Developing Research Paper Writing Programs for EFL/ESL Undergraduate Students Using Process Genre Approach
Bibliographic record
Abstract
Research Paper Writing (RPW) plays a key role in completingall research work. Poor writing could lead to the postponement of publications. Therefore, it is necessary todevelop a program of (RPW) to improve RPW ability for EFL/ESL writers, especially for undergraduate students in Higher Education (HE) institutions, which has caught less attention of curriculum developers so far. Therefore, this studyaims to determine the core components of (RPW) program perceived as essential for EFL/ESL undergraduate studentsusing Process Genre Approach (PGA) to develop a program of RPW. The Delphi Technique (DT) was used to validate those components through the interviews of experts including two boards of ten experienced and qualified lecturers of TESOL and curriculum studies in Can Tho University (CTU) in Vietnam and UniversitiSains Malaysia (USM). The results revealed that the corecomponents of RPW programfor EFL/ESL undergraduate students were determined and confirmed. This paper is therefore believed to make a great contribution to practical applications for RPW program developers, lecturers, undergraduate and postgraduate students in EFL/ESL contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".