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An Introduction to Artificial Intelligence in Education
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An Introduction to Artificial Intelligence in EducationНазвание: An Introduction to Artificial Intelligence in Education
Автор: Shengquan Yu, Yu Lu
Издательство: Springer
Год: 2021
Страниц: 205
Язык: английский
Формат: pdf (true)
Размер: 10.09 MB

This book systematically reviews a broad range of cases in education that utilize cutting-edge Artificial Intelligence (AI) technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds.

The purposes of this book are to review existing solutions of AI in education and to build bridges in schools, industries, and research institutions so as to jointly explore the possibility of transforming education with AI. To power education with AI, we are supposed to focus on both specific technologies and the real problems in educational practices. Generally speaking, there are three core components in applying AI in education, including computational power, intelligent algorithms, and real-world scenarios. Among them, knowledge of real-world application scenarios is critical to the success of AI in education. Therefore, this book aims to understand AI in education in terms of application scenarios and pressing issues in educational practices.

AI is not a single technology but a group of technologies that work together as a whole. This section begins with a general technology framework for the application of AI in education. Right after that, there is an overview of major AI technologies, including Machine Learning, cloud computing, knowledge graph, natural language processing (NLP), computer vision, human–computer interaction, virtual reality and augmented reality, intelligent control, and robots.

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