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| artificial intelligence language learning: AI in Language Teaching, Learning, and Assessment Pan, Fang, 2024-02-12 The introduction of Artificial Intelligence (AI) has ignited a fervent academic discourse. AI's role is as both a powerful ally and a potential adversary in education. For instance, ChatGPT is a generative AI which mimics human conversation with impressive precision. Its capabilities span the educational spectrum, from answering questions and generating essays to composing music and coding. Yet, as with any innovation, its advent has sparked a spirited academic dialogue. AI in Language Teaching, Learning, and Assessment seeks to address these concerns with rigor and thoughtfulness. It explores the undeniable drawbacks of AI in language education and offers strategic insights into their prevention. It scrutinizes the resources and safeguards required to ensure the ethical and secure integration of AI in academic settings. This book lays out the multifaceted benefits of incorporating AI into language teaching, learning, and assessment. Its chapters dissect the transformative impact of AI on pedagogy, teaching materials, assessment methodologies, applied linguistics, and the broader landscape of language education development. This book is a valuable resource for language learners, educators, researchers, and scholars alike. It beckons to those who are keen on exploring and implementing AI in education, as well as AI developers and experts seeking to bridge the chasm between technology and language education. |
| artificial intelligence language learning: Virtual Reality, Artificial Intelligence, and Language Learning Ulf Schütze, 2024-06-15 It is intriguing and challenging to learn a language by diving into the worlds of Virtual Reality (3-D environments, avatars, games) and Artificial Intelligence (chatbots, agents). What are the issues and benefits of these technological innovations? Taking readers on a journey through the brain, this book explains how VR and AI may foster and sustain connectivity between language faculties, the senses/emotions, working and long-term memory, and attention. With the speed of technological innovation increasing, cognitive demand as well as aspects of intrinsic motivation are analyzed, charted, and discussed, as these may become essential for future development of language learning experiences. This volume should be of interest to instructors, researchers, and students of languages and linguistics, cognitive psychology, and computer science. |
| artificial intelligence language learning: Artificial Intelligence in Second Language Learning Marina Dodigovic, 2005-10-07 This volume argues that adults can learn English as a second language if their typical errors are corrected systematically and in line with their preferred style of learning. The remedy designed for this purpose relies on artificial intelligence. The book describes original research which demonstrates the success of this approach. |
| artificial intelligence language learning: Statistical Language Learning Eugene Charniak, 1996 This text introduces statistical language processing techniques--word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation--along with the underlying mathematics and chapter exercises. |
| artificial intelligence language learning: Transforming the Language Teaching Experience in the Age of AI Kartal, Galip, 2023-09-11 Transforming the Language Teaching Experience in the Age of AI, edited by Galip Kartal, is a vital resource that addresses the evolving challenges in language education due to technological advancements. This book offers a comprehensive analysis of AI's impact on language education, providing innovative research, practical insights, and interdisciplinary collaboration opportunities. From AI-driven language learning methods to ethical considerations, the book equips educators, policymakers, and researchers with valuable insights to shape effective educational strategies and policies, inspiring the adoption of innovative approaches that harness AI's potential to enhance language teaching. Through successful case studies and forward-thinking perspectives, Transforming the Language Teaching Experience in the Age of AI envisions a future where AI-driven methodologies redefine global language education. This publication not only facilitates a deeper understanding of AI's role in language education but also fosters a shared vision among educators and researchers, promoting a transformative and collaborative learning experience for students worldwide. |
| artificial intelligence language learning: Language Learning with Technology Lindsay Miller, Junjie Gavin Wu, 2021-08-31 This book is about language learning with technology, offering readers theoretical insights as well as practical case studies with a focus on Asia and Asian students. Although technology is rapidly advancing and most, if not all, students are already using technology in their everyday lives, traditional teaching/learning practices still exist throughout Asia. This book provides examples, written by representative educators, from a variety of countries/regions and contexts where technology has successfully been used to enhance language learning. In addition to some everyday examples of using technology: Wikipedia, PowerPoint, Google Docs and YouTube, the book also offers the readers an insight into the future possible uses of advanced technology: Augmented Reality, Virtual Reality, Artificial Intelligence and Eye Tracking. The book presents illustrations of how teachers can, and perhaps should, be open to integrating some form of technology into in-class learning or using it to supplement out-of-class activities. |
