Investigating interactive language use by L2 writers in a large-scale online written interaction task


Yılmaz S., Çimrin M., Sarıcaoğlu Aygan A.

21st EALTA (European Association for Language Testing and Assessment), Salzburg, Avusturya, 26 - 31 Mayıs 2025, ss.41, (Özet Bildiri)

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: Salzburg
  • Basıldığı Ülke: Avusturya
  • Sayfa Sayıları: ss.41
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Online posts are increasingly used in both academic and professional settings, yet writing tasks based on this emerging genre remain underutilized by test developers (Kremmel et al., 2023), with few exceptions, such as TOEFL's online discussion task and e-TEP's online written interaction task (Türkiye's Electronic Test of Proficiency). As these tasks emerge in standardized tests, understanding how test-takers demonstrate successful written interaction becomes essential. This study investigates interpersonal metadiscourse in responses to e-TEPs Online Written Interaction Task, which requires test takers to effectively contribute to an online thread through accurate information synthesis and appropriate stance expression. Using Hyland's (2005) metadiscourse model, we specifically analyzed 270 responses across three score levels (low, intermediate, high) and qualitatively contextualized linguistic markers following Sun and Jiang (2024). We also investigated the relationship between interactive language use and writing quality based on the e-TEP rubric's content dimension. Our results revealed differences in engagement with the thread and interactive language use across the score levels. High-

scoring responses were characterized by the more varied use of interactive discourse markers, while low-scoring responses often included unclear stance expression and weaker synthesis of information from the thread. We found a strong relationship between the frequency and diversity of interactional discourse markers and higher scores in the content dimension. Our findings highlight the importance of these features in predicting performance success in online written interaction tasks and contribute to the assessment of the evolving construct of L2 writing in digital contexts.