It is often the case - perhaps more often than not - that new ideas arrive long before there is the me ans to clothe and deli ver them. We can think ofLeonardo da Vinci's drawings of helicopters and submarines among many other examples. Computer-Assisted Learning (CAL) is an example of an idea which has had a particularly long gestation. As I will illustrate early in the book, the principles of CAL were really first discovered by Socrates. As a formal method of teaching, the Socratic method disappeared for over two millennia until the 1950s. It was then revived in the form ofProgrammed Learning (PL) which resulted from the researches ofB. F. Skinner at Harvard University. Even then, PL was premature. In the 1950s and 60s, methods were devised, such as teaching machines and various sorts ofPL text books, and there was a mushrooming of PL publishing at that time. For a complex of reason- economic, logistical and technical-PL also largely disappeared from the mid- 60s, although it continued in a few specialized areas ofteaching and industrial training. However, during the same period, PL quietly transformed itselfinto CAL. But the computerized form was not capable of mass dissemination until recently hecause personal microcomputers did not have sufficient internal memory sizes. That situation has now changed very dramatically and 128K microcomputers are becoming cheap and widely available. Cheap memory chips of256K and 1024K cannot be far away, either.

This book deals with "Computer Aided Writing", CAW for short. The contents of that is a sector of Knowledge based technics and Knowledge Management. The role of Knowledge Management in social media, education and Industry 4.0 is out of question. More important is the expectation of combining Knowledge Management and Cognitive Technology, which needs more and more new innovations in this field to face recent problems in social and technological areas. The book is intended to provide an overview of the state of research in this field, show the extent to which computer assistance in writing is already being used and present current research contributions. After a brief introduction into the history of writing and the tools that were created, the current developments are examined on the basis of a formal writing model. Tools such as word processing and content management systems will be discussed in detail. The special form of writing, "journalism", is used to examine the effects of Computer Aided Writing. We dedicate a separate chapter to the topic of research, since it is of essential importance in the writing process. With Knowledge Discovery from Text (KDT) and recommendation systems we enter the field of Knowledge Management in the context of Computer Aided Writing. Finally, we will look at methods for automated text generation before giving a final outlook on future developments.

This volume includes insights into, and reflections about, different perspectives of the relationship between L2 writing and technology with particular emphasis on the writing process, development of linguistic skills, development of writing competencies and literacy, educational approaches to writing, as well as task creation and assessmetn in diverse writing contexts. In this regards, the chapters incorporate the recognition of a connection between the fields of second language writing, pedagogy, second language acquisition, and CALL emphasizing the need for technological innovation and integration to be built upon a strong pedagogical and research-based foundation.

This book broadly covers a scope of the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fifth International Conference of Artificial Intelligence, Medical Engineering, and Education (AIMEE2021), which took place at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1–3 October 2021. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineering to increase the effectiveness of medical diagnosing and treatment. In digital artificial intelligence systems, scientists endeavour to reproduce the innate intellectual abilities of humans and other organisms, and the in-depth study of genetic systems and inherited biological processes can provide new approaches to create more and more effective artificial intelligence methods. Topics of the included papers concern thematic materials in the following spheres: mathematics and biomathematics; medical approaches; technological and educational approaches. The book is a compilation of cutting-edge research papers in the field, covering a comprehensive range of subjects that are relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students who are interested in artificial intelligence, bioinformatics systems, also their expanding applications. The intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.

A complete update to a classic, respected resource Invaluable reference, supplying a comprehensive overview on how to undertake and present research

This fascinating book explores machines as authors of fiction, past, present, and future. For centuries, writers have dreamed of mechanical storytellers. We can now build these devices. What will be the impact on society of AI programs that generate original stories to entertain and persuade? What can we learn about human creativity from probing how they work? In Story Machines, two pioneers of creative artificial intelligence explore the design and impact of AI story generators. The book covers three themes: language generators that compose coherent text, storyworlds with believable characters, and AI models of human storytellers. Providing examples of story machines through the ages, it covers the history, recent developments, and future implications of automated story generation. Anyone with an interest in story writing will gain a new perspective on what it means to be a creative writer, what parts of creativity can be mechanized, and what is essentially human. Story Machines is for those who have ever wondered what makes a good story, why stories are important to us, and what the future holds for storytelling.

Presents poems, stories, dialogues, essays, and aphorisms created by a computer using the Racter program

After centuries of rethinking education and learning, the current theory is based on technology's approach to and effect on the planned interaction between knolwedge trainers and trainees. Demonstrates, through the exposure of successful cases in online education and training, the necessity of the human factor, particualarly in teaching/tutoring roles, for ensuring the development of quality and excellent learning activities. The didactic patterns derived from these experiences and methodologies will provide a basis for a more powerful and efficient new generation of technology-based learning solutions.

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research. Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text Use linear regression to predict the number of page views for the top 1,000 websites Learn optimization techniques by attempting to break a simple letter cipher Compare and contrast U.S. Senators statistically, based on their voting records Build a “whom to follow” recommendation system from Twitter data

A landmark volume that explores the interconnected nature of technologies and rhetorical practice Rhetorical Machines addresses new approaches to studying computational processes within the growing field of digital rhetoric. While computational code is often seen as value-neutral and mechanical, this volume explores the underlying, and often unexamined, modes of persuasion this code engages. In so doing, it argues that computation is in fact rife with the values of those who create it and thus has powerful ethical and moral implications. From Socrates’s critique of writing in Plato’s Phaedrus to emerging new media and internet culture, the scholars assembled here provide insight into how computation and rhetoric work together to produce social and cultural effects. This multidisciplinary volume features contributions from scholar-practitioners across the fields of rhetoric, computer science, and writing studies. It is divided into four main sections: “Emergent Machines” examines how technologies and algorithms are framed and entangled in rhetorical processes, “Operational Codes” explores how computational processes are used to achieve rhetorical ends, “Ethical Decisions and Moral Protocols” considers the ethical implications involved in designing software and that software’s impact on computational culture, and the final section includes two scholars’ responses to the preceding chapters. Three of the sections are prefaced by brief conversations with chatbots (autonomous computational agents) addressing some of the primary questions raised in each section. At the heart of these essays is a call for emerging and established scholars in a vast array of fields to reach interdisciplinary understandings of human-machine interactions. This innovative work will be valuable to scholars and students in a variety of disciplines, including but not limited to rhetoric, computer science, writing studies, and the digital humanities.