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Artificial Intelligence + Education: Theory and Practice in Application Development is a work in the field of AI applications in education that combines cutting-edge theory with practical value for frontline educational practice.
Artificial Intelligence + Education: Theory and Practice in Application Development, authored by Dr. Feng Xiang, Associate Research Fellow at East China Normal University (ECNU), is presented as a crucial resource for educators navigating the complexities of digital and intelligent educational transformation. The book distinguishes itself by meticulously integrating advanced theoretical concepts with practical, actionable strategies pertinent to contemporary educational settings. Its primary objective is to equip frontline educators with the necessary insights and confidence to tackle the evolving landscape of AI-driven education effectively. This comprehensive approach ensures that both foundational understanding and real-world application are thoroughly covered, making it a valuable guide for educational practitioners and researchers alike.
Dr. Feng Xiang strategically employs Shannon's Communication Theory to offer a profound theoretical underpinning for understanding the new "encoding" and "decoding" interaction paradigms emerging within the context of human-AI collaboration in teaching. This theoretical framework sets the stage for the book's practical contributions, which involve an in-depth exploration and analysis of various typical educational software application scenarios. These include sophisticated techniques for learner modeling, advanced algorithms for adaptive learning path recommendations tailored to individual student needs, and the integration of affective computing to enhance personalized learning experiences. The book thus bridges abstract theory with tangible, implementable solutions for modern classrooms.
A significant feature of the book is its commitment to democratizing intelligent educational application development. It explicitly addresses the challenge of technical barriers by advocating for and detailing low-code and no-code development methodologies. Practical tools such as App Inventor and Orange are introduced and explained, demonstrating how educators and students, even without a background in computer science, can readily construct their own intelligent educational tools. However, the book does not shy away from critically examining the inherent risks and ethical dilemmas posed by advanced technology in education. It meticulously discusses pressing concerns such as potential data privacy breaches, the pervasive issue of algorithmic bias that can perpetuate inequalities, and the risk of neglecting fundamental humanistic values in an overly tech-centric environment. In light of the cognitive shifts induced by generative AI, the author posits that the development of future talent must undergo a comprehensive reorientation. This reorientation should prioritize the cultivation of "meta-knowledge," which refers to an understanding of how knowledge is acquired and used; "meta-thinking," encompassing critical reflection on one's thought processes; and "meta-awareness," involving a deeper understanding of one's own cognitive and emotional states. This holistic approach prepares individuals not just for technical proficiency but for thoughtful and ethical engagement with AI.
Ultimately, Dr. Feng Xiang's work transcends the realm of mere technical instruction, presenting itself as a visionary guide for comprehending and shaping the future trajectory of education. It offers an illuminating exploration into a future where human intelligence and artificial intelligence coexist and collaborate synergistically, laying out a pathway for educators to foster an environment of human-AI symbiosis that benefits learners comprehensively. The book encourages readers to look beyond immediate technological solutions and consider the broader societal and developmental implications of integrating AI into educational frameworks.
Dr. Feng Xiang brings a wealth of academic and practical experience to this publication. He earned his Ph.D. and completed postdoctoral research in computer applications, with affiliations at prestigious institutions like Shanghai Jiao Tong University and Alcatel Shanghai Bell. Currently, he serves as an Associate Research Fellow and master's supervisor within the Department of Education Information Technology at ECNU. His distinguished affiliations also include the Shanghai Engineering Research Center of Digital Education Equipment. Furthermore, Dr. Xiang plays a pivotal role as a committee member of the Educational Technology Subcommittee of the National Information Technology Standardization Technical Committee and holds the position of Deputy Secretary-General for the Professional Committee on Information Technology Education for Primary and Secondary Schools of the Chinese Society of Education (8th and 9th Councils). His research is focused on advanced educational informatization, particularly in areas such as AI applications in education, learning analytics, AI and programming education for K12 schools, and broader educational digitalization initiatives. His extensive contributions include leading and participating in over 30 national and provincial-level research projects, publishing more than 30 academic papers in highly regarded domestic and international journals (indexed by SCI, SSCI, EI, CSSCI), presenting at major international conferences, and securing three national invention patents along with more than ten software copyrights. This robust background underscores his authority and deep understanding of the subject matter presented in the book.