Use of the CANTOR system for collaborative learning in medical visual object recognition

Hans H. K. Sønderstrup-Andersen; Verner Andersen; Birgit Guldhammer Skov

Use of the CANTOR system for collaborative learning in medical visual object recognition

Hans H. K. Sønderstrup-Andersen, Verner Andersen, Birgit Guldhammer Skov

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

Abstract

This paper reports from a user requirement, design and evaluation study on supporting collaborative learning by visual perception in the medical education domain. The CANTOR (Converging Agreement by Networking Telematics for Object Recognition) system can briefly be described as a tool that support collaborative consensus making when classifying sets of medical images or objects in medical images An evaluation experiment showed that using CANTOR seems to give a better learning effect than by using traditional methods.

Original language	English
Title of host publication	CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community
Editors	Gerry Stahl
Publisher	International Society of the Learning Sciences
Publication date	2002
Pages	544-545
Publication status	Published - 2002
Externally published	Yes
Event	CSCL 2002 Conference on Computer Support for Collaborative Learning : Foundations for a CSCL Community - Boulder, Colorado, United States Duration: 7 Jan 2002 → 11 Jan 2002

Conference

Conference	CSCL 2002 Conference on Computer Support for Collaborative Learning
Country/Territory	United States
City	Boulder, Colorado
Period	07/01/2002 → 11/01/2002

Cite this

Sønderstrup-Andersen, Hans H. K. ; Andersen, Verner ; Skov, Birgit Guldhammer. / Use of the CANTOR system for collaborative learning in medical visual object recognition. CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning: : Foundations for a CSCL Community . editor / Gerry Stahl. International Society of the Learning Sciences, 2002. pp. 544-545

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abstract = "This paper reports from a user requirement, design and evaluation study on supporting collaborative learning by visual perception in the medical education domain. The CANTOR (Converging Agreement by Networking Telematics for Object Recognition) system can briefly be described as a tool that support collaborative consensus making when classifying sets of medical images or objects in medical images An evaluation experiment showed that using CANTOR seems to give a better learning effect than by using traditional methods.",

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Sønderstrup-Andersen, HHK, Andersen, V & Skov, BG 2002, Use of the CANTOR system for collaborative learning in medical visual object recognition. in G Stahl (ed.), CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning: : Foundations for a CSCL Community . International Society of the Learning Sciences, pp. 544-545, CSCL 2002 Conference on Computer Support for Collaborative Learning , Boulder, Colorado, United States, 07/01/2002.

Use of the CANTOR system for collaborative learning in medical visual object recognition. / Sønderstrup-Andersen, Hans H. K.; Andersen, Verner; Skov, Birgit Guldhammer.

CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning: : Foundations for a CSCL Community . ed. / Gerry Stahl. International Society of the Learning Sciences, 2002. p. 544-545.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

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AB - This paper reports from a user requirement, design and evaluation study on supporting collaborative learning by visual perception in the medical education domain. The CANTOR (Converging Agreement by Networking Telematics for Object Recognition) system can briefly be described as a tool that support collaborative consensus making when classifying sets of medical images or objects in medical images An evaluation experiment showed that using CANTOR seems to give a better learning effect than by using traditional methods.

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BT - CSCL '02 Proceedings of the Conference on Computer Support for Collaborative Learning:

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