Immersive technology as an umbrella concept consists of multiple emerging technologies including augmented reality (AR), virtual reality (VR), gaming, simulation, and 3D printing. Research has shown immersive technology provides unique learning opportunities for experiential learning, multiple perspectives, and knowledge transfer. Due to its role in influencing learners’ cognitive and affective processes, it is shown to have great potential in changing the educational landscape in the decades to come. However, there is a lack of general cognitive and affective theoretical framework to guide the diverse aspects of immersive technology research. In fact, lacking the cognitive and affective theoretical framework has begun to hamper the design and application of immersive technology in schools and related professional training. Cognitive and Affective Perspectives on Immersive Technology in Education is an essential research book that explores methods and implications for the design and implementation of upcoming immersive technologies in pedagogical and professional development settings. The book includes case studies that highlight the cognitive and affective processes in immersive technology as well as the successful applications of immersive technology in education. Featuring a wide range of topics such as curriculum design, K-12 education, and mobile learning, this book is ideal for academicians, educators, policymakers, curriculum developers, instructional designers, administrators, researchers, and students.

This monograph integrates theoretical perspectives on affect and learning with recent research in affective computing with an emphasis on building new learning technologies. The "new perspectives" come from the intersection of several research themes: -Basic research on emotion, cognition, and motivation applied to learning environments -Pedagogical and motivational strategies that are sensitive to affective and cognitive processes -Multimodal Human Computer Interfaces, with a focus on affect recognition and synthesis -Recent advances in affect-sensitive Intelligent Tutoring Systems -Novel methodologies to investigate affect and learning -Neuroscience research on emotions and learning

Establishing a student-centered classroom environment where learning puts students’ interests first is essential for middle school students to learn and thrive. Student success does not simply rely on instruction; it relies on external factors such as school and classroom climate, positive relationships with their teachers and other adults, and a strong sense of belonging with their peers. The young adolescent learner is at a turning point where the need for love, belonging, and acceptance is heightened. Research studies indicate that large percentages of students lack social-emotional competence and believe their teachers do not care about them. Social-emotional learning skills are vital for young adolescents, as are 21st century skills and competencies to prepare them for an information- and technology-driven world. Aligning Social-Emotional and 21st Century Learning in the Classroom: Emerging Research and Opportunities shows teachers practical ways to combine the skills that young adolescents need (social-emotional) and the 21st century skills that they learn to create a culture of success in their middle school classrooms. This book also provides examples of education technologies that teachers can use to promote 21st century learning in their classroom. Highlighting a wide range of topics such as communication skills, critical thinking, social media, and emotional intelligence, this book is crucial for teachers, school administrators, instructional designers, K-12 educators, curriculum developers, academicians, researchers, and students.

This book focuses on designing and being a designer of immersive education. It introduces readers to the human experiences within immersive learning environments and contributes research evidence on the effectiveness of immersive technologies in K-12 and post-secondary contexts. Through the chapters, illustrative contextual examples and vignettes demonstrate immersive learning in real-world educational practice. Readers will be equipped to design engaging and culturally relevant immersive experiences for learning in a post-COVID world. Immersive Education: Designing for Learning brings researchers, designers, and educators together to offer pedagogical strategies and design guidelines. The originality lies in integrating theoretical and practical knowledge to design meaningful immersive experiences, with attention to sustainability, community, and creativity. Valuable insights are provided to support students and teachers as immersive learning designers and storytellers.

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply. Presents the application of innovative AI techniques to collaborative learning activities Offers strategies to provide automatic and effective tutoring to students’ activities Offers methods to collect, analyze and correctly visualize learning data in educational environments

The Covid-19 pandemic has directly impacted the way teachers and learners worldwide teach and learn languages, forcing numerous educational activities in technologically-deprived contexts to stop altogether and those in technologically-rich environments to go online on an emergency basis. This volume provides a collection of theoretical and practical insights into the challenges and affordances faced globally during the pandemic and lessons learnt about the application of digital technologies for language teaching and learning. The chapters explore the vital role of technology in its various forms, including the internet, social media, CALL (Computer-Assisted Language Learning), MALL (Mobile Assisted Language Learning), TALL (Technology Assisted Language Learning) and TELL (Technology Enhanced Language Learning). Topics explored include the new avenues digital technology has opened up for language teachers and learners, options and challenges in applying technology in various contexts, and how the second language education industry could have been adversely impacted at the time of the pandemic without technological affordances. The contributions showcase studies from various geographical contexts, revealing how the global crisis was received and tackled differently in Australia, Hong Kong, Iran, Italy, Japan, New Zealand, the UAE, the UK and the USA.

The two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023. The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.