This book addresses computer-supported collaborative learning (also known as CSCL) particularly within a tertiary education environment. It includes articles on theory and practice in this area including topics such as: how can groups with shared goals work collaboratively using the new technologies? What problems can be expected, and what are the benefits? In what ways does online group work differ from face-to-face group work? And what implications are there for both educators and students seeking to work in this area?

This book constitutes the thoroughly refereed proceedings of the 11th International Conference on Computer Supported Education, CSEDU 2019, held in Heraklion, Crete, Greece, in May 2019. The 30 revised full papers were carefully reviewed and selected from 202 submissions. The papers cover wide research fields including authoring tools and content development, AV-communication and multimedia, classroom management, e-Learning hardware and software, blended learning, critical success factors in distance learning.

Decades of research have shown that student collaboration in groups doesn't just happen; rather it needs to be a deliberate process facilitated by the instructor. Promoting collaboration in virtual learning environments presents a variety of challenges. Computer-Supported Collaborative Learning: Best Practices & Principles for Instructors answers the demand for a thorough resource on techniques to facilitate effective collaborative learning in virtual environments. This book provides must-have information on the role of the instructor in computer-supported collaborative learning, real-world perspectives on virtual learning group collaboration, and supporting learning group motivation.

CSCL has in the past 15 years (and often in conjunction with Springer) grown into a thriving and active community. Yet, lacking is a comprehensive CSCL handbook that displays the range of research being done in this area. This handbook will provide an overview of the diverse aspects of the field, allowing newcomers to develop a sense of the entirety of CSCL research and for existing community members to become more deeply aware of work outside their direct area. The handbook will also serve as a ready reference for foundational concepts, methods, and approaches in the field. The chapters are written in such a way that each of them can be used in a stand-alone fashion while also serving as introductory readings in relevant study courses or in teacher education. While some CSCL-relevant topics are addressed in the International Handbook of the Learning Sciences and the International Handbook of Collaborative Learning, these books do not aim to present an integrated and comprehensive view of CSCL. The International Handbook of Computer- Supported Collaborative Learning covers all relevant topics in CSCL, particularly recent developments in the field, such as the rise of computational approaches and learning analytics.

This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Computer Supported Education, CSEDU 2017, held in Porto, Portugal, in April 2017. The 22 revised full papers were carefully reviewed and selected from 179 submissions. The papers deal with the following topics: new educational environments, best practices and case studies of innovative technology-based learning strategies, institutional policies on computer-supported education including open and distance education.

"Intelligent Support for Computer Science Education presents the authors' research journey into the effectiveness of human tutoring, with the goal of developing educational technology that can be used to improve introductory Computer Science education at the undergraduate level. Nowadays, Computer Science education is central to the concerns of society, as attested by the penetration of information technology in all aspects of our lives; consequently, in the last few years interest in Computer Science at all levels of schooling, especially at the college level, has been flourishing. However, introductory concepts in Computer Science such as data structures and recursion are difficult for novices to grasp. This book will be of special interest to the Computer Science education community, specifically instructors of introductory courses at the college level, and Advanced Placement (AP) courses at the high school level. Additionally, all the authors' work is relevant to the Educational Technology community, especially to those working in Intelligent Tutoring Systems, their interfaces, and Educational Data Mining, in particular as applied to human-human pedagogical interactions and to user interaction with educational software"--

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.