Sequential Pattern Mining System for Analysis of Programming Learning History

Shoichi Nakamura; Kaname Nozaki; Hiroki Nakayama; Yasuhiko Morimoto; Youzou Miyadera

doi:10.1109/DSDIS.2015.120

Sequential Pattern Mining System for Analysis of Programming Learning History

Shoichi Nakamura, Kaname Nozaki, Hiroki Nakayama, Yasuhiko Morimoto, Youzou Miyadera

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

The overall goal of this research is to establish the methodology for analyzing learning history data of programming exercise in accordance with learning processes. To achieve this goal, we developed a theoretical method of sequential pattern mining specialized for learning histories in programming exercise. On the basis of this method, we designed a system for analyzing the programming learning history data. This system consists of functions that are responsible for collection of learning histories, generation of sequence from the collected learning histories, extraction of noteworthy patterns from a set of sequences, and acquisition of findings from the extracted patterns. This paper mainly describes the functions of the system and their implementation along with an overview of the sequential pattern mining method.

本文言語	English
ホスト出版物のタイトル	Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	69-74
ページ数	6
ISBN（電子版）	9781509002146
DOI	https://doi.org/10.1109/DSDIS.2015.120
出版ステータス	Published - 2015
外部発表	はい
イベント	2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015 - Sydney, Australia 継続期間: 2015 12 11 → 2015 12 13

Other

Other	2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015
Country	Australia
City	Sydney
Period	15/12/11 → 15/12/13

ASJC Scopus subject areas

Computational Theory and Mathematics
Theoretical Computer Science
Computer Networks and Communications

文献へのアクセス

10.1109/DSDIS.2015.120

フィンガープリント「Sequential Pattern Mining System for Analysis of Programming Learning History」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル

Nakamura, S., Nozaki, K., Nakayama, H., Morimoto, Y., & Miyadera, Y. (2015). Sequential Pattern Mining System for Analysis of Programming Learning History. In Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015 (pp. 69-74). [7396483] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSDIS.2015.120

Sequential Pattern Mining System for Analysis of Programming Learning History. / Nakamura, Shoichi; Nozaki, Kaname; Nakayama, Hiroki; Morimoto, Yasuhiko; Miyadera, Youzou.

Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 69-74 7396483.

研究成果: Conference contribution

Nakamura, S, Nozaki, K, Nakayama, H, Morimoto, Y & Miyadera, Y 2015, Sequential Pattern Mining System for Analysis of Programming Learning History. in Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015., 7396483, Institute of Electrical and Electronics Engineers Inc., pp. 69-74, 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015, Sydney, Australia, 15/12/11. https://doi.org/10.1109/DSDIS.2015.120

Nakamura S, Nozaki K, Nakayama H, Morimoto Y, Miyadera Y. Sequential Pattern Mining System for Analysis of Programming Learning History. In Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 69-74. 7396483 https://doi.org/10.1109/DSDIS.2015.120

Nakamura, Shoichi ; Nozaki, Kaname ; Nakayama, Hiroki ; Morimoto, Yasuhiko ; Miyadera, Youzou. / Sequential Pattern Mining System for Analysis of Programming Learning History. Proceedings - 2015 IEEE International Conference on Data Science and Data Intensive Systems; 8th IEEE International Conference Cyber, Physical and Social Computing; 11th IEEE International Conference on Green Computing and Communications and 8th IEEE International Conference on Internet of Things, DSDIS/CPSCom/GreenCom/iThings 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 69-74

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abstract = "The overall goal of this research is to establish the methodology for analyzing learning history data of programming exercise in accordance with learning processes. To achieve this goal, we developed a theoretical method of sequential pattern mining specialized for learning histories in programming exercise. On the basis of this method, we designed a system for analyzing the programming learning history data. This system consists of functions that are responsible for collection of learning histories, generation of sequence from the collected learning histories, extraction of noteworthy patterns from a set of sequences, and acquisition of findings from the extracted patterns. This paper mainly describes the functions of the system and their implementation along with an overview of the sequential pattern mining method.",

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author = "Shoichi Nakamura and Kaname Nozaki and Hiroki Nakayama and Yasuhiko Morimoto and Youzou Miyadera",

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