| artificial intelligence language learning: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| artificial intelligence language learning: Artificial Intelligence in Second Language Learning Marina Dodigovic, 2005-01-01 The aim of this volume is to cater to a wide range of audiences associated with the field of Computer Assisted Language Learning (CALL). In a true cross-disciplinary fashion it brings together instances of research in second language acquisition, language awareness, computer assisted language learning, artificial intelligence and natural language processing. It is intended for language teachers, students of applied linguistics and language engineering as well as for applied linguists in general.--BOOK JACKET. |
| artificial intelligence language learning: The Natural Language for Artificial Intelligence Dioneia Motta Monte-Serrat, Carlo Cattani, 2021-04-06 The Natural Language for Artificial Intelligence presents natural language as the next frontier because it identifies something that is most sought after by scholars: The universal structure of language that gives rise to the respective universal algorithm. In short, this book presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind that, at the same time, interprets the context of reality. It is a non-static approach to natural language, which is defined as a complex system whose parts interact with the ability to generate a new quality of behavior and whose dynamic elements are mapped in order to be understood and executed by intelligent systems, guiding the paradigms of cognitive computing. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language, leading to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed, to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine. |
| artificial intelligence language learning: Artificial Intelligence in Education Rosemary Luckin, Kenneth R. Koedinger, Jim E. Greer, 2007 The nature of technology has changed since Artificial Intelligence in Education (AIED) was conceptualized as a research community and Interactive Learning Environments were initially developed. |
| artificial intelligence language learning: Linguistics for the Age of AI Marjorie Mcshane, Sergei Nirenburg, 2021-03-02 A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language. |
| artificial intelligence language learning: Essentials of Artificial Intelligence Matt Ginsberg, 2012-12-02 Since its publication, Essentials of Artificial Intelligence has been adopted at numerous universities and colleges offering introductory AI courses at the graduate and undergraduate levels. Based on the author's course at Stanford University, the book is an integrated, cohesive introduction to the field. The author has a fresh, entertaining writing style that combines clear presentations with humor and AI anecdotes. At the same time, as an active AI researcher, he presents the material authoritatively and with insight that reflects a contemporary, first hand understanding of the field. Pedagogically designed, this book offers a range of exercises and examples. |
| artificial intelligence language learning: Artificial Intelligence in Education Wayne Holmes, Maya Bialik, Charles Fadel, 2019-02-28 The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book Artificial Intelligence in Education, Promises and Implications for Teaching and Learning by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant. --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue.I commend this book to anyone concerned with the future of education in a digital world. --Marc Durando, Executive Director, European Schoolnet |
| artificial intelligence language learning: Machine Learning for Kids Dale Lane, 2021-01-19 A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+ |
| artificial intelligence language learning: Artificial Intelligence Techniques in Language Learning Rex William Last, 1989 |
| artificial intelligence language learning: Deep Natural Language Processing and AI Applications for Industry 5.0 Tanwar, Poonam, Saxena, Arti, Priya, C., 2021-06-25 To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students. |
| artificial intelligence language learning: Introduction to Machine Learning Shan-e-Fatima, 2023-09-25 With the use of machine learning (ML), which is a form of artificial intelligence (AI), software programmers may predict outcomes more accurately without having to be explicitly instructed to do so. In order to forecast new output values, machine learning algorithms use historical data as input. Machine learning is frequently used in recommendation engines. Business process automation (BPA), predictive maintenance, spam filtering, malware threat detection, and fraud detection are a few additional common uses. Machine learning is significant because it aids in the development of new goods and provides businesses with a picture of trends in consumer behavior and operational business patterns. For many businesses, machine learning has emerged as a key competitive differentiation. The fundamental methods of machine learning are covered in the current book. |
