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Record W4405134044 · doi:10.5539/jel.v14n2p259

A Case Study on Writing Difficulties of Five Chinese English Majors

2024· article· en· W4405134044 on OpenAlexvenueno aff
Jing Lan

Bibliographic record

VenueJournal of Education and Learning · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Research and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationLinguisticsPedagogy

Abstract

fetched live from OpenAlex

Writing ability is an essential skill for college students to improve their school performance and complete their academic writing tasks. Proficient English writing skills are also highly advantageous for their future career prospects and personal growth. However, many English learners face difficulties in various aspects of English writing. The study investigated the writing difficulties encountered by five Chinese undergraduates majoring in English; and discussed the primary causes of these writing difficulties. The research instruments included two writing tasks and the retrospective interviews. Thematic analysis was employed for data analysis. The findings showed that their writing difficulties are mainly manifested in constructing writing content, coherence and cohesion, insufficient linguistic knowledge, difficulties in applying writing theories to writing practices, and difficulties caused by time constraints. The participants also shared their perspectives about the English writing courses, emphasizing the addition of more genres other than argumentative writing, actual writing practice over objective examinations, and the need for improvement of the textbooks.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0030.002
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 head0.031
GPT teacher head0.386
Teacher spread0.355 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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