Comparing the Effects of Graphic Organisers and Conventional Method on Students’ Writing Skills
Bibliographic record
Abstract
Graphic Organisers help students make valuable connections by cataloguing and patterning ideas in writing. This study aims to investigate whether there is any difference in the overall mean writing scores between two groups: the Experimental Group (using Graphic Organisers) and the Control Group (using the Conventional Method) in the post-test. This study employs a quasi-experimental design, with quantitative data used for data analysis. Bubble maps and tree maps were the Graphic Organisers used by the Experimental Group in learning ESL writing skills. The study consisted of 120 Form Four students (16 years old) from two schools in the District of Hulu Langat, Selangor. The sample consisted of 60 students in each group (Experimental Group and Control Group). The experiment lasted for eight weeks. A pre-test was conducted prior to the intervention, and the post-test was carried out at the end of the experiment. The instruments (pre-test and post-test) consisted of three types of writing tasks: email writing, directed writing, and extended writing. ANCOVA was used to analyse the data obtained from the pre-test and post-test. The results showed that the Experimental Group significantly outperformed the Control Group in their overall writing performance, particularly in the areas of content, communicative achievement, organization, and language. The Control Group had difficulty in their overall and the four areas of writing because the Conventional Method did not help them improve their performance. This study has pivotal pedagogical implications as it demonstrates that Graphic Organisers (Bubble maps and Tree maps) facilitate students in their ESL writing.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".