A novel genetic algorithm for test sheet assembling problem in learning cloud

Shih Pang Tseng; Long Yeu Chung; Po Lin Huang; Ming Chao Chiang; Chu-Sing Yang

doi:10.1007/978-94-007-7262-529

A novel genetic algorithm for test sheet assembling problem in learning cloud

Shih Pang Tseng, Long Yeu Chung, Po Lin Huang, Ming Chao Chiang, Chu-Sing Yang

Institute of Computer and Communication Engineering

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

1 Citation (Scopus)

Abstract

The assessment is the most effectively tool for the teachers to realized the learning status of the learners. The test sheet assembling is an important job in the E-learning. In the future learning cloud environment, the large amount of items would be aggregated into the itembank from various sources. The test sheet assembling algorithm should be with the ability of abstract the needed information directly from the items. This paper proposed an effective method based on genetic algorithm to solve the test sheet assembling problem. The experimental result shows the effectiveness of the proposed method.

Original language	English
Title of host publication	Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013
Pages	247-255
Number of pages	9
DOIs	https://doi.org/10.1007/978-94-007-7262-529
Publication status	Published - 2014 Feb 17
Event	Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013 - , Taiwan Duration: 2013 Aug 23 → 2013 Aug 25

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	260 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Other

Other	Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013
Country	Taiwan
Period	13-08-23 → 13-08-25

All Science Journal Classification (ASJC) codes

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-94-007-7262-529

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Tseng, S. P., Chung, L. Y., Huang, P. L., Chiang, M. C., & Yang, C-S. (2014). A novel genetic algorithm for test sheet assembling problem in learning cloud. In Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013 (pp. 247-255). (Lecture Notes in Electrical Engineering; Vol. 260 LNEE). https://doi.org/10.1007/978-94-007-7262-529

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title = "A novel genetic algorithm for test sheet assembling problem in learning cloud",

abstract = "The assessment is the most effectively tool for the teachers to realized the learning status of the learners. The test sheet assembling is an important job in the E-learning. In the future learning cloud environment, the large amount of items would be aggregated into the itembank from various sources. The test sheet assembling algorithm should be with the ability of abstract the needed information directly from the items. This paper proposed an effective method based on genetic algorithm to solve the test sheet assembling problem. The experimental result shows the effectiveness of the proposed method.",

author = "Tseng, {Shih Pang} and Chung, {Long Yeu} and Huang, {Po Lin} and Chiang, {Ming Chao} and Chu-Sing Yang",

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booktitle = "Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013",

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Tseng, SP, Chung, LY, Huang, PL, Chiang, MC & Yang, C-S 2014, A novel genetic algorithm for test sheet assembling problem in learning cloud. in Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013. Lecture Notes in Electrical Engineering, vol. 260 LNEE, pp. 247-255, Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013, Taiwan, 13-08-23. https://doi.org/10.1007/978-94-007-7262-529

A novel genetic algorithm for test sheet assembling problem in learning cloud. / Tseng, Shih Pang; Chung, Long Yeu; Huang, Po Lin; Chiang, Ming Chao; Yang, Chu-Sing.

Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013. 2014. p. 247-255 (Lecture Notes in Electrical Engineering; Vol. 260 LNEE).

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

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