Journal of Intelligent & Robotic Systems

, Volume 81, Issue 1, pp 117–129 | Cite as

Experiences Incorporating Lego Mindstorms Robots in the Basic Programming Syllabus: Lessons Learned

  • Ainhoa ÁlvarezEmail author
  • Mikel Larrañaga


Basic Programming is a first year mandatory course of the Computer Engineering degree. Both students and teachers face difficulties in this course, which has high failure and drop-out rates. Several authors have proposed the use of visual programming environments and robots to overcome the difficulties of this course, some of which have been successful. This paper presents the two-year experiment using Lego Robots carried out at the University of the Basque Country (UPV/EHU) with around 100 students, along with the results. Satisfactory results have been obtained regarding both motivation and the perception of the students of their learning process; moreover the drop-out rate decreased even though no statistical significance was obtained regarding the final marks of the course. From those results and the analysis of the data it was derived that robot sessions should be more integrated in the curriculum, giving them greater relevance in the final marks. In addition, it is indispensable to classify course students and adapt learning sessions to each student type due to the high student heterogeneity.


Basic Programming Lego Mindstorms Robots in Computer Engineering Education 


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  1. 1.
    Alvarez, A., Larrañaga, M.: Using LEGO mindstorms to engage students on algorithm design. In: Frontiers in Education (FIE’13), pp. 1346–1351 (2013)Google Scholar
  2. 2.
    Alvarez, A., Martin, M., Fernandez-Castro, I., Urretavizcaya, M.: Blending traditional teaching methods with learning environments: experience, cyclical evaluation process and impact with MAgAdI. Comput. Educ. 68, 129–140 (2013)CrossRefGoogle Scholar
  3. 3.
    Anderson, L.W., Krathwohl, D.R.: A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’S Taxonomy of Educational Objectives. Longman, New York (2001)Google Scholar
  4. 4.
    Bloom, B.S., Engelhart, M.D., Furst, E.J., Hill, W.H., Krathwohl, D.R.: Taxonomy of Educational Objectives: The Classification of Educational Goals: Handbook I, Cognitive Domain. Longman, New York (1956)Google Scholar
  5. 5.
    Burbaite, R., Damaševičius, R., Štuikys, V.: Using robots as learning objects for teaching computer science. In: X World Conference on Computers in Education (WCCE’13), pp. 103–111 (2013)Google Scholar
  6. 6.
    Dagdilelis, V., Sartatzemi, M., Kagani, K.: Teaching (with) robots in secondary schools: some new and not-so-new pedagogical problems. In: Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies (ICALT’05), pp. 757–761. IEEE, Kaohsiung (2005)Google Scholar
  7. 7.
    Fagin, B.S., Merkle, L.: Quantitative analysis of the effects of robots on introductory computer science education. J. Educ. Resour. Comput. (JERIC) 2(4) (2002)Google Scholar
  8. 8.
    Gomes, A., Mendes, A.J.: Learning to program-difficulties and solutions. In: International Conference on Engineering Education (ICEE’07), vol. 2007. Coimbra (2007)Google Scholar
  9. 9.
    Hernandez, C.C., Silva, L., Segura, R.A., Schimiguel, J., Ledón, M.F.P., Bezerra, L.N.M., Silveira, I.F.: Teaching programming principles through a game engine. CLEI Electron. J. 13(2), 3 (2010)Google Scholar
  10. 10.
    Hirst, A.J., Johnson, J., Petre, M., Price, B.A., Richards, M.: What is the best environment-language for teaching robotics using lego MindStorms? Artif. Life Robot. 7(3), 124–131 (2003)CrossRefGoogle Scholar
  11. 11.
    Keppel, G., Wickens, T.D.: Design and Analysis: A Researcher’s Handbook, 4th edn. Pearson (2004)Google Scholar
  12. 12.
    Lahtinen, E., Ala-Mutka, K., Jarvinen, H.M.: A study of the difficulties of novice programmers. ACM SIGCSE Bull. 37(3), 14–18 (2005)CrossRefGoogle Scholar
  13. 13.
    Leonard, D.C.: Learning Theories, A to Z. Oryx Press, Westport (2002)Google Scholar
  14. 14.
    Likert, R.: A technique for the measurement of attitudes. Arch. Psychol. 22(140), 1–55 (1932)Google Scholar
  15. 15.
    Malan, D.J., Leitner, H.H.: Scratch for budding computer scientists. ACM SIGCSE Bull. 39(1), 223–227 (2007)CrossRefGoogle Scholar
  16. 16.
    Orton-Johnson, K.: ‘I’ve stuck to the path I’m afraid’: exploring student non-use of blended learning. Br. J. Educ. Technol. 40(5), 837–847 (2009)CrossRefGoogle Scholar
  17. 17.
    Pap-Szigeti, R., Pásztor, A., Lakatos-Török, E.: Effects of using model robots in the education of programming. Inf. Educ.—Int. J. 9(1), 133–140 (2010)Google Scholar
  18. 18.
    Papert, S.: The Children’s Machine: Rethinking School in the Age of the Computer. BasicBooks, New York (1993)Google Scholar
  19. 19.
    Pásztor, A., Pap-Szigeti, R., Torok, E.: Mobile robots in teaching programming for IT engineers and its effects. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 4(1), 162–168 (2013)Google Scholar
  20. 20.
    Peña-Ayala, A.: Intelligent and Adaptive Educational-Learning Systems. Springer, Berlin (2013)zbMATHCrossRefGoogle Scholar
  21. 21.
    Renumol, V.G., Jayaprakash, S., Janakiram, D.: Classification of Cognitive Difficulties of Students to Learn Computer Programming. Tech. Rep. IITM-CSE-DOS-2009-01. Indian Institute of Technology Madras, India (2009)Google Scholar
  22. 22.
    Sartatzemi, M., Dagdilelis, V., Kagani, K.: Teaching introductory programming concepts with lego MindStorms in greek high schools: a two-year experience. In: Service Robot Applications. InTech (2008)Google Scholar
  23. 23.
    Shamlian, S., Killfoile, K., Kellogg, R., Duvallet, F.: Fun with robots: a student-taught undergraduate robotics course. In: IEEE International Conference on Robotics and Automation (ICRA’06), pp. 369–374 (2006)Google Scholar
  24. 24.
    Steckler, A., McLeroy, K.R., Goodman, R.M., Bird, S.T., McCormick, L.: Toward integrating qualitative and quantitative methods: an introduction. Health Educ. Behav. 19(1), 1–8 (1992)CrossRefGoogle Scholar
  25. 25.
    Wang, C., Dong, L., Li, C., Zhang, W., He, J.: The reform of programming teaching based on constructivism. In: Hu, W. (ed.) Advances in Electric and Electronics, no. 155 in Lecture Notes in Electrical Engineering, pp 425–431. Springer, Berlin Heidelberg (2012)Google Scholar
  26. 26.
    Wilson, A., Moffat, D.C.: Evaluating scratch to introduce younger schoolchildren to programming. In: Proceedings of the 22nd Annual Psychology of Programming Interest Group (2010)Google Scholar
  27. 27.
    Wu, C.C., Tseng, I.C., Huang, S.L.: Visualization of program behaviors: physical robots versus robot simulators. In: Mittermeir, R.T., Syslo, M.M. (eds.) Informatics Education—Supporting Computational Thinking, no. 5090 in Lecture Notes in Computer Science, pp 53–62. Springer, Berlin Heidelberg (2008)Google Scholar

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© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Languages and Computer SystemsUniversity of the Basque Country, UPV/EHUVitoria-GasteizSpain

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