MétaCan
Menu
Back to cohort
Record W2771906454 · doi:10.5539/elt.v11n2p1

Perceptions of EFL College Students toward Collaborative Learning

2017· article· en· W2771906454 on OpenAlexvenueno aff
Yingling Chen

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPerceptionMathematics educationCollaborative learningCooperative learningCoachingCurriculumNarrativePedagogyQualitative researchTeaching method

Abstract

fetched live from OpenAlex

The purpose of the study was to understand the perceptions of EFL college students toward collaborative learning (CL). This qualitative research design used narrative approach since the study emphasized on each participant’s learning experiences with CL strategy. The data collection instruments for this research were consisted by interview questions. The researcher observed, took notes, and recorded Interview responses from each participant in order to understand their perceptions of collaborative learning. The finding of this study provides inspirations and motivation for English teachers to offer second language learners suitable curriculum and environment. Through collaborative learning, the results show that students quickly realize that they are able to solve problems as a group that they would not be able to solve as individuals. Students were satisfied by peer coaching, and peer review. Students worked together and brought effective strategies into the classroom activity.

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)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.413
Teacher spread0.389 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicInnovative Teaching and Learning MethodsFrench-language works237,207