| artificial intelligence language learning: Future Hype Robert B. Seidensticker, 2006 |
| artificial intelligence language learning: Technologies, Artificial Intelligence and the Future of Learning Post-COVID-19 Allam Hamdan, Aboul Ella Hassanien, Timothy Mescon, Bahaaeddin Alareeni, 2022-02-17 This book aims to assess the experience of education during COVID-19 pandemic and explore the future of application of technologies and artificial intelligence in education. Education delivery requires the support of new technologies such as artificial intelligence (AI), the Internet of Things (IoT), big data, and machine learning to fight and aspire to new diseases. The academic community and those interested in education agree that education after the corona pandemic will not be the same as before. The book also questions the role of accreditation bodies (e.g., AACSB, etc.) to ensure the effectiveness and efficiency of technology tools in achieving distinguished education in times of crisis. |
| artificial intelligence language learning: Lifelong Machine Learning, Second Edition Zhiyuan Sun, Bing Leno da Silva, 2022-06-01 Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields. |
| artificial intelligence language learning: The Intelligence Revolution Bernard Marr, 2020 Harness the transformative power of artificial intelligence and integrate it in your business strategy to deliver intelligent products, services and business processes that put you above the rest. |
| artificial intelligence language learning: Multidisciplinary Functions of Blockchain Technology in AI and IoT Applications Niaz Chowdhury, Ganesh Chandra Deka, 2020-10 This edited book deliberates upon prospects of blockchain technology for facilitating the analysis and acquisition of big data using AI and IoT devices in various application domains-- |
| artificial intelligence language learning: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| artificial intelligence language learning: Applications of Machine Learning and Artificial Intelligence in Education Seda Khadimally, 2021 Focuses on the parameters of remote learning, machine learning, deep learning, and artificial intelligence under 21st-century learning and instructional contexts. Topics covered include data coding and social networking technology. |
| artificial intelligence language learning: Cross-Cultural Perspectives on Technology-Enhanced Language Learning Tafazoli, Dara, Gomez Parra, M. Elena, Huertas-Abril, Cristina A., 2018-06-08 The ability to effectively communicate with individuals from different linguistic and cultural backgrounds is an invaluable asset. Learning a second language proves useful as students navigate the culturally diverse world; however, studying a second language can be difficult for learners who are not immersed in the real and natural environment of the foreign language. Also, changes in education and advancements in information and communication technologies pose a number of challenges for implementing and maintaining sound practices within technology-enhanced language learning (TELL). Cross-Cultural Perspectives on Technology-Enhanced Language Learning provides information on educational technologies that enable language learners to have access to authentic and useful language resources. Readers will explore themes such as language pedagogy, how specific and universal cultural contexts influence audio-visual media used in technology-enhanced language learning (TELL), and the use of English video games to promote foreign language learning. This book is a valuable resource for academicians, education practitioners, advanced-level students, and school administrators seeking to improve language learning through technology-based resources. |
| artificial intelligence language learning: New Technologies in Language Learning A. Zettersten, 2014-06-28 This is the first book to provide a comprehensive survey of the use of new technologies in language learning. In order to explain how new technologies open up possibilities for language learning, numerous practical experiments made with various electronic media are analysed. They include the use of microcomputers, videotex (viewdata), teletext, video and videodiscs. In addition, artificial intelligence, synthetic speech, robots, distance education, language testing as well communicative training and the problem of accuracy and fluency are dealt with. |
| artificial intelligence language learning: AI and education Miao, Fengchun, Holmes, Wayne, Ronghuai Huang, Hui Zhang, UNESCO, 2021-04-08 Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed] |
| artificial intelligence language learning: Multilingual Multimedia Masoud Yazdani, 1993 Includes chapters that provide a survey of approaches to developing multimedia software and relevant multilingual issues; design considerations for a visual language and how it might be developed for maximum ease of use. |
