Grammatical Errors in Iranian Academic Journal Abstracts: A Surface Strategy Taxonomy Analysis
محورهای موضوعی : Instructional Assessment and Evaluation including ELT
Marjan Abbasian
1
,
Roya Ranjbar Mohammadi Bonab
2
1 - Department of English Language, Cihan University, Erbil, Kurdistan Region, Iraq
2 - Department of English, Bon.C., Islamic Azad University, Bonab, Iran.
کلید واژه: Abstract, Academic Writing, EFL Researchers, Error Analysis, Grammatical Errors, Surface Strategy Taxonomy,
چکیده مقاله :
For non-native researchers, grammatical accuracy is essential for successful communication with the Academic community. Therefore, the aim of this study was to identify the types of errors found in the academic writings of Iranian researchers and their distribution. To this end, 50 abstracts were randomly selected from two Iranian academic journals to identify the possible grammatical errors. A qualitative descriptive approach was utilized to analyze these abstracts. To achieve this, Surface Strategy Taxonomy was used to detect and categorize errors into four groups: omission, addition, misformation, and misordering. As a result, 120 errors were identified in 10 abstracts out of the 50. The results showed that the most prevalent errors in academic writings were omissions, whereas additions were the least common. These findings demonstrated the importance of the Surface Strategy Taxonomy for analyzing error patterns in academic writing and highlighted the most frequent grammatical errors in several published articles. Researchers and journal editors can benefit from these results to enhance the linguistic quality of English-language abstracts.
For non-native researchers, grammatical accuracy is essential for successful communication with the Academic community. Therefore, the aim of this study was to identify the types of errors found in the academic writings of Iranian researchers and their distribution. To this end, 50 abstracts were randomly selected from two Iranian academic journals to identify the possible grammatical errors. A qualitative descriptive approach was utilized to analyze these abstracts. To achieve this, Surface Strategy Taxonomy was used to detect and categorize errors into four groups: omission, addition, misformation, and misordering. As a result, 120 errors were identified in 10 abstracts out of the 50. The results showed that the most prevalent errors in academic writings were omissions, whereas additions were the least common. These findings demonstrated the importance of the Surface Strategy Taxonomy for analyzing error patterns in academic writing and highlighted the most frequent grammatical errors in several published articles. Researchers and journal editors can benefit from these results to enhance the linguistic quality of English-language abstracts.
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