JOURNAL ARTICLE

Error Analysis of Grammar Usage Among Non-Native English Speakers

Noorkholis Luthfil HakimNoor Adil Hakim

Year: 2025 Journal:   International Journal of Social Science and Human Research Vol: 08 (08)

Abstract

This research investigates the common grammatical errors made by non-native English speakers, focusing on female students in their third and fourth years at the College of Education for Girls, University of Kufa. The research aims to identify the most frequent grammar errors, analyze the underlying causes, and suggest effective teaching strategies to minimize these errors. Using a mixed-methods approach, the study combines qualitative and quantitative analyses of students' written essays and comprehension tests. The findings reveal that the most prevalent errors include incorrect preposition usage (95.7% in comprehension tests and 92.9% in production tests), verb tense errors (84.3% in production tests), and unnecessary article usage (60% in production tests). Other common errors involve subject-verb agreement, misuse of auxiliary verbs, and incorrect noun forms. The study attributes these errors to factors such as native language interference (particularly from Arabic), the complexity of English grammar rules, overgeneralization, and limited exposure to English outside the classroom. The research concludes that targeted teaching strategies, increased exposure to English, and a focus on error analysis are essential for improving grammatical accuracy among EFL learners. These findings align with previous studies, such as those by Susi Damaiyanti (2021) and Santi Kunnur (2024), which also identified article and verb tense errors as common challenges for EFL learners. The study provides valuable insights for educators and curriculum developers to enhance language teaching practices and foster a more effective learning environment.

Keywords:
Linguistics Grammar Error analysis Natural language processing Computer science English grammar Psychology Artificial intelligence Mathematics Philosophy

Metrics

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Cited By
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FWCI (Field Weighted Citation Impact)
3
Refs
0.14
Citation Normalized Percentile
Is in top 1%
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Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Subtitles and Audiovisual Media
Social Sciences →  Arts and Humanities →  Language and Linguistics
EFL/ESL Teaching and Learning
Social Sciences →  Arts and Humanities →  Language and Linguistics

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