Inspector : The Tool For Automated Assessment Of Learner Text Complexity

EFL methodology has always recognized the importance of giving student learners of foreign languages regular and quick feedback on student speech production, both written and oral, but over the past two decades there appeared various tools ensuring the provision of automated instant feedback. The presented paper offers such a tool that focuses on measuring text complexity, which will hopefully translate into reasonable feedback about the level of language proficiency when taking into account those text features that are significant for Russian learners of English. The application provides students with advice on how to improve the weaker aspects of the evaluated essay and underlines the relevant linguistic features of the text - for example, the number of adjectival clauses. We point out what text features are more relevant for the assessment of the essays written in English by Russian students. We analyzed 3440 texts from Russian Error-Annotated English Learner Corpus, and for each of them we calculated the text criteria values. Then we used the methods of machine learning and statistical analysis to predict the grade that could be received for the essay