnglishTest (biology)Control (management)Teaching methodPedagogySocial psychologyComputer science

Abstract

fetched live from OpenAlex

This research investigated a comparison between the effect of cooperative learning and lecture teaching on Comprehensive English classes in a Chinese Independent College. An empirical study for two semesters was carried out in the forms of pretest, posttest, questionnaire and interviews. While control class was taught in the conventional way, experiment class was instructed based on cooperative base groups with positive interdependence structured on purpose. Compared with traditional instructions, cooperative learning as pedagogy can improve students’ performance on course exams, but not necessarily their language competence as shown in national English competency tests taken before and after the experiement. Test results also indicate students from experiment class who excelled in competency test outnumbered those from control class, revealing that cooperative learning has positive impacts especially on students at a relatively higher academic level. Questionaire results show that students are most inclined to agree they have more chances to practice the language in a cooperative environment.

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)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.039
GPT teacher head0.432
Teacher spread0.393 · 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.

Study designQualitative
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

Citations6
Published2017
Admission routes1
Has abstractyes

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