This text explores fundamental issues relating to student literacies and instructor roles and practices within academic contexts. It offers a brief history of literacy theories and argues for "socioliterate" approaches to teaching and learning in which texts are viewed as primarily socially constructed. Central to socioliteracy, the concepts "genre" and "discourse community," are presented in detail. The author argues for roles for literacy practitioners in which they and their students conduct research and are involved in joint pedagogical endeavors. The final chapters are devoted to outlining how the views presented can be applied to a variety of classroom texts. Core curricular design principles are outlined, and three types of portfolio-based academic literacy classrooms are described.

Written by a leading researcher in the field, this fascinating examination of the relations between grammar, text, and discourse is designed to provoke critical discussion on key issues in discourse analysis which are not always clearly identified and examined. Written by a leading researcher in the field Continues the enquiry into discourse analysis that Zellig Harris initiated 50 years ago, which raised a number of problematic issues that have remained unresolved ever since Introduces the notion of pretext as an additional factor in the general interpretative process Focuses attention specifically on the work of critical discourse analysis (CDA) in light of the issues discussed

A substantial revision to a classroom favorite Explore the literature, history, and social context of the Old Testament/Hebrew Bible and their relevance for making sense of this ancient collection. This significant revision of a classroom standard pays particular attention to the original Mediterranean context--how it differs from modern Western culture--and its importance for interpretation. The significance of critical scholarly methods as well as the value of archaeology are likewise explored. Designed with the realities of the classroom in mind, it includes helpful illustrations, insets, and maps; study questions; a glossary; and indexes of subjects, personal and place names, and Scripture citations.

Text, ConText, and HyperText presents recent developments in three related and important areas of technical communication: the design of effective documentation; the impact of new technology and research on technical writing; and the training and management of technical writers.The contributors are all authorities drawn from universities and industry who are active in defining and analyzing the role of computing in technical documentation and the role of documentation in the development of computing technology. This first synthesis of their diverse but related research provides a unique conceptualization of the field of computers and writing and documentation.The book first examines techniques for writing online documentation and the value of usability testing. It presents new research into the impact of human factors in screen design and designing online help, and looks at the impact of desktop publishing on documentation, and at visual literacy and graphic design.Artificial intelligence and documentation processing are then addressed with discussion of data acquisition, automated formatting in expert systems, and document databases; the uses of HyperText in documentation; and the future of technical writing in this new environment.Text, ConText, and HyperText concludes by examining the training and management of documentation groups: how they "learn to write" in industry, management of large-scale documentation projects and their effect on product development; and the "two cultures" of engineering and documentation.Edward Barrett is a Lecturer in the Writing Program at MIT. Text, ConText, and HyperText is included in the Information Systems series, edited by Michael Lesk.

Well-respected Old Testament professor Victor Matthews identifies eight landmark stories that shaped Israel's identity.

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity