Face to Face Cooperation with CoFFEE

Belgiorno, Furio; Chiara, Rosario De; Manno, Ilaria; Overdijk, Maarten; Scarano, Vittorio; Diggelen, Wouter van

doi:10.1007/978-3-540-87605-2_6

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…Bouyias et al (2008) report on ideas for an architecture to support the fading of collaboration scripts. Also, some authors propose component-based architectures for their ITS systems (Kumar et al 2007;Israel and Aiken 2007;Tedesco 2003) to facilitate the exchange of modules, argue for specific client-server architectures underlying their implementations (Baghaei et al 2007;Tedesco 2003;Vizcaino et al 2000), or describe architectures comprising collaborative learning tools (Belgiorno et al 2008). Yet, these software architecture descriptions are not adapted to the specific requirements of educational argumentation systems, and it is not clear how they can be used more generally.…”

Section: Architecture and Technologymentioning

confidence: 98%

“…Some systems offer configuration facilities to define when tools are available during the learning process. An example is CoFFEE (Collaborative Face to Face Educational Environment; Belgiorno et al 2008). CoFFEE provides a chat to send quick messages, a threaded forum for more structured discussions, a graphical discussion tool for collaborative brainstorming, and a collaborative writing tool.…”

Section: Argument Representationsmentioning

confidence: 99%

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Computer-supported argumentation: A review of the state of the art

Scheuer

Loll

Pinkwart

et al. 2010

Computer Supported Learning

303

185

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Argumentation is an important skill to learn. It is valuable not only in many professional contexts, such as the law, science, politics, and business, but also in everyday life. However, not many people are good arguers. In response to this, researchers and practitioners over the past 15-20 years have developed software tools both to support and teach argumentation. Some of these tools are used in individual fashion, to present students with the "rules" of argumentation in a particular domain and give them an opportunity to practice, while other tools are used in collaborative fashion, to facilitate communication and argumentation between multiple, and perhaps distant, participants. In this paper, we review the extensive literature on argumentation systems, both individual and collaborative, and both supportive and educational, with an eye toward particular aspects of the past work. More specifically, we review the types of argument representations that have been used, the various types of interaction design and ontologies that have been employed, and the system architecture issues that have been addressed. In addition, we discuss intelligent and automated features that have been imbued in past systems, such as automatically analyzing the quality of arguments and providing intelligent feedback to support and/or tutor argumentation. We also discuss a variety of empirical studies that have been done with argumentation systems, including, among other aspects, studies that have evaluated the effect of argument diagrams (e.g., textual versus graphical), different representations, and adaptive feedback on learning argumentation. Finally, we conclude by summarizing the "lessons learned" from this large and impressive body of work, particularly focusing on lessons for the CSCL research community and its ongoing efforts to develop computermediated collaborative argumentation systems.

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Section: Architecture and Technologymentioning

confidence: 98%

Section: Argument Representationsmentioning

confidence: 99%

Computer-supported argumentation: A review of the state of the art

Scheuer

Loll

Pinkwart

et al. 2010

Computer Supported Learning

303

185

View full text Add to dashboard Cite

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“…Assisting students in essays with structured and sound arguments is an important educational goal [20]. Hence, various argumentative support systems has been applied in collaborative educational environments [2], [18]. Persuasive essays are extensively studied in the context of automated essay grading.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Enacting textual entailment and ontologies for automated essay grading in chemical domain

Groza

Szabo

2015

2015 16th IEEE International Symposium on Computational Intelligence and Informatics (CINTI)

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We propose a system for automated essay grading using ontologies and textual entailment. The process of textual entailment is guided by hypotheses, which are extracted from a domain ontology. Textual entailment checks if the truth of the hypothesis follows from a given text. We enact textual entailment to compare students answer to a model answer obtained from ontology. We validated the solution against various essays written by students in the chemistry domain.

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