Book | Brief | |
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This book includes a collection of expanded papers from the 2019 Sino-German Symposium on AI-supported educational technologies, which was held in Wuhan, China, March, 2019. The contributors are distinguished researchers from computer science and learning science.
The contributions are organized in four sections: (1) Overviews and systematic perspectives , (2) Example Systems, (3) Algorithms, and (4) Insights gained from empirical studies. For example, different data mining and machine learning methods to quantify different profiles of a learner in different learning situations (including interaction patterns, cognitive modes, knowledge skills, interests and emotions etc.) as well as connections to measurements in psychology and learning sciences are discussed in the chapters. |
Why? - build a strategic, smart and strong analytics capability to transform your institution and ensure a future proof competitive advantage. This type of transformation impacts top-line growth—such as those related to institutional transformation and data utilization—as well as productivity and performance. This discipline includes: Agile and rapid prototyping. Analytics capability assessment and transformation. Remember the conviction: #Analyticship:#BI,#ML,#AI,#BigData,#Analytics,#HiEd:
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Saturday, July 25, 2020
Advances in Analytics for Learning and Teaching
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