From GreedEx to GreedEx Tab v2.0: Tool for Learning Greedy Algorithms on iPad Following CIAM Mobile Methodology

  • Yoel Arroyo
  • Manuel Ortega Cordovilla
  • Miguel A. Redondo
  • Ana I. Molina
  • María del Carmen Lacave
  • Manuel Ortega Cantero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10283)

Abstract

The growth in the use of mobile devices have allowed for the development of new educational modalities within e-Learning. Because of this, we have shown the evolution experienced by GreedEx, a desktop application that facilitates the learning of greedy algorithms. Two iPad versions were developed (GreedEx Tab v1.0 and v2.0). The first iPad version adapted many functionalities to mobile devices, whilst the latest one adds several pedagogical usability characteristics. For that, we followed the CIAM Mobile methodology, improving the educational and collaborative aspects. Our main aim is to verify that this methodology is useful for the production of new methodological approaches aligned with the principles of MDE (Model-Driven Engineering) that gives support to learning activities within a group. Therefore, this work can be considered a preliminary m-CIAM test case .

Keywords

Mobile usability Mobile learning Methodology Greedy algorithms learning Knapsack problem iOS iPad Model-driven development 

References

  1. 1.
    Cormen, T.H.: Introduction to Algorithms. MIT Press, Cambridge (2009)MATHGoogle Scholar
  2. 2.
    Ortega Cordovilla, M., et al.: GreedEx Tab: tool for learning Greedy algorithms on mobile devices. In: IARIA 2016, pp. 28–35 (2016)Google Scholar
  3. 3.
    Arroyo, Y., Navarro, C.X., Molina, A.I., Redondo, M.A.: CIAM mobile: methodology supporting mobile application design and evaluation applied on GreedEx Tab. In: Luo, Y. (ed.) CDVE 2016. LNCS, vol. 9929, pp. 102–109. Springer, Cham (2016). doi:10.1007/978-3-319-46771-9_14 CrossRefGoogle Scholar
  4. 4.
    Molina, A.I., et al.: CIAM: a methodology for the development of groupware user interfaces. J. UCS 14(9), 1435–1446 (2008)Google Scholar
  5. 5.
    Navarro, C.X., et al.: Framework to evaluate M-learning systems: a technological and pedagogical approach. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 11(1), 33–40 (2016)CrossRefGoogle Scholar
  6. 6.
    Pettey, C., et al.: A tool for promoting algorithm development in introductory CS classes. In: Proceedings of ED-MEDIA (2009)Google Scholar
  7. 7.
    Rößling, G., Schüer, M., Freisleben, B.: The ANIMAL algorithm animation tool. ACM SIGCSE Bull. (2000). ACMGoogle Scholar
  8. 8.
    Naps, T.L.: JHAVÉ: supporting algorithm visualization. IEEE Comput. Graph. Appl. 25(5), 49–55 (2005)CrossRefGoogle Scholar
  9. 9.
    Ullrich, T., Fellner, D.: AlgoViz-a computer graphics algorithm visualization toolkit. In: World Conference on Educational Multimedia, Hypermedia and Telecommunications (2004)Google Scholar
  10. 10.
    Lahoti, M.: GATutor: Intelligent Tutoring System for Greedy Algorithms. Indian Institute of Technology Bombay, Mumbai (2014)Google Scholar
  11. 11.
    Velazquez-Iturbide, J.A., et al.: GreedEx: a visualization tool for experimentation and discovery learning of greedy algorithms. IEEE Trans. Learn. Technol. 6(2), 130–143 (2013)CrossRefGoogle Scholar
  12. 12.
    Molina, A.I., et al.: Evaluación basada en eye tracking de las técnicas de visualización de programas soportadas por el sistema GreedExGoogle Scholar
  13. 13.
    Molina, A.I., et al.: Assessing representation techniques of programs supported by GreedEx. In: 2014 International Symposium on Computers in Education (SIIE). IEEE (2014)Google Scholar
  14. 14.
    Schwaber, K.: SCRUM development process. In: Sutherland, J., Casanave, C., Miller, J., Patel, P., Hollowell, G. (eds.) Business Object Design and Implementation, pp. 117–134. Springer, London (1997)CrossRefGoogle Scholar
  15. 15.
    Kroll, P., MacIsaac, B.: Agility and Discipline Made Easy: Practices from OpenUP and RUP. Pearson Education, Boston (2006)Google Scholar
  16. 16.
    Beck, K., et al.: Manifesto for agile software development (2001)Google Scholar
  17. 17.
    Ortega Cordovilla, M.: Usability Tests of GreedEx Tab. CHICO Wiki. http://chico.inf-cr.uclm.es/greedextab/wiki/index.php/Pruebas_de_usabilidad. Accessed 29 Dec 2016
  18. 18.
    Shneiderman, B., Plaisant, C.: Designing the User Interface: Strategies for Effective Human-Computer Interaction, vol. 5. Addison-Wesley Publishing Co., Boston (2010)Google Scholar
  19. 19.
    Apple Inc.: iOS Human Interface Guidelines. Apple Developer Website. https://developer.apple.com/ios/human-interface-guidelines/overview/design-principles/. Accessed 10 Jan 2017
  20. 20.
    Nielsen, J., Budiu, R.: Mobile Usability. MITP-Verlags GmbH & Co. KG (2013)Google Scholar
  21. 21.
    Molina, A.I., et al.: A Model-Driven Approach for the Development of CSCL Tools that Considers Pedagogical UsabilityGoogle Scholar
  22. 22.
    Koschmann, T.D.: CSCL, Theory and Practice of an Emerging Paradigm. Routledge, New York (1996)Google Scholar
  23. 23.
    Gallardo, J., Bravo, C., Redondo, M.A.: A model-driven development method for collaborative modeling tools. J. Netw. Comput. Appl. 35(3), 1086–1105 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yoel Arroyo
    • 1
  • Manuel Ortega Cordovilla
    • 1
  • Miguel A. Redondo
    • 1
  • Ana I. Molina
    • 1
  • María del Carmen Lacave
    • 1
  • Manuel Ortega Cantero
    • 1
  1. 1.Escuela Superior de InformáticaUniversidad de Castilla-La ManchaCiudad RealSpain

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