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Artificial intelligence (AI) is changing the world as we know it. Recent advances are enabling people, companies, and governments to envision and experiment with new methods of interacting with computers and modifying how virtual and physical processes are carried out. One of the fields in which this transformation is taking place is education. After years of witnessing the incorporation of technological innovations into learning/teaching processes, we can currently observe many new research works involving AI. Moreover, there has been increasing interest in this research area after the COVID-19 pandemic, driven toward fostering digital education. Among recent research in this field, AI applications have been applied to enhance educational experiences, studies have considered the interaction between AI and humans while learning, analyses of educational data have been conducted, including using machine learning techniques, and proposals have been presented for new paradigms mediated by intelligent agents. This book, entitled “AI in Education”, aims to highlight recent research in the field of AI and education. The included works discuss new advances in methods, applications, and procedures to enhance educational processes via artificial intelligence and its subfields (machine learning, neural networks, deep learning, cognitive computing, natural language processing, computer vision, etc.).

Information technology industries --- performance measurement --- key performance indicators --- educational data mining --- institutes performance --- governance --- educational mining --- machine learning --- artificial intelligence --- decision support systems --- systematic literature review --- learning styles --- hybrid university teaching --- e-behaviour --- big five personality --- student performance --- plagiarism --- ethics --- academic dishonesty --- online education --- higher education --- AS&P model --- Pakistan

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This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Information technology industries --- machine learning --- deep learning --- image processing --- classification --- tea --- fermentation --- automated image coding --- data collection methods --- interdisciplinary learning theory --- research methods --- systematic literature review --- visitor use management --- image classification --- multi-instance learning --- divergence --- dissimilarity --- bag-to-class --- Kullback–Leibler --- segment-based temporal modeling --- two-stream network --- action recognition --- internet of things --- detection --- dataset --- plant disease recognition --- image segmentation --- aphid --- Aphoidea --- lemon --- breast cancer mammogram dataset --- ultrasound breast cancer scans --- BI-RADS --- clinical data --- machine learning --- deep learning --- image processing --- classification --- tea --- fermentation --- automated image coding --- data collection methods --- interdisciplinary learning theory --- research methods --- systematic literature review --- visitor use management --- image classification --- multi-instance learning --- divergence --- dissimilarity --- bag-to-class --- Kullback–Leibler --- segment-based temporal modeling --- two-stream network --- action recognition --- internet of things --- detection --- dataset --- plant disease recognition --- image segmentation --- aphid --- Aphoidea --- lemon --- breast cancer mammogram dataset --- ultrasound breast cancer scans --- BI-RADS --- clinical data

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This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

machine learning --- deep learning --- image processing --- classification --- tea --- fermentation --- automated image coding --- data collection methods --- interdisciplinary learning theory --- research methods --- systematic literature review --- visitor use management --- image classification --- multi-instance learning --- divergence --- dissimilarity --- bag-to-class --- Kullback–Leibler --- segment-based temporal modeling --- two-stream network --- action recognition --- internet of things --- detection --- dataset --- plant disease recognition --- image segmentation --- aphid --- Aphoidea --- lemon --- breast cancer mammogram dataset --- ultrasound breast cancer scans --- BI-RADS --- clinical data

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This book, entitled “Gamification and Advanced Technology to Enhance Motivation in Education”, contains an editorial and a collection of ten research articles that highlight the use of gamification and other advanced technologies as powerful tools for motivation during learning. Motivation is the driving force behind many human activities, especially learning. Motivated students are ready to make a significant mental effort and use deeper and more effective learning strategies. Numerous studies indicate that playing promotes learning, since when fun pervades the learning process, motivation increases and tension is reduced. Therefore, games can be very powerful tools in the improvement of learning processes from three different and complementary perspectives: as tools for teaching content or skills, as an object of the learning project itself and as a philosophy to be taken into account when designing the training process. Each contributions presented in this book falls into one of these categories; that is to say, they all deal with the use of games or related technologies, and they all study how playing enhances motivation in education.

Information technology industries --- gamification --- active methodologies --- secondary education --- evaluation rubric --- evaluation criteria --- Thomas W. Malone --- game --- design --- Sebastian Deterding --- Nick Pelling --- learning by doing --- serious games --- game design --- human computer-interaction --- HCI education --- entrepreneurship education --- FLIGBY --- Flow --- positive psychology --- higher education --- MOOC --- fun --- social networks --- virtual learning communities --- video games --- collaborative learning --- education --- teacher --- attitudes --- primary education --- technology --- ICT --- Likert scale --- game elements --- online learning --- MOOCs --- empirical studies --- systematic literature review --- university --- serious video games --- game-based learning --- professors --- video games design --- knowledge --- skills training --- digital technologies --- automated learning --- serious game --- usability --- game engagement --- virtual reality --- rubric --- capability approach --- capacity building --- enabling tools --- mental images --- motivation

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This book, entitled “Gamification and Advanced Technology to Enhance Motivation in Education”, contains an editorial and a collection of ten research articles that highlight the use of gamification and other advanced technologies as powerful tools for motivation during learning. Motivation is the driving force behind many human activities, especially learning. Motivated students are ready to make a significant mental effort and use deeper and more effective learning strategies. Numerous studies indicate that playing promotes learning, since when fun pervades the learning process, motivation increases and tension is reduced. Therefore, games can be very powerful tools in the improvement of learning processes from three different and complementary perspectives: as tools for teaching content or skills, as an object of the learning project itself and as a philosophy to be taken into account when designing the training process. Each contributions presented in this book falls into one of these categories; that is to say, they all deal with the use of games or related technologies, and they all study how playing enhances motivation in education.

gamification --- active methodologies --- secondary education --- evaluation rubric --- evaluation criteria --- Thomas W. Malone --- game --- design --- Sebastian Deterding --- Nick Pelling --- learning by doing --- serious games --- game design --- human computer-interaction --- HCI education --- entrepreneurship education --- FLIGBY --- Flow --- positive psychology --- higher education --- MOOC --- fun --- social networks --- virtual learning communities --- video games --- collaborative learning --- education --- teacher --- attitudes --- primary education --- technology --- ICT --- Likert scale --- game elements --- online learning --- MOOCs --- empirical studies --- systematic literature review --- university --- serious video games --- game-based learning --- professors --- video games design --- knowledge --- skills training --- digital technologies --- automated learning --- serious game --- usability --- game engagement --- virtual reality --- rubric --- capability approach --- capacity building --- enabling tools --- mental images --- motivation