Investigating syntactic complexity and language-related error patterns in EFL students’ writing: corpus-based and epistemic network analyses

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