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Record W2970758304 · doi:10.5539/elt.v12n10p1

Individual, Pair and Group Writing Activity: A Case Study of Undergraduate EFL Student Writing

2019· article· en· W2970758304 on OpenAlexvenueno aff
Chittima Kaweera, Rattana Yawiloeng, Khomkrit Tachom

Bibliographic record

VenueEnglish Language Teaching · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyGroup workMathematics educationPedagogyMedical education

Abstract

fetched live from OpenAlex

The present study aimed to compare between individual and collaborative writing (pair and group of four) activities of 72 EFL students. The subjects of the study were assigned to produce their tasks by these three activities. Qualitative method was employed by using interview of nine students drawn from students with different levels of English proficiency (low, fair and high). It was focused on their perspectives towards skills practiced during working on written tasks: writing, thinking, participation, communication as well as their satisfaction of these activities. The results from content analysis demonstrated that overall the students practiced participation skills when doing individual and pair work. The students practiced writing skills when joining group work. With regard to the students’ satisfaction, low proficiency students in low group were likely to enjoy coauthoring activity either pair or group work. Their satisfaction seemed to increase according to the number of group members. This is important for writing teachers to provide this activity for low proficiency students as this may lower the students’ anxiety and foster their self-confidence, compared with completing tasks individually. On the contrary high proficiency students seemed to enjoy writing alone and were fairly satisfied group work. These students were likely to be more confident when performing the tasks individually or experienced some problems that might impede working collaboratively.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.282
Teacher spread0.260 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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