Effect of Using Mobile-based Online Assignments on Grammar Test Performance among Iranian Elementary EFL Learners
Year: 2025
Type: article
Abstract: This research aimed to investigate how Iranian students of English as a foreign language (EFL) utilise online mobile-based assignments to enhance their grammar skills and mindset. Thirty Iranian elementary EFL learners (male and female), ranging in age from eleven to sixteen, were chosen at random using convenience sampling to achieve this goal. Next, they were randomly assigned to one of two groups: either the experimental group (comprising 15 learners) or the control group (also comprising 15 learners). Primary English as a Foreign Language (EFL) students were randomly assigned to take the Oxford Quick Placement Test (OQPT). For one week, students in the experimental group used Live Worksheets, an online mobile grammar tool, to practice their comprehension of simple present, count, and non-count nouns; in contrast, students in the control group were given more conventional, pen-and-paper grammar activities. To gather data, two post-tests were administered: one immediately after therapy to assess immediate effects and another two weeks later to evaluate retention and transfer of knowledge. Using SPSS, we conducted t-tests on the gathered data, utilising both paired and independent samples. According to the results, using online mobile-based grammar assignments has a substantial effect on EFL learners’ ability to acquire grammatical skills. Additionally, the results indicated that participants generally considered mobile-based grammar assignments a good idea. Thus, this study’s findings could provide educators, policymakers, and researchers with a better understanding of how online, mobile-based assignments affect students' learning of grammar skills.
Authors: Maryam Zaman Sani, Shiela Kheirzadeh
Language: English
Topic: Mobile Learning in Education
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7009618491
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