Application of dominance-based rough set theory for knowledge discovery in cooperative learning

Syed Arshad Raza; Iftikhar U Sikder

doi:10.1109/ICCITechn.2014.7073157

Application of dominance-based rough set theory for knowledge discovery in cooperative learning

Syed Arshad Raza
, Iftikhar U Sikder

Information Systems

University of Dammam
Cleveland State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper illustrates a rule induction approach to discover decision patterns by using Dominance-based Rough Set Approach (DRSA) to unravel the intrinsic factors for learning successes and failures in a cooperative group-learning environment. It employs an innovative group quiz method in a university Management Information Systems (MIS) course which induces students into a unique learning process. The survey results enumerate the conditioning factors in terms of multiple criteria ranked in ordinal scale or preference-ordered. The DRSA model is uniquely appropriate when data includes multiple criteria whose domains are preference-ordered. The assessment of the learning success shows how a preference-centric group decision model can be integrated with the dominance-based principle of rough set to derive minimal covering 'ifn, thenn' decision rules. The paper demonstrates that it is possible to develop a formal approximate reasoning scheme to develop group dynamics and discover inherent patterns of the heuristics for group decisions.

Original language	English
Title of host publication	2014 17th International Conference on Computer and Information Technology, ICCIT 2014
Place of Publication	usa
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	273-279
Number of pages	7
ISBN (Electronic)	9781479962884
DOIs	https://doi.org/10.1109/ICCITechn.2014.7073157
State	Published - Dec 23 2014
Event	17th International Conference on Computer and Information Technology, ICCIT 2014 - Dhaka, Bangladesh Duration: Dec 22 2014 → Dec 23 2014

Conference

Conference	17th International Conference on Computer and Information Technology, ICCIT 2014
Country/Territory	Bangladesh
City	Dhaka
Period	12/22/14 → 12/23/14

Keywords

Cooperative learning
Knowledge discovery
Multi-criteria sorting
Rough set theory

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10.1109/ICCITechn.2014.7073157

Cite this

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title = "Application of dominance-based rough set theory for knowledge discovery in cooperative learning",

abstract = "This paper illustrates a rule induction approach to discover decision patterns by using Dominance-based Rough Set Approach (DRSA) to unravel the intrinsic factors for learning successes and failures in a cooperative group-learning environment. It employs an innovative group quiz method in a university Management Information Systems (MIS) course which induces students into a unique learning process. The survey results enumerate the conditioning factors in terms of multiple criteria ranked in ordinal scale or preference-ordered. The DRSA model is uniquely appropriate when data includes multiple criteria whose domains are preference-ordered. The assessment of the learning success shows how a preference-centric group decision model can be integrated with the dominance-based principle of rough set to derive minimal covering 'ifn, thenn' decision rules. The paper demonstrates that it is possible to develop a formal approximate reasoning scheme to develop group dynamics and discover inherent patterns of the heuristics for group decisions.",

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note = "17th International Conference on Computer and Information Technology, ICCIT 2014 ; Conference date: 22-12-2014 Through 23-12-2014",

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Raza, SA & Sikder, IU 2014, Application of dominance-based rough set theory for knowledge discovery in cooperative learning. in 2014 17th International Conference on Computer and Information Technology, ICCIT 2014., 7073157, Institute of Electrical and Electronics Engineers Inc., usa, pp. 273-279, 17th International Conference on Computer and Information Technology, ICCIT 2014, Dhaka, Bangladesh, 12/22/14. https://doi.org/10.1109/ICCITechn.2014.7073157

Application of dominance-based rough set theory for knowledge discovery in cooperative learning. / Raza, Syed Arshad; Sikder, Iftikhar U.
2014 17th International Conference on Computer and Information Technology, ICCIT 2014. usa: Institute of Electrical and Electronics Engineers Inc., 2014. p. 273-279 7073157.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Raza, Syed Arshad

AU - Sikder, Iftikhar U

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N2 - This paper illustrates a rule induction approach to discover decision patterns by using Dominance-based Rough Set Approach (DRSA) to unravel the intrinsic factors for learning successes and failures in a cooperative group-learning environment. It employs an innovative group quiz method in a university Management Information Systems (MIS) course which induces students into a unique learning process. The survey results enumerate the conditioning factors in terms of multiple criteria ranked in ordinal scale or preference-ordered. The DRSA model is uniquely appropriate when data includes multiple criteria whose domains are preference-ordered. The assessment of the learning success shows how a preference-centric group decision model can be integrated with the dominance-based principle of rough set to derive minimal covering 'ifn, thenn' decision rules. The paper demonstrates that it is possible to develop a formal approximate reasoning scheme to develop group dynamics and discover inherent patterns of the heuristics for group decisions.

AB - This paper illustrates a rule induction approach to discover decision patterns by using Dominance-based Rough Set Approach (DRSA) to unravel the intrinsic factors for learning successes and failures in a cooperative group-learning environment. It employs an innovative group quiz method in a university Management Information Systems (MIS) course which induces students into a unique learning process. The survey results enumerate the conditioning factors in terms of multiple criteria ranked in ordinal scale or preference-ordered. The DRSA model is uniquely appropriate when data includes multiple criteria whose domains are preference-ordered. The assessment of the learning success shows how a preference-centric group decision model can be integrated with the dominance-based principle of rough set to derive minimal covering 'ifn, thenn' decision rules. The paper demonstrates that it is possible to develop a formal approximate reasoning scheme to develop group dynamics and discover inherent patterns of the heuristics for group decisions.

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KW - Knowledge discovery

KW - Multi-criteria sorting

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Application of dominance-based rough set theory for knowledge discovery in cooperative learning

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