Factors Influencing Students’ Performance in Second Language Writing Skills
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.
Bibliographic record
Abstract
The ability to articulate ideas, convey information, and engage stakeholders through written mediums has become a vital competency. This study delves into the Factors influencing Engineering students’ performance in second language writing skills at two private higher education institutions. The research aims to analyze the issues surrounding students’ writing skills comprehensively. To conduct this investigation, a quantitative methodology was employed. A sample of 247 students was randomly selected, and their opinions were gathered through a survey questionnaire. The findings of the research revealed that the majority of the students struggle to master the art of effective writing. The results show that the majority of students exhibited poor writing performance because of the errors that occurred such as: prepositions, articles, spelling, concord, verb tense, word choice, structure, organization, omission, repetition and cohesion. To enhance their writing skills, students need more chances to practice writing in structured ways. Activities that require crafting complete sentences, experimenting with sentence variation, and incorporating fresh vocabulary will help. In addition, constructive feedback is crucial for pinpointing mistakes and offering strategies for improvement, guiding students toward more polished writing. Reading and writing are deeply connected, so teachers shold increase students' exposure to diverse reading materials which will help them better understand grammar, sentence structure, and vocabulary.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it