• Computer. Technology (i.e., computer hardware and/or software) plays a major role in changing the traditional view of education by creating the next generation of environments and infrastructures that enable new forms of learning and increase collaboration and educational opportunities to meet students' needs in the 21st century. New tools to facilitate collaboration, better methods of analyzing students' interactions, and effective ways to group students are some examples of the benefits that technology brings to the field.
• Supported. The term “Supported” refers to both pedagogical and technological support. To enhance collaborative learning, the interaction processes among students need to be well thought out and well structured. Furthermore, teachers need to continually assess students and groups in order to provide formative feedback and better guidance (e.g., scaffolding). Pedagogical support to create collaboration scripts and methods for group assessment is fundamental. Similarly, many other tasks that are already in use or are expected to be adopted by education practitioners will have a stronger impact upon learning if they are compliant with educational research findings. However, conducting these tasks in practice is quite difficult and time-consuming. Therefore, large-scale and effective deployment of collaborative learning can be better achieved through computational support as described above.
• Collaborative. In CSCL, collaboration plays the central role in the learning process. Students can learn collaboratively in many different ways: by engaging in argumentation and negotiation activities, sharing ideas, proposing different perspectives to solve a problem, discussing and reaching group consensus, and creating artifacts together with other people. To understand collaboration, researchers have studied the collaborative process as either a process that needs to be designed and managed or as an artifact that needs to be analyzed and understood. Many findings have shown that, in some situations, group learning may take longer, but the knowledge and skills acquired are much deeper and last longer if compared with individual learning [ 2]. However, grouping students together without any support often fails to create a nurturing, productive learning environment. Therefore, structured interactions and adequate group formation based on theoretical foundations are the keys to increase the chances of fruitful collaboration among peers [ 1].
• Learning. The ultimate goal of any educational technology, pedagogical method, or theory of learn-ing/instruction is to help students learn. Learning is not always a straightforward process where it is possible to write a single recipe. Nonetheless, it is possible to influence the conditions that increase the chances of learning to occur. The emergence and widespread adoption of collaboration technologies that enable people to collaborate anytime and anywhere, and the creation of better and more robust pedagogies and theoretical frameworks to support collaborative learning, have opened numerous new opportunities for students to engage in well-planned group activities and, through meaningful interactions, gradually construct their knowledge.
• S. Isotani is with the Human-Computer Interaction Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213. E-mail: firstname.lastname@example.org.
• J. Bourdeau is with the Department of Education, TELUQ-UQAM, 100, Sherbrooke St., Quebec, Canada, H2X 3P2. E-mail: email@example.com.
• R. Mizoguchi is with the Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, Japan, 567-0047. E-mail: firstname.lastname@example.org.
• W. Chen and B. Wasson are with the Department of Information Science and Media Studies, University of Bergen, Fosswinckelsgate 6 - 5007 Bergen, Norway. E-mail: email@example.com, firstname.lastname@example.org.
• J. Jovanovic is with the Department of Software Engineering, FOS - School of Business Administration, University of Belgrade, Jove Ilica 154, 11000 Belgrade, Serbia. E-mail: email@example.com.
For information on obtaining reprints of this article, please send e-mail to: firstname.lastname@example.org.
Seiji Isotani received the BSc and MSc degrees in computer science from the University of Sao Paulo, Brazil, and the PhD degree in information engineering from Osaka University, Japan. He is a research fellow associated with Carnegie Mellon University, Pittsburgh, Pennsylvania, and an assistant professor associated with the University of Sao Paulo, Brazil. His research interests are in the areas of ontological engineering, Computer-Supported Collaborative Learning (CSCL), Artificial Intelligence in Education (AIED), and technology-enhanced learning. His research on group formation and formalization of collaborative learning has received international recognition from the IEEE, the ACM, and IBM Research. He is a member of the IEEE.
Riichiro Mizoguchi received the PhD degree from Osaka University in 1977 and is currently a professor with the Institute of Scientific and Industrial Research at Osaka University. His research interests include non-parametric data analyses, knowledge-based systems, ontological engineering, and intelligent learning support systems. Dr. Mizoguchi was president of the International AI in ED Society, of the Asia-Pacific Society for Computers in Education from 2001 to 2003, and of the Japanese Society for Artificial Intelligence (JSAI) from 2006 to 2008, respectively. He is currently vice-president of the Semantic Web Science Association (SWSA).
Weiqin Chen received the PhD degree in computer science (AIED) from the Chinese Academy of Sciences. She is an associate professor in the Department of Information Science and Media Studies at the University of Bergen, Norway. Before moving to Bergen, she first worked as a researcher at Osaka University in Japan, then as a researcher and project leader at an Internet start-up company in Tokyo. Her current research focuses on intelligent support for collaborative learning, pedagogical agents, and educational data mining.
Barbara Wasson is a professor of pedagogical information science with the Department of Information Science and Media Studies, University of Bergen, Norway. She is one of the founders of the Kaleidoscope European Network of Excellence and has served on its executive board, its core group, and as the leader of the CSCL Special Interest Group. She is an associate editor of the International Journal of Computer Support for Collaborative Learning (iJCSCL) and in 2003 was the conference chair and local organizer of the International CSCL Conference. Her research interests include collaborative learning in distributed settings, socio-cultural theories of learning, design-based research, methodologies for studying virtual environments, and pedagogical agents.
Jelena Jovanovic received the BS, MSc, and PhD degrees in informatics and software engineering from the University of Belgrade, Serbia, in 2003, 2005, and 2007, respectively. She is an assistant professor of computer science with the Department of Software Engineering, FOS - School of Business Administration, University of Belgrade, Serbia. Her research interests lie in the areas of semantic technologies, web technologies, technology-enhanced learning, and knowledge management. She is a member oftheGOOD OLD AI research network. She can be reached at http://jelenajovanovic.net.