| artificial intelligence language learning: New Technological Applications for Foreign and Second Language Learning and Teaching Kruk, Mariusz, Peterson, Mark, 2020-03-13 Population diversity is becoming more prevalent globally with increasing immigration, emigration, and refugee placement. These circumstances increase the likelihood that a child will be raised speaking a different language in the home than the common language used in each country. This necessitates the development of comprehensive strategies that promote second language learning through the adoption of new technological advancements. New Technological Applications for Foreign and Second Language Learning and Teaching is a scholarly publication that explores how the latest technologies have the potential to engage foreign and second language learners both within and outside the language classroom and to facilitate language learning and teaching in the target language. Highlighting a range of topics such as learning analytics, digital games, and telecollaboration, this book is ideal for teachers, instructional designers, curriculum developers, IT consultants, educational software developers, language learning specialists, academicians, administrators, professionals, researchers, and students. |
| artificial intelligence language learning: Artificial Intelligence Charles Jennings, 2019-05-08 Self-learning machines called AIs are popping up all around us. They’re real, and really important. They’re affecting our lives—as workers, consumers, investors, citizens, patients and students. AIs bring huge promise, but also existential risk. The biggest risk isn’t killer robots—it’s the renegade leaders, despots, and unrestrained hackers everywhere we should worry about. Charles Jennings’ insightful new book, Artificial Intelligence: The Rise of the Lightspeed Learners presents sides of AI most people have never even considered before. That surprises are a main product of AIs. That AI cybersecurity is much more critical than traditional IT security. That, as Vladimir Putin put it, “the country that leads in AI will control the world.” Jennings blends insights into Silicon Valley, Washington D.C., and Beijing with insider AI stories, irreverent humor and strong opinions. He explores the global AI ecosystem from Cambridge to Beijing; and provides a stark assessment of AI activity in China—where he lived for two years working with senior government officials. He claims that the U.S. and China are in an AI horserace that will be the most important technology contest ever, with the outcome still very much in doubt. Consisting of stories, musings, interviews, and more, it provides a timely and accessible explanation of AI and its key issues to the general reading public. |
| artificial intelligence language learning: Recent Developments in Technology-Enhanced and Computer-Assisted Language Learning Zou, Bin, Thomas, Michael, 2019-12-06 The pace at which technology changes has created unique challenges in the integration of such technologies into language teaching and learning. Innovative pedagogies and strategies must be developed that adapt to these changes and accommodate future technological changes. Recent Developments in Technology-Enhanced and Computer-Assisted Language Learning is an essential research publication that focuses on technological influences on language education and applications of technology in language learning courses including foreign and second language learning. Featuring an array of topics such as artificial intelligence, teacher preparation, and distance learning, this book is ideal for teachers, language instructors, IT specialists, instructional designers, curriculum developers, researchers, education professionals, academicians, administrators, practitioners, and students. |
| artificial intelligence language learning: Natural Language Processing Yue Zhang, Zhiyang Teng, 2021-01-07 This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework. |
| artificial intelligence language learning: Natural Language Processing in Artificial Intelligence Brojo Kishore Mishra, Raghvendra Kumar, 2020-11-01 This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP. |
| artificial intelligence language learning: Artificial Intelligence and Machine Learning for Business for Non-Engineers Stephan S. Jones, Frank M. Groom, 2019-11-22 The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI’s current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry. |
| artificial intelligence language learning: Ultralearning Scott H. Young, 2019-08-06 Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success. |
| artificial intelligence language learning: Active Learning Burr Chen, 2022-05-31 The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose queries, usually in the form of unlabeled data instances to be labeled by an oracle (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or query selection frameworks. We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations |
| artificial intelligence language learning: Natural Language Annotation for Machine Learning James Pustejovsky, Amber Stubbs, 2013 Includes bibliographical references (p. 305-315) and index. |
