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| artificial intelligence in 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 in 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 in 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 in 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 in 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 in 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 in 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 in 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 in 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 in 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 in 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 in 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 in language learning: Artificial Intelligence and Inclusive Education Jeremy Knox, Yuchen Wang, Michael Gallagher, 2019-06-13 This book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologies and the necessity of developing inclusive teaching and learning. To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and ‘smart’ software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to ‘personalise’ learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by ‘big data’. |
| artificial intelligence in 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 in 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 in 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 in 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 in 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 in 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 in 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 in language learning: Emerging Concepts in Technology-Enhanced Language Teaching and Learning Zou, Bin, Thomas, Michael, Barr, David, Jia, Wen, 2022-01-21 For years, language teachers have increasingly been using technologies of all kinds, from computers to smartphones, to help their students learn. Current trends in TELTL (technology-enhanced language teaching and learning), such as artificial intelligence, virtual reality, augmented reality, gamification, and social networking, appear to represent major shifts in the digital language learning landscape. However, various applications of technology to mediate language learning may be informed by reflecting not only on the present but perhaps more importantly on relevant insights from past research and practice. Emerging Concepts in Technology-Enhanced Language Teaching and Learning explores the recent development of the new technologies for language teaching and learning to gain insights into and synergy of the theories, pedagogies, technological design, and evaluation of TELTL environments for comprehending the trends and strategies of the new digital era as well as investigate the possibility of future TELTL research direction. The book includes trends shaped by contemporary issues such as the COVID-19 pandemic. Covering topics such as digital education tools, L2 learnings, and sentiment analysis, this book serves as an essential resource for researchers, language teachers, educational software developers, administrators, IT consultants, technologists, professors, pre-service teachers, academicians, and students. |
| artificial intelligence in language learning: Artificial Intelligence Techniques in Language Learning Rex William Last, 1989 |
| artificial intelligence in 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 in 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 in 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 in language learning: Artificial Intelligence Applications in Distance Education Kose, Utku, 2014-07-31 This book seeks to examine the efforts made to bridge the gap between student and educator with computer applications through an in-depth discussion of applications employed to overcome the problems encountered during educational processes--Provided by publisher. |
| artificial intelligence in language learning: Artificial Intelligence and Deep Learning in Pathology Stanley Cohen, 2020-06-02 Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. - Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. - Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. - Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more. |
| artificial intelligence in language learning: Revolutionizing Education in the Age of AI and Machine Learning Habib, Maki K., 2019-09-15 Artificial Intelligence (AI) serves as a catalyst for transformation in the field of digital teaching and learning by introducing novel solutions to revolutionize all dimensions of the educational process, leading to individualized learning experiences, teachers playing a greater role as mentors, and the automation of all administrative processes linked to education. AI and machine learning are already contributing to and are expected to improve the quality of the educational process by providing advantages such as personalized and interactive tutoring with the ability to adjust the content and the learning pace of each individual student while assessing their performance and providing feedback. These shifts in the educational paradigm have a profound impact on the quality and the way we live, interact with each other, and define our values. Thus, there is a need for an earnest inquiry into the cultural repercussions of this phenomenon that extends beyond superficial analyses of AI-based applications in education. Revolutionizing Education in the Age of AI and Machine Learning addresses the need for a scholarly exploration of the cultural and social impacts of the rapid expansion of artificial intelligence in the field of education including potential consequences these impacts could have on culture, social relations, and values. The content within this publication covers such topics as AI and tutoring, role of teachers, physical education and sports, interactive E-learning and virtual laboratories, adaptive curricula development, support critical thinking, and augmented intelligence and it is designed for educators, curriculum developers, instructional designers, educational software developers, education consultants, academicians, administrators, researchers, and professionals. |
| artificial intelligence in 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 in 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 in 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 in language learning: Expanding Global Horizons Through Technology Enhanced Language Learning Yun Wen, Yi-ju Wu, Grace Qi, Siao-Cing Guo, J. Michael Spector, Shobhana Chelliah, Kinshuk, Yu-Ju Lan, 2021-06-15 This book uncovers the important issues in language learning and teaching in the intelligent, digital era. “Social connectivity” is a contemporary style of learning and living. By engaging in the connectivity of physical and digital worlds, how essential parts of language learning and teaching can be achieved? How can the advanced technologies, such as virtual reality and artificial intelligent, be used to solve the problems encountered by language learners? To answer the above mentioned question, plenty of inspiring studies are included in the book. It is a platform of exchange for researchers, educators, and practitioners on the theory and/or application of state-of-the-art uses of technology to enhance language learning. |
| artificial intelligence in 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 in language learning: Toward Human-Level Artificial Intelligence Philip C. Jackson, Jr, 2019-11-13 How can human-level artificial intelligence be achieved? What are the potential consequences? This book describes a research approach toward achieving human-level AI, combining a doctoral thesis and research papers by the author. The research approach, called TalaMind, involves developing an AI system that uses a 'natural language of thought' based on the unconstrained syntax of a language such as English; designing the system as a collection of concepts that can create and modify concepts to behave intelligently in an environment; and using methods from cognitive linguistics for multiple levels of mental representation. Proposing a design-inspection alternative to the Turing Test, these pages discuss 'higher-level mentalities' of human intelligence, which include natural language understanding, higher-level forms of learning and reasoning, imagination, and consciousness. Dr. Jackson gives a comprehensive review of other research, addresses theoretical objections to the proposed approach and to achieving human-level AI in principle, and describes a prototype system that illustrates the potential of the approach. This book discusses economic risks and benefits of AI, considers how to ensure that human-level AI and superintelligence will be beneficial for humanity, and gives reasons why human-level AI may be necessary for humanity's survival and prosperity. |
| artificial intelligence in 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 in language learning: Application of Artificial Intelligence to Assessment Hong Jiao, Robert W. Lissitz, 2020-03-01 The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices. |
| artificial intelligence in language learning: Machine Learning R.S. Michalski, J.G. Carbonell, T.M. Mitchell, 2013-04-17 The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed interest has spawned many new research projects and resulted in an increase in related scientific activities. In the summer of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon University in Pittsburgh. In the same year, three consecutive issues of the Inter national Journal of Policy Analysis and Information Systems were specially devoted to machine learning (No. 2, 3 and 4, 1980). In the spring of 1981, a special issue of the SIGART Newsletter No. 76 reviewed current research projects in the field. . This book contains tutorial overviews and research papers representative of contemporary trends in the area of machine learning as viewed from an artificial intelligence perspective. As the first available text on this subject, it is intended to fulfill several needs. |
| artificial intelligence in language learning: Artificial Intelligence in Schools Varun Arora, 2021-12-30 Artificial Intelligence in Schools is the first book to explore the use of Artificial Intelligence (AI) as a tool to enhance K–12 instruction and administration. Every industry and sector will be drastically affected by the presence of artificial intelligence, and schooling is no exception! Written for the in-service community—leaders, administrators, coaches, and teachers alike—this is your one-stop opportunity to make sure you don’t fall behind the fast pace and promising innovations of today’s most advanced learning technology. Author Varun Arora presents AI as a problem-solving tool for teaching and learning, exploring its potential and application in real-world school contexts and in the language of educators. Covering curriculum development, feedback and scoring, student empowerment, behavioral and classroom management, college readiness, and more, the book is full of novel insights and concrete, strategic takeaways. |
| artificial intelligence in 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 in language learning: Artificial Intelligence and Machine Learning Fundamentals Zsolt Nagy, 2018-12-12 Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python). |
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 …
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 …
