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Assessment of Examination Paper Quality Using Soft Computing Technique

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Advances in Computer and Computational Sciences

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 554))

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Abstract

The level of the education is an important aspect in the career of a student. Quality of education is the root parameter to enhance the standard of teaching. In order to achieve superior quality of teaching examination paper’s quality plays a vital role. Student’s knowledge, potential, and skills are all judged with the help of exam papers. Thus, examination papers play a very crucial role in the phase of student’s life and also help in judging the quality of teaching. So, the foremost aim of this paper is to assess the quality of examination paper using fuzzy logic.

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References

  1. Farhana Yakoob, Noor Hasimah Ibrahim Teo and Nur Atiqah Sia Abdullah, “Cognitive Knowledge Representation for Examination Questions Specification Analysis”, International Conference on Advanced Computer Science Applications and Technologies, 2013, pp. 530–533.

    Google Scholar 

  2. Yemin Guo and Lanmei Wang, “Preliminary Study on Evaluation of the Quality of Examination paper Based on Fuzzy theory”, 7th International Conference on Fuzzy Systems and Knowledge Discovery, 2010, pp. 1328–1331.

    Google Scholar 

  3. Xien Cheng and Jinghua Zheng, “Novel Approach of Auto-generating Examination Papers”, International Conference on e-Education, e-Business, e-Management and e-Learning, 2010, pp. 411–414.

    Google Scholar 

  4. Dimple V. Paul, Shankar B. Naik, Priyanka Rane and Jyoti D. Pawar, “Use of an Evolutionary Approach for Question Paper Template Generation”, 4th International Conference on Technology for Education, 2012, pp. 144–148.

    Google Scholar 

  5. Yuli Song and Feng Hong, “EPAC: Examination Paper Automatic Construction Based on K-Means Algorithm”, International Conference on Information Technology and Applications, 2013, pp. 232–235.

    Google Scholar 

  6. Ling Ling Han and Xiao Dong Li, “The Analysis of Exam Paper Component based on genetic algorithm”, 4th International Conference on Communication Systems and Network Technologies, 2014, pp. 561–564.

    Google Scholar 

  7. Liu Fang, Yang Ting-Ting, Chen Shou-Gang, Liu Jing-Duo, Zhang Shao-Gang and Chen Pu, He Jie-Tao, He Bin-Sheng, “Hierarchical clustering based teaching reform courses examination data analysis approach applied in China Open University system”, Seventh International Symposium on Computational Intelligence and Design, 2014, pp. 377–381.

    Google Scholar 

  8. Wang Jing jing, “Research On Intelligent Test Paper of WEB-Based”, International Conference on Computer Science and Information Processing (CSIP), 2012, pp. 369–371.

    Google Scholar 

  9. Wei Huang and Zhao-hui Wang, “Design of Examination Paper Generating System from Item Bank by Using Genetic Algorithm”, International Conference on Computer Science and Software Engineering, 2008, pp. 1323–1325.

    Google Scholar 

  10. Qingzhen Xu and Jing Kong, “Fuzzy Mathematics application in marking examination papers”, ISECS International Colloquium on Computing, Communication, Control, and Management, 2009, pp. 67–70.

    Google Scholar 

  11. Stergiopoulos, Charalampos, Panagiotis Tsiakas, Dimos Triantis, and Maria Kaitsa. “Evaluating Electronic Examination Methods Applied to Students of Electronics. Effectiveness and Comparison to the Paper-and-Pencil Method.” In Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006. IEEE International Conference, 2006, pp. 143–151.

    Google Scholar 

  12. Swart, Arthur James. “Evaluation of final examination papers in engineering: A case study using Bloom’s Taxonomy.” Education, IEEE Transactions on 53, no. 2 (2010): 257–264.

    Google Scholar 

  13. Shiyan, Wen. “Teaching methods for a school-based curriculum.” In Networking and Digital Society (ICNDS), 2nd International Conference, 2010, pp. 508–511.

    Google Scholar 

  14. Wang, Xiuhui, and Junqin Wen. “Architectures and algorithms for auto-generating examination paper system.” In Biomedical Engineering and Informatics (BMEI), 3rd International Conference, 2010, pp. 2893–2895.

    Google Scholar 

  15. Jiang, Lanling, and Fang Zhang. “Research and implementation of intelligent paper generating system.” In 2011 International Conference on Computer Science and Service System (CSSS). 2011.

    Google Scholar 

  16. Raus, Mohd Ikhsan M., Roziah Mohd Janor, Roslan Sadjirin, and Zahriah Sahri. “The development of i-QuBES for UiTM: From feasibility study to the design phase.” In Control and System Graduate Research Colloquium (ICSGRC), 2014, pp. 96–101.

    Google Scholar 

  17. Mogale, Miemie, Mariana Gerber, Mariana Carroll, and Rossouw Von Solms. “Information Security Assurance Model (ISAM) for an Examination Paper Preparation Process.” In Information Security for South Africa (ISSA), 2014, pp. 1–10.

    Google Scholar 

  18. Artificial Intelligence-Fuzzy Logic Systems. http://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_fuzzy_logic_systems.htm.

  19. MATLAB Toolbox, http://www.mathworks.com.

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Correspondence to Shruti Mangla .

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Mangla, S., Singhal, A. (2018). Assessment of Examination Paper Quality Using Soft Computing Technique. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_46

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  • DOI: https://doi.org/10.1007/978-981-10-3773-3_46

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3772-6

  • Online ISBN: 978-981-10-3773-3

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