| artificial intelligence language learning: Digital Pedagogies and the Transformation of Language Education Montebello, Matthew, 2021-05-14 Education has undergone numerous radical changes as the digital era has transformed the way we as humans communicate, inform ourselves, purchase goods, and perform other mundane chores at home and at work. Social media is one of those phenomena that has affected not only society at large but has heavily influenced educational processes around the world. The demand for and availability of networked educational services have also increased, enabling online education to gain popularity and become an internationally accessible option. Furthermore, universities and other private higher educational institutions embrace digital technology and have adopted the new learning medium as they realize the prospects of having the world’s population as a potential source of revenue. A related phenomenon has been the proliferation of massive open online courses (MOOCs). These have changed the ways in which learners interact with educational institutions, professors, and with each other. At the same time, the upsurge in digital education has raised issues with language as online learners from all over the world and from a plethora of cultures and foreign languages have found themselves challenged to take full advantage and optimally benefit from the same educational media and resources that English-speaking counterparts have tapped into. Digital Pedagogies and the Transformation of Language Education will answer questions of how to optimize language learning in such a defining new era and what the educational, sociological, and technological dimensions of radical change are. The book will explore the different challenges and the multitude of opportunities that new and transformative pedagogies have enabled. Beyond teaching/learning practices being presented, this book also focuses on how learners will adjust to the technology and the readiness of practitioners to psychologically adjust to the changing and demanding media technology has unleashed. The chapters provide international experiences and perspectives on the impact of e-educational technologies on student experience, success, learning, and comprehension in the realm of language learning specifically. This book is essential for educational technologists, online instructional designers, education policymakers and administrators, curriculum developers, practitioners, stakeholders, researchers, academicians, and students who are interested in digital language pedagogies. |
| artificial intelligence language learning: Fostering Communication and Learning With Underutilized Technologies in Higher Education Ali, Mohammed Banu, Wood-Harper, Trevor, 2020-09-04 Higher education is undergoing radical changes with the arrival of emerging technology that can facilitate better teaching and learning experiences. However, with a lack of technical awareness, technophobia, and security and trust issues, there are several barriers to the uptake of emerging technologies. As a result, many of these new technologies have been overlooked or underutilized. In the information systems and higher education domains, there exists a need to explore underutilized technologies in higher education that can foster communication and learning. Fostering Communication and Learning With Underutilized Technologies in Higher Education is a critical reference source that provides contemporary theories in the area of technology-driven communication and learning in higher education. The book offers new knowledge about educational technologies and explores such themes as artificial intelligence, digital learning platforms, gamification tools, and interactive exhibits. The target audience includes researchers, academicians, practitioners, and students who are working or have a keen interest in information systems, learning technologies, and technology-led teaching and learning. Moreover, the book provides an understanding and support to higher education practitioners, faculty, educational board members, technology vendors and firms, and the Ministry of Education. |
| artificial intelligence language learning: Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence Gogate, Lakshmi, 2013-02-28 The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research. |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
artificial - Wiktionary, the free dictionary
6 days ago · artificial (comparative more artificial, superlative most artificial) Man-made; made by humans; of artifice. The flowers were artificial, and he thought them rather tacky. An artificial …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
Artificial Intelligence Is Not Intelligent - The Atlantic
Jun 6, 2025 · The good news is that nothing about this is inevitable: According to a study released in April by the Pew Research Center, although 56 percent of “AI experts” think artificial …
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is synthetic.
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
artificial - Wiktionary, the free dictionary
6 days ago · artificial (comparative more artificial, superlative most artificial) Man-made; made by humans; of artifice. The flowers were artificial, and he thought them rather tacky. An artificial …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real version, …
Artificial Intelligence Is Not Intelligent - The Atlantic
Jun 6, 2025 · The good news is that nothing about this is inevitable: According to a study released in April by the Pew Research Center, although 56 percent of “AI experts” think artificial …
