The Impact of Rotation Model on Minimizing Inflectional Morphemes Errors in English Writing
A Comparative Study of Error Analysis
Bibliographic Data
| ID | 21807185 |
|---|---|
| Authors | Mohammad Usama (0000-0003-2395-8441), Sohaib Alam (0000-0002-9972-9357, Prince Sattam Bin Abdulaziz University), Shashikanta Tarai (0000-0003-2457-2866), Sameena Banu (0000-0001-8718-5148, Prince Sattam Bin Abdulaziz University) |
| Year | 2024 |
| Volume | 14 |
| Issue | 2 |
| Pages | 307-318 |
| Publication date | 2024-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Theory and Practice in Language Studies (JOURNAL) |
| Journal identifiers | ISSN: 1799-2591 • E-ISSN: 2053-0692 |
| Publisher | Academy Publication (PUBLISHER • GB) |
| DOI | 10.17507/tpls.1402.01 |
| OpenAlex | W4391477063 |
| Language | EN |
| Citations received | 3 |
| References cited | 20 |
The study aims to analyze 12th-grade students’ writing errors related to inflectional morphemes. In addition, the research measures efficacy of the Rotation Model (RM) and the Grammar Translation Method (GTM) in minimizing writing errors among learners of English. Comparative studies are rare to find the effectiveness of two teaching models in the context of error analysis. Eighty-two samples were taken into consideration for randomize sampling. The present research is divided into two groups; the experimental group, consisting of 41 participants, provided with instruction via RM, and the control group, also comprising 41 individuals, being taught through GTM. Pre and post-test treatment data were collected and analyzed with the help of SPSS 22. The results revealed common errors with inflectional morphemes among both groups. Additionally, the mean values for each type of error were significantly minimized due to the post-instruction of RM compared to the GTM. The study’s findings largely devoted to pedagogical improvement among ESL learners’ writing. The findings are reviewed concerning future research directions and instructional strategies
Error Analysis · Linguistics · Morpheme · Natural language processing · Computer Science · Educational Methods and Media Use · Mathematics · Philosophy · Applied Mathematics · Artificial Intelligence
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| Citations per year | 3 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |