Abstract
Instructional design has a significant influence on the construction of knowledge, especially for novices. Specifically, the way the instruction of algorithmic problem solving is designed has a significant effect on the development of the student’s capabilities to analyze and solve problems. We present a pedagogical approach regarding teaching algorithmic problem solving, which is based on the assimilation of a new concept by demonstrating its different facets through a variety of relevant examples. The approach aims to support multi-facet problem comprehension, as well as to enhance the student’s ability to utilize algorithmic ideas in different contexts. The approach was introduced to computer science teachers through a workshop activity aimed at discussing the topic of evaluating the complexity level of problems and their challenging characteristics. We think that an activity of this kind is beneficial for raising teachers’ awareness of the way they select problems in order to develop students’ problem-solving skills.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Fleury, A.E.: Encapsulation and reuse as viewed by Java students. In: Proceedings of the 31th SIGCSE Technical Symposium on CS Education, pp. 189–193 (2001)
Ginat, D., Haberman, B., Cohen, D., Catz, D., Muller, O., Menashe, E.: Patterns in computer science. Tel- Aviv University (in Hebrew) (2001)
Hoare, C.A.R., Jones, C.B.: Essays in Computing Science. Prentice-Hall International, Englewood Cliffs (1989)
Linn, M.C., Clancy, M.J.: The case for case studies of programming problems. Communications of the ACM 35(3), 121–132 (1992)
Marshall, S.P.: Schemas in problem solving. Cambridge University Press, New York (1995)
Muller, O., Haberman, B., Averbuch, H.: (An almost) pedagogical pattern for pattern-based problem-solving instruction. In: Proceedings of ITiCSE 2004, Leeds, UK, pp. 102–106 (2004)
Muller, O.: Pattern oriented instruction and the enhancement of analogical reasoning. In: Proceedings of the 1st International Computing Education Research (ICER) Workshop, pp. 57–67 (2005)
Muller, O.: The effect of pattern-oriented instruction in computer-science on algorithmic problem-solving skills. Doctoral dissertation, Tel-Aviv University, Israel (2007)
Perkins, D.N., Martin, F.: Fragile knowledge and neglected strategies in novice programmers. In: Soloway, E., Iyengar, S. (eds.) Empirical Studies of Programmers, pp. 213–229. Albex Publishing Corporation, Norwood, New Jersey (1986)
Rist, R.S.: Schema creation in programming. Cognitive Science 13, 389–414 (1989)
Robins, A.: Transfer in cognition. Connection Science 8(2), 185–203 (1996)
Robins, S., Mayer, R.E.: Schema training in analogical reasoning. Journal of educational Psychology 85(3), 529–538 (1993)
Samurcay, R.: The concept of variable in programming: its meaning and use in problem-solving by novice programmers. In: Soloway, E., Spohrer, J.C. (eds.) Studying the Novice Programmer. Lawrence Erlbaum Associates, Hillsdale (1989)
Soloway, E.: From problems to programs via plans: the content and structure of knowledge for introductory lisp programming. J. Educational Computing Research 1(2), 157–172 (1985)
Wing, J.M.: Computational thinking. Communication of the ACM 49(3), 33–35 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Haberman, B., Muller, O., Averbuch, H. (2008). Multi-facet Problem Comprehension: Utilizing an Algorithmic Idea in Different Contexts. In: Mittermeir, R.T., Sysło, M.M. (eds) Informatics Education - Supporting Computational Thinking. ISSEP 2008. Lecture Notes in Computer Science, vol 5090. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69924-8_17
Download citation
DOI: https://doi.org/10.1007/978-3-540-69924-8_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69923-1
Online ISBN: 978-3-540-69924-8
eBook Packages: Computer ScienceComputer Science (R0)