Description

Book Synopsis
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.

Table of Contents
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.

Computational Text Analysis and Reading

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    A Hardback by Trisevgeni Liontou

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      Book details

      Publisher Peter Lang AG
      Published 29 December 2014
      ISBN-13 9783631656556
      978-3631656556
      ISBN-10 3631656556

      Description

      Book Synopsis
      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.

      Table of Contents
      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.

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