ESL Pre-service Teachers’ Perceptions on the Use of Paragraph Punch in Teaching Writing
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 development of Information and Communication Technologies (ICTs) provides broad opportunities in teaching English in ESL countries. Given the rapid development in computer applications, it is important to look at how these applications can be used in language teaching specifically for writing skills. The purpose of this paper is to investigate the pre-service teachers’ perceptions of a writing software called ‘Paragraph Punch’ as a tool for assisting beginner writers. This software is designed to help learners of English as a second language to develop and organise paragraphs in essay writing. This paper provides an overview of the development of computer-assisted language learning (CALL) over the years, and the background and features of Paragraph Punch. Data for this study have been gathered from third-year TESL students in a state university in Malaysia using a questionnaire survey to elicit their views on the use of Paragraph Punch as a potential writing tool. The descriptive analysis of the data showed that the (i) respondents have a positive view towards Paragraph Punch as a potential writing tool, (ii) Paragraph Punch is more suited for beginner writers, and (iii) the software can still be improved in terms of interactivity and layout to enhance writing. The findings have been discussed with regard to ESL writing.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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