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Design and Evaluation of OptimEx, an Experimentation System for Optimization Algorithms

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ICT in Education

Abstract

We hardly find educational systems that allow computer science students to experiment with optimization algorithms with respect to the optimality property. We may highlight the GreedEx system, but it has the limitation of only being usable with a small set of predefined problems. In this chapter, we present a system similar to GreedEx but generic, called OptimEx. The contributions of the chapter are threefold. Firstly, we introduce the main features of the OptimEx system. Secondly, we describe different issues regarding its educational use: usage in educational scenarios, usage with different algorithm design techniques, and how it can inform us about students’ errors. Thirdly, we present the results of a usability evaluation conducted with students. As a result, students consider the system highly usable but they also report on a number of issues that should be addressed to enhance it.

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References

  • ACM & IEEE Computer Society. (2013). The joint task force on computing curricula: Computer science curricula 2013. Retrieved from http://www.acm.org/education/CS2013-final-report.pdf

  • Ala-Mutka, K. M. (2005). A survey of automatic assessment approaches for programming assignments. Computer Science Education, 15(2), 83–102.

    Article  Google Scholar 

  • Baldwin, D. (1992). Using scientific experiments in early Computer Science laboratories. In Proceedings of the 23rd SIGCSE Technical Symposium on Computer Science Education, SIGCSE’92 (pp. 102–106). Nueva York: ACM.

    Google Scholar 

  • Brassard, G., & Bratley, P. (1996). Fundamentals of algorithmics. Upper Saddle River, NJ: Prentice-Hall.

    Google Scholar 

  • Chen, M.-Y., Wei, J.-D., Huang, J.-H., Lee, D. T. (2006). Design and applications of an algorithm benchmark system in a computational problem solving environment. In Proceedings of the 11th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE’06 (pp. 123–127). Nueva York: ACM.

    Google Scholar 

  • Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to algorithms (3rd ed.). Cambridge, MA: The MIT Press.

    Google Scholar 

  • Denning, P. J., Comer, D. E., Gries, D., Mulder, M. C., Tucker, A. B., Turner, A. J., et al. (1989). Computing as a discipline. Communications of the ACM, 32(1), 9–23.

    Article  Google Scholar 

  • Dix, A., Finlay, J., Abowd, G. D., & Beale, R. (2004). Human-computer interaction (3rd ed.). Harlow, England: Pearson Education.

    Google Scholar 

  • Douce, C., Livingstone, D., & Orwell, J. (2005). Automatic test-based assessment of programming: A review. Journal of Educational Resources in Computing, 5(3), 4.

    Article  Google Scholar 

  • Edwards, S. (2003). Rethinking Computer Science education from a test-first perspective. In Proceedings of the ACM Symposium on Object-Oriented Programming Systems, Languages, and Applications, OOPSLA’03 (pp. 148–155). New York: ACM.

    Google Scholar 

  • Ginat, D. (2003). The greedy trap and learning from mistakes. In Proceedings of the 34th SIGCSE Technical Symposium on Computer Science Education, SIGCSE’03 (pp. 11–15). New York: ACM. doi:10.1145/611892.611920

  • Ihantola, P., Ahoniemi, T., Karavirta, V., & Seppälä, O. (2010). Review of recent systems for automatic assessment of programming assignments. In Proceedings of the 10th Koli Calling International Conference on Computing Education Research, Koli Calling’10 (pp. 86–93). New York: ACM.

    Google Scholar 

  • Kleinberg, J., & Tardos, É. (2006). Algorithm design. Boston: Pearson Addison-Wesley.

    Google Scholar 

  • Reed, D., Miller, C. S., & Braught, G. (2000). Empirical investigation through the CS curriculum. In Proceedings of the 31st SIGCSE Technical Symposium on Computer Science Education, SIGCSE’00 (pp. 202–206). New York: ACM.

    Google Scholar 

  • Sahni, S. (2005). Data structures, algorithms and applications in Java (2nd ed.). Summit, NJ: Silicon Press.

    Google Scholar 

  • Velázquez-Iturbide, J. Á., Debdi, O., Esteban-Sánchez, N., & Pizarro, C. (2013). GreedEx: A visualization tool for experimentation and discovery learning of greedy algorithms. IEEE Transactions on Learning Technologies, 6(2), 130–143. doi:10.1109/TLT.2013.8.

    Article  Google Scholar 

  • Velázquez-Iturbide, J. Á. (2013). An experimental method for the active learning of greedy algorithms. ACM Transactions on Computing Education, 13(4), article 18. doi:10.1145/2534972

    Google Scholar 

  • Velázquez-Iturbide, J. Á. (2014). Una evaluación de usabilidad de OptimEx, Serie de Informes Técnicos DLSI1-URJC, 2014-02. Departamento de Lenguajes y Sistemas Informáticos I, Universidad Rey Juan Carlos

    Google Scholar 

  • Velázquez-Iturbide, J. Á. (2014). Difficulties, attitudes and misconceptions on experimenting with optimization algorithms. In: Proceedings of the 2014 International Symposium on Computers in Education, SIIE’14 (pp. 17–22). IEEE. doi:10.1109/SIIE.2014.7017698

  • Velázquez-Iturbide, J. Á., & Debdi, O. (2011). Experimentation with optimization problems in algorithm courses. In Proceedings of the IEEE International Conference on Computer as a Tool, EUROCON 2011. IEEE. doi:10.1109/EUROCON.2011.5929294

  • Velázquez-Iturbide, J. Á., Debdi, O., & Paredes-Velasco, M. (2015). A review of teaching and learning through practice of optimization algorithms. In R. Queirós (Ed.), Innovative teaching strategies and new learning paradigms in computer programming (pp. 65–87). IGI Global: Hershey, PA. doi:10.4018/978-1-4666-7304-5.

    Google Scholar 

  • Velázquez-Iturbide, J. Á., Pérez-Carrasco, A., & Debdi, O. (2013). Experiences in usability evaluation of educational programming tools. In C. González (Ed.), Student usability in educational software and games: Improving experiences (pp. 241–260). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-1987-6.

    Chapter  Google Scholar 

  • Velázquez-Iturbide, J. Á., Pareja-Flores, C., Debdi, O., & Paredes-Velasco, M. (2012). Interactive experimentation with algorithms. In S. Abramovich (Ed.), Computers in Education (Vol. 2, pp. 47–70). New York: Nova Science.

    Google Scholar 

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Acknowledgements

This work was supported by the Spanish Ministry of Economy and Competitiveness under research grant TIN2011-29542-C02-01, the Region of Madrid under research grant S2013/ICE-2715, and the Universidad Rey Juan Carlos under research grant 30VCPIGI15.

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Correspondence to J. Ángel Velázquez-Iturbide .

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Velázquez-Iturbide, J.Á. (2016). Design and Evaluation of OptimEx, an Experimentation System for Optimization Algorithms. In: Marcelino, M., Mendes, A., Gomes, M. (eds) ICT in Education. Springer, Cham. https://doi.org/10.1007/978-3-319-22900-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-22900-3_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22899-0

  • Online ISBN: 978-3-319-22900-3

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