The main outcomes of the present research are the Text Classification Profile that includes the qualitative and quantitative description of linguistic characteristics pertinent in Intermediate and Advanced English reading texts and the L.A.S.T. Text Difficulty Index that makes possible the automatic classification of B2 and C1 English reading texts.

This book delineates a range of linguistic features that characterise the reading texts used at the B2 (Independent User) and C1 (Proficient User) levels of the Greek State Certificate of English Language Proficiency exams in order to help define text difficulty per level of competence. In addition, it examines whether specific reader variables influence test takers' perceptions of reading comprehension difficulty. The end product is a Text Classification Profile per level of competence and a formula for automatically estimating text difficulty and assigning levels to texts consistently and reliably in accordance with the purposes of the exam and its candidature-specific characteristics.

Autorentext

Trisevgeni Liontou holds a PhD in English Linguistics with specialization in Testing from the Faculty of English Studies at the National and Kapodistrian University of Athens (Greece). She holds a BA in English Language & Literature and an MA in Lexicography: Theory and Applications, both from the same faculty. She also holds a M.Sc. in Information Technology in Education from Reading University (UK). Her current research interests include theoretical and practical issues of reading comprehension performance, computational linguistics, online teaching practices and classroom-based assessment.

Inhalt
Contents: Text readability Automatic text classification Reading comprehension text complexity Text difficulty Text calibration Computational Linguistics Machine Learning systems Reading comprehension exam performance EFL reading comprehension EFL reading strategies Test-taker's perspective EFL test-taking strategies.