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"Inasmuch as the utility of technical manuals is influenced to a marked extent by their reading difficulty or readability, the Automated Readability Index was devised to provide an easy, automated method of collecting data from which textual material can be evaluated in terms of readability. Whereas most readability formulas include separate factors related to (1) word difficulty and (2) sentence difficulty, the Automated Readability Index provides for the mechanical tabulation of the required data on passages as they are typed on a standard typewriter. Impulses from the typewriter activate counters which record the number of letters, words and sentences contained in the passage. From this, the average word length and average sentence length are computed. Appropriate weightings of these factors result in an index reflecting the readability of the passage. This index is in close agreement with other indexes of readability."--Abstract.
Coh-Metrix is among the broadest and most sophisticated automated textual assessment tools available today. Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides. Part I of the book focuses on the theoretical perspectives that led to the development of Coh-Metrix, its measures, and empirical work that has been conducted using this approach. Part II shifts to the practical arena, describing how to use Coh-Metrix and how to analyze, interpret, and describe results. Coh-Metrix opens the door to a new paradigm of research that coordinates studies of language, corpus analysis, computational linguistics, education, and cognitive science. This tool empowers anyone with an interest in text to pursue a wide array of previously unanswerable research questions.
Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.
The purpose of this book is to introduce the research on readability, defined here as reading ease. The first part of the book covers how people read. A series of national literacy surveys show that the average person in the U.S. and most other countries are adults of limited reading skills. For example, the average adult in the U.S. reads at the 9th-grade level, with nearly half reading below that level. The second part of this work covers the efforts made to match texts with readers. The research shows that more readable texts increase comprehension, retention, reading speed, and persistence. Other studies show how factors in both the reader and the text contribute to reading ease. Finally, the work follows the development of the readability formulas and the controversies that surrounded them. George Klare's Readability Ranking Test is appended. An index is included. (Contains 14 figures and 9 tables.).
A comprehensive manual for pre- and in-service ESL and EFL educators, this frontline text balances insights from current reading theory and research with highly practical, field-tested strategies for teaching and assessing L2 reading in secondary and post-secondary contexts. Teaching Readers of English: provides a through yet accessible survey of L2 reading theory and research addresses the unique cognitive and socioeducational challenges encountered by L2 readers covers the features of L2 texts that teachers of reading must understand acquaints readers with methods for designing reading courses, selecting curricular materials, and planning instruction explores the essential role of systematic vocabulary development in teaching L2 literacy includes practical methods for assessing L2 students’ proficiency, achievement, and progress in the classroom. Pedagogical features in each chapter include questions for reflection, further reading and resources, reflection and review questions, and application activities.
What your reader wants; Ten principles of clear writing; Causes and cures.
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