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Web-Based Mathematics Testing with Automatic Assessment

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PRICAI 2012: Trends in Artificial Intelligence (PRICAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7458))

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Abstract

Web-based testing is an effective approach for self-assessment and intelligent tutoring in an e-learning environment. In this paper, we propose a novel framework for Web-based testing and assessment, in particular, for mathematics testing. There are two major components in Web-based mathematics testing and assessment: automatic test paper generation and mathematical answer verification. The proposed framework consists of an efficient constraint-based Divide-and-Conquer approach for automatic test paper generation, and an effective Probabilistic Equivalence Verification algorithm for automatic mathematical answer verification. The performance results have shown that the proposed framework is effective for web-based mathematics testing and assessment. In this paper, we will discuss the proposed framework and its performance in comparison with other techniques.

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References

  1. Alon, N.: The probabilistic method. Wiley (2008)

    Google Scholar 

  2. Beckmann, N.: The r*-tree: an efficient and robust access method for points and rectangles. ACM SIGMOD Record 19(2), 322–331 (1990)

    Article  Google Scholar 

  3. Conati, C.: Intelligent tutoring systems: new challenges and directions. In: Proceedings of the 14th International Conference on AI in Education (AIED), pp. 2–7 (2009)

    Google Scholar 

  4. Conejo, R., Guzmán, E., Millán, E., Trella, M., Pérez-De-La-Cruz, J.L., Ríos, A.: Siette: a web-based tool for adaptive testing. International Journal of Artificial Intelligence in Education 14(1), 29–61 (2004)

    Google Scholar 

  5. Gonzalez, T.F.: Handbook of Approximation Algorithms and Metaheuristics. Chapman & Hall/Crc (2007)

    Google Scholar 

  6. Guzman, E., Conejo, R.: Improving student performance using self-assessment tests. IEEE Intelligent Systems 22(4), 46–52 (2007)

    Article  Google Scholar 

  7. Ho, T.F., Yin, P.Y., Hwang, G.J., Shyu, S.J.: Multi-objective parallel test-sheet composition using enhanced particle swarm optimization. Journal of Educational Technology & Society 12(4), 193–206 (2008)

    Google Scholar 

  8. Hu, X.M., Zhang, J., Chung, H.S.H.: An intelligent testing system embedded with an ant-colony-optimization-based test composition. IEEE Trans. on Systems, Man, and Cybernetics 39(6), 659–669 (2009)

    Article  Google Scholar 

  9. Hwang, G.J.: A test-sheet-generating algorithm for multiple assessment requirements. IEEE Transactions on Education 46(3), 329–337 (2003)

    Article  Google Scholar 

  10. Hwang, G.J., Lin, B., Tseng, H.H.: On the development of a computer-assisted testing system with genetic test sheet-generating approach. IEEE Trans. on Systems, Man, and Cybernetics 35(4), 590–594 (2005)

    Article  Google Scholar 

  11. Hwang, G.J., Yin, P.Y., Yeh, S.H.: A tabu search approach to generating test sheets for multiple criteria. IEEE Trans. on Education 49(1), 88–97 (2006)

    Article  Google Scholar 

  12. Kullback, S.: Information theory and statistics. Dover (1997)

    Google Scholar 

  13. Mapple: Version 15 (2011), http://www.maplesoft.com/

  14. Mathematica (2011), http://www.wolfram.com/mathematica/

  15. Nguyen, M.L., Hui, S.C., Fong, A.C.: An efficient multi-objective optimization approach for online test paper generation. In: IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM), pp. 182–189 (2011)

    Google Scholar 

  16. Roussopoulos, N., Kelley, S.: Nearest neighbor queries. In: Proceedings of the ACM SIGMOD, pp. 71–79 (1995)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Nguyen, M.L., Hui, S.C., Fong, A.C.M. (2012). Web-Based Mathematics Testing with Automatic Assessment. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_32

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  • DOI: https://doi.org/10.1007/978-3-642-32695-0_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32694-3

  • Online ISBN: 978-3-642-32695-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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