Artificial Intelligence Supported Educational Technologies

AI in education, examined from multiple angles

Artificial Intelligence Supported Educational Technologies gathers research emerging from the 2019 Sino-German Symposium on AI-supported educational technologies. The result is an edited volume that moves beyond broad claims about AI and education and instead looks closely at the systems, methods, and educational questions that shape the field.

Because the book brings together work from computer science and learning science, it offers a useful cross-disciplinary view of how AI is being applied in teaching and learning. The chapters address learning analytics, adaptive instructional systems, recommendation and prediction methods, multimodal sensing, and ethical issues in AI-supported education.

Organized for readers who want both overview and depth

The book is arranged in four sections:

• Overviews — survey-style and conceptual discussions of learning analytics, feedback, and collaborative teaching support
• Systems — AI-supported instructional and monitoring systems, including attention and sensor-based learning support
• Algorithms — technical approaches such as prediction, recommendation, and knowledge representation
• Empirical Studies — applied research on self-regulated learning, adaptive question-answering, emotion-based systems, and innovation in higher education

This structure gives the volume a strong reference-book feel: readers can move from broad perspectives into concrete designs and then into field-tested studies.

What the volume brings into view

The edited chapters reflect a field that is still actively defining its best practices. Alongside technical advances, the book pays attention to questions of educational fit, human-computer interaction, and the responsibilities that come with collecting and interpreting learner data. That balance makes it especially useful for readers who want to understand not only what AI can do in education, but also how those tools are being studied and evaluated.

Well suited to a professional and academic audience

This is a strong match for researchers, graduate students, instructional designers, and education professionals interested in artificial intelligence in education, learning analytics, intelligent tutoring systems, and data-informed teaching. As an edited scholarly volume, it works best as a reference for focused reading rather than a single-sitting narrative.

Published by Springer as part of the Advances in Analytics for Learning and Teaching series, this title offers a clear snapshot of where AI-supported educational technologies stood at the time of publication—and why the topic continues to matter.