MétaCan
Menu
Back to cohort
Record W2035666816 · doi:10.5539/elt.v8n3p89

An Empirical Study on the Application of Process Approach in Non-English Majors’ Writing

2015· article· en· W2035666816 on OpenAlex
Dongmei Zhou

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnglish Language Teaching · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Writing processPsychologyProfessional writingMathematics educationCollege EnglishEmpirical researchProduct (mathematics)CognitionComputer science

Abstract

fetched live from OpenAlex

Process approach has been introduced to China for more than two decades. This approach which views writing as a recursive mental cognitive process is one of the most popular methods for teaching writing. It attaches more importance to a series of activities in the process of writing and the interaction among the student writers. Meanwhile, it emphasizes that writing should be learned in the writing process. This paper aims at exploring the influence of process approach on non-English majors. The author first made a questionnaire to investigate how the non-English majors accomplished their writing tasks and then did an experiment to explore the influence of process approach on their writing ability. The research findings show that non-English majors tend to employ the traditional product approach in writing and that process approach has positive influence on their writing ability. This study sheds light to non-English major teachers in teaching writing.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.333
Teacher spread0.301 · 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