Marianne Nikolov

Students’ writing proficiency is measured through holistic and analytical ratings in writing assessment; however, recent studies suggest that measurement of syntactic complexity in second language writing research has become an effective measure of writing proficiency. Within this paradigm, we investigated how automated measurement of syntactic complexity helped distinguish the writing proficiency of students from two Higher Education institutions. In addition, we also examined language-related errors in students’ writing to further indicate the differences in the error patterns of the two groups. Data was drawn from a corpus of 1,391 sentences, comprising 58 texts produced by first-year undergraduate students from Myanmar and Hungary. Automated tools were used to measure the syntactic complexity of students’ writing. We performed a corpus-based analysis, focusing on syntactic complexity, while language-related error patterns in writing were investigated through an epistemic network approach. Findings suggested that the Myanmar students tended to write longer essays comprising simpler sentences, whereas the Hungarian students preferred shorter texts with more complex sentences. Most complexity measures were also found to distinguish the texts produced by the two groups: length of production units, sentence complexity, and subordination indices. An examination of the language-related error patterns revealed statistically significant differences in the error patterns in student writing: errors were found to be more prevalent in Myanmar students’ essays. Implications for enhancing teaching L2 writing in educational contexts are discussed.