Reimagining language education through intelligent technologies and computer assistance marks a shift in how we approach language learning in the digital age. With advancements in artificial intelligence and machine learning, there is potential to transform traditional methods into personalized educational experience. Intelligent systems now offer adaptive learning pathways that cater to individual proficiency levels, learning styles, and progress rates, making language education more accessible and effective. These technologies beg further exploration to effectively provide real-time feedback and support, creating a more engaging and responsive educational experience. Reimagining Intelligent Computer-Assisted Language Education explores fundamental aspects of educational technology to improve language teaching and learning. It reimagines educational practice for language teaching and learning through the integration of educational technology for making the language teaching and learning process more efficient and engaging, while improving learner performance and progress. This book covers topics such as artificial intelligence, language education, and academic writing, and is a useful resource for education professionals, language learners, computer engineers, academicians, scientists, and researchers.

Education stakeholders are at a crossroads where teaching and learning paths intersect with technologies fueled by emerging artificial intelligence. Educators who observe the residual effects of a global pandemic are left to wonder what creative technology solutions that sustain teaching and learning amidst mutating contagions should be retained, abandoned, or re-imagined to create sustainable pedagogy practices. In this book about e-learning, invited authors analyze the impacts of overarching issues facing educators across the globe to rethink how they deliver content and assess students' learning. A global community of scholars and researchers contributed twenty chapters to examine artificial intelligence, alternative assessments, education policy, creative technology, creative lesson plans, and emerging workforce trends to foster emerging paradigms in the post-pandemic era.

Artificial Intelligence Applications in Higher Education offers direct examples of how artificial intelligence systems can be applied in today’s higher education contexts. As the use of AI rapidly advances within colleges and universities worldwide, there is a pressing need to showcase the challenges, opportunities, and ethical considerations that are inherent in deploying these advanced computational tools. This book highlights the multifaceted roles of AI across teaching and learning, institutional administration, student data management, and beyond. Its collected case studies furnish actionable insights into enhancing academic institutions and addressing diverse learning priorities, such as motivation, engagement, feedback, and achievement goals. This valuable reference for researchers, designers, administrators, teaching faculty, and graduate students across various university programs offers fresh perspectives on generative AI, adaptive learning, intelligent tutoring systems, chatbots, predictive technologies, remote learning, and more.

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.

In a diverse society, the ability to cross communication barriers is critical to the success of any individual personally, professionally, and academically. With the constant acceleration of course programs and technology, educators are continually being challenged to develop and implement creative methods for engaging English-speaking and non-English-speaking learners. Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines the relationship between language education and technology and the potential for curriculum enhancements through the use of mobile technologies, flipped instruction, and language-learning software. This multi-volume book is geared toward educators, researchers, academics, linguists, and upper-level students seeking relevant research on the improvement of language education through the use of technology.

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]

With the recent growth of big data and the internet of things (IoT), individuals can now upload, retrieve, store, and collect massive amounts of information to help drive decisions and optimize processes. Due to this, a new age of predictive computing is taking place, and data can now be harnessed to predict unknown occurrences or probabilities based on data collected in real time. Predictive Intelligence Using Big Data and the Internet of Things highlights state-of-the-art research on predictive intelligence using big data, the IoT, and related areas to ensure quality assurance and compatible IoT systems. Featuring coverage on predictive application scenarios to discuss these breakthroughs in real-world settings and various methods, frameworks, algorithms, and security concerns for predictive intelligence, this book is ideally designed for academicians, researchers, advanced-level students, and technology developers.