Directions for Future Automated Analyses of L2 Written Texts
Xiaofei Lu · 2021
Previous research on automated analyses of written texts has focused on detecting lexical, collocational, and grammatical errors in written texts and on identifying linguistic features of written texts that are discriminative of proficiency levels or predictive of writing quality. This chapter starts with a brief description of the history of this line of research and the cumulative knowledge it has generated. It then proposes an agenda for future research on automated analyses of written texts. Three research questions are raised: 1) How can we improve the accuracy of natural language processing tools on texts produced by second language learners? 2) How can we automatically assess whether the linguistic features deployed in written texts are appropriate and effective for the rhetorical functions they are used to realize? 3) How can the capability to automatically identify form-function mappings and assess their appropriateness and effectiveness in written texts be utilized to inform and promote the teaching and learning of second language writing? Two empirical studies are suggested for each research question, each taking a different approach. The chapter concludes with a discussion of the critical importance of a functional turn in research on automated analyses of written texts.