Learning styles: novices decide

ABSTRACT

We present what students say about their preferred learning style to succeed in introductory programming. Using the Felder-Silverman learning styles, students contrasted the 'best' learning style for programming with the 'best' for learning mathematics. Overall students believe that while they learn mathematics using a reflective style, learning to program is significantly more active. They also believe learning mathematics has a strong verbal component, whereas learning programming is primarily visual.

References

1. Allert, J. 2004. Learning style and factors contributing to success in an introductory computer science course. In Proceedings of the IEEE International Conference on Advanced Learning Technologies (August, 2004). ICALT'04. IEEE, 385--389.
2. Eckerdal, A., Thuné, M., and Berglund, A. 2005. What does it take to learn 'programming thinking'?. In Proceedings, ICER '05 (Seattle, WA, USA, October, 2005). ACM, New York, NY, 135--142.
3. Felder, R.M. and Silverman, L.K. 1988. Learning and Teaching Styles in Engineering Education. Engineering Education. 78, 7 (1988), 674--681.
4. Felder, R.M. and Spurlin, J. 2005. Applications, Reliability and Validity of the Index of Learning Styles. Int Journal of Engineering Education. 21, 1 (2005), 103--112.
5. Garvin--Doxas, K. and Barker, L. J. 2004. Communication in computer science classrooms: understanding defensive climates as a means of creating supportive behaviors. J. Educ. Resour. Comput. 4, 1 (Mar. 2004), 2.
6. Layman, L., Cornwell, T., and Williams, L. 2006. Personality types, learning styles, and an agile approach to software engineering education. SIGCSE Bull. 38, 1 (March 2006), 428--432.
7. Lister, R., Berglund, A., Clear, T., Bergin, J., Garvin-Doxas, K., Hanks, B., Hitchner, L., Luxton-Reilly, A., Sanders, K., Schulte, C., and Whalley, J. L. 2006. Research perspectives on the objects-early debate. In Working Group Reports on ITiCSE (Bologna, Italy, June, 2006). ACM, New York, NY, 146--165.
8. Lopes, W.M.G. 2002. ILS-Inventário de Estilos de Aprendizagem de Felder-Soloman: Investigação de sua Validade em Estudantes Universitários de Belo Horizonte, Masters Thesis, Universidade Federal de Santa Caterina, Brazil, 2002. Quoted in {4}.
9. Mead, J., Gray, S., Hamer, J., James, R., Sorva, J., Clair, C. S., and Thomas, L. 2006. A cognitive approach to identifying measurable milestones for programming skill acquisition. In Working Group Reports on ITiCSE (Bologna, Italy, June, 2006). ACM, New York, NY, 182--194.
10. Muller, O. 2005. Pattern oriented instruction and the enhancement of analogical reasoning. In Proceedings, ICER'05 (Seattle, WA, USA, 2005). ACM, New York, NY, 57--67.
11. Murphy, L. and Thomas, L. 2008. Dangers of a fixed mindset: implications of self-theories research for computer science education. In Proceedings of the 13th Annual Conference on ITiCSE (Madrid, Spain, June, 2008). ACM, New York, NY, 271--275.
12. Thomas, L., Ratcliffe, M., Woodbury, J., and Jarman, E. 2002. Learning styles and performance in the introductory programming sequence. In Proceedings of the 33rd SIGCSE Technical Symposium (Cincinnati, Kentucky, February, 2002). ACM, New York, NY, 33--37.
13. Tobias, S. 1990. They're Not Dumb, They're Different: Stalking the Second Tier. Research Corporation, Tucson.
14. Turner, E. H., Albert, E., Turner, R. M., and Latour, L. 2007. Retaining majors through the introductory sequence. In Proceedings of the 38th SIGCSE Technical Symposium (Covington, Kentucky, USA, March, 2007). ACM, New York, NY, 24--28.
15. Wu, C., Dale, N. B., and Bethel, L. J. 1998. Conceptual models and cognitive learning styles in teaching recursion. In Proceedings of the Twenty-Ninth SIGCSE Technical Symposium (Atlanta, Georgia, United States, February, 1998). ACM, New York, NY, 292--296.

Index Terms

• Social and professional topics

  • Professional topics

    • Computing education

      • Computing education programs

        • Computer science education

        • Information science education