This book is an edited volume of case studies exploring the uptake and use of computer supported collaborative learning in work settings. This book fills a significant gap in the literature. A number of existing works provide empirical research on collaborative work practices (Lave & Wenger, 1987; Davenport, 2005), the sharing of information at work (Brown & Duguid, 2000), and the development of communities of practice in workplace settings (Wenger, 1998). Others examine the munificent variation of information and communication technology use in the work place, including studies of informal social networks, formal information distribution and other socio-technical combinations found in work settings (Gibson & Cohen, 2003). Another significant thread of prior work is focused on computer supported collaborative learning, much of it investigating the application of computer support for learning in the context of traditional educational institutions, like public schools, private schools, colleges and tutoring organizations. Exciting new theories of how knowledge is constructed by groups (Stahl, 2006), how teachers contribute to collaborative learning (reference to another book in the series) and the application of socio-technical scripts for learning is explicated in book length works on CSCL. Book length empirical work on CSCW is widespread, and CSCL book length works are beginning to emerge with greater frequency. We distinguish CSCL at Work from prior books written under the aegis of training and development, or human resources more broadly. The book aims to fill a void between existing works in CSCW and CSCL, and will open with a chapter characterizing the emerging application of collaborative learning theories and practices to workplace learning. CSCL and CSCW research each make distinct and important contributions to the construction of collaborative workplace learning.

The Computer Supported Collaborative Learning (CSCL) Conference 2013 proceedings, Volume 1

The Computer Supported Collaborative Learning (CSCL) Conference 2013 proceedings, Volume 2

Mass collaboration on Internet platforms like Wikipedia and Scratch, along with wider movements like the maker space and citizen science, are poised to have profound impacts on learning and education. Bringing together researchers from such fields as: psychology, education, information technology, and economics, the book offers a comprehensive overview of mass collaboration, novel, cross disciplinary, theoretical accounts, and methodological approaches for studying and improving these massively collaborative enterprises. The book is aimed to serve as an information source for researchers, educators, and designers of platforms and learning environments.

This book constitutes the refereed proceedings of the 6th International Workshop on Learning Technology for Education in Cloud, LTEC 2017, held in Beijing, China, in August 2017. The 16 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers are organized in topical sections on Learning Technologies; Learning Tools and Environment; Online Learning and MOOC; Problem Solving and Knowledge Transfer.

The Learning Sciences in Conversation explores the unique pluralities, complex networks, and distinct approaches of the learning scientists of today. Focused on four key scholarly areas – transdisciplinarity, design, cognition, and technology – this cutting-edge volume draws on empirical and theoretical foundations to illustrate the directions, perspectives, methods, and questions that continue to define this evolving field. Contributions by researchers are put in dialogue with one another, offering an exemplary analysis of a field that synthesizes, in situ, various scholarly traditions and orientations to create a critical and heterogenous understanding of learning.

The emerging field of Data Science has had a large impact on science and society. This book explores how one distinguishing feature of Data Science – its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded – suggests serious implications for learning and education. Drawing from theories of learning and identity development in the learning sciences, this volume investigates the impacts of these complex relationships on how learners think about, use, and share data, including their understandings of data in light of history, race, geography, and politics. More than just using ‘real world examples’ to motivate students to work with data, this book demonstrates how learners’ relationships to data shape how they approach those data with agency, as part of their social and cultural lives. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, socially aware, and transformative Data Science Education. The chapters in this book were originally published as a special issue of the Journal of the Learning Sciences.