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Artificial Intelligence Applications in Higher Education: Theories, Ethics, and Case Studies for Universities

Artificial Intelligence Applications in Higher Education: Theories, Ethics, and Case Studies for Universities - Helen Crompton

Artificial Intelligence Applications in Higher Education: Theories, Ethics, and Case Studies for Universities

Artificial Intelligence Applications in Higher Education offers direct examples of how artificial intelligence systems can be applied in today's higher education contexts.


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.

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Artificial Intelligence Applications in Higher Education offers direct examples of how artificial intelligence systems can be applied in today's higher education contexts.


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.

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