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The most extensive and influential example of an effort to impact schooling with a CSCL approach has been the Knowledge Forum project, directed for many years by Marlene Scardamalia and Carl Bereiter at OISE in Toronto. Based on theories of the role of reading and writing in learning, they proposed that students should have media and practices through which they could communicate and build textual knowledge together on the model of academic communities.

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Just as journal articles and conference papers allow scholars to articulate their ideas, discuss them and revise them in a community context, so students should be able to propose theories, react to the theories of others, share pro and con evidence and collectively refine the theories. The project developed many iterations of software to support this process, involved researchers from around the world and mentored teachers for years. The project experimented with curricular topics from various academic fields and published analyses of classroom experiences. This continuing project has produced many researchers and teachers oriented to CSCL.

It has also developed the central theory of knowledge building, in which ideas are refined through computer-supported classroom discourse. In this issue, Bodong Chen, Marlene Scardamalia and Carl Bereiter propose a new feature for their software, support for promising ideas.

The ability to recognize and focus on promising ideas is an important skill for knowledge building. For instance, Ph.D. Students must propose a promising idea for their dissertation topic in order to succeed and researchers must argue for a promising idea in order to be awarded a grant. In this article, the authors describe a promising idea for software support of knowledge building: a promising-ideas tool.

They show that even young children (about 8 years old) can identify, communicate, respond to and build upon promising ideas in their knowledge-building discussions, mediated by this tool. By making the identification of promising ideas explicit within the classroom discourse practices, the tool instills in the students the important skill of making judgments of what is likely to become an important idea in their community discourse. This tool is just one new refinement to the software and classroom practices of the authors' DBR process of iteratively testing new features, just like last issue’s formative-feedback tool (Resendes et al. Argumentation style. Another dominant research effort within CSCL has been the exploration of support for argumentation. It seems reasonable that this would be a promising idea in CSCL since argumentation is a way of conceptualizing the negotiation of meaning and the building of knowledge through community discourse.

Aristotle began the formalization of rational discourse as logic and Toulmin ( ) proposed a rubric for scientific arguments. Toulmin’s logical model has been influential in CSCL research, despite the fact that student discussions of topics generally follow very different patterns. For recent ijCSCL articles on argumentation, see (Alagoz; Asterhan & Schwarz; Scheuer et al.,; Schwarz et al., ). The Irish authors of our second paper— Owen M. Harney, Michael J. Hogan, Benjamin Broome, Tony Hall and Cormac Ryan—explore the effects on argumentation style of various task-level and process-level prompts.

These experimentally manipulated features of the support software mediate the student argumentation. This alters the group discourse practice and, potentially, the individual students' style of argument (including their silent mental thinking). Cohesion and dialogism. Live feedback to students about their behavior can be effective in many ways (Enyedy et al.,; Schneider & Pea ). However, the promise of robust and useful automated discourse analysis—especially in real time—has been largely elusive until now.

Statistical AI approaches require large amounts of data, which were hard to collect quickly in the past. With the proliferation of online education—especially using MOOCs—techniques developed for “big data” are now becoming applicable. In the final article of the 2015 volume of ijCSCL, Matthew Berland, Don Davis and Carmen Petrick Smith provide an example of identifying specific discourse features relevant to collaborative learning and displaying representations of the behavior of these features in the interaction of student groups. These displays are made available to the teacher in real time to inform the process of matching students into collaborating pairs. While the idea of displaying learning analytics to teachers and students in a live setting has been frequently proposed, the evidence that the analytics proposed by researchers and programmers are understandable and helpful for classroom teachers and their students is far less common. Christina aguilera you lost me piano pdf music.