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IJIET 2019 Vol.9(7): 470-476 ISSN: 2010-3689
doi: 10.18178/ijiet.2019.9.7.1248

Teaching Methods for Computer Science Education in the Context of Significant Learning Theories

Andreas Zendler

Abstract—Answers to the questions of which teaching methods are suitable for school and should be applied in teaching individual subjects and also how teaching methods support them act of learning represent challenges to general education and education in individual subjects. This study focuses on teaching methods for computer science education with respect to significant learning theories. Using an expert survey, subjects rated the importance of behavioristic, cognitivist and constructivist learning theories for 20 teaching methods. The result of the study makes it clear that the importance of learning theories for certain teaching methods in computer science education is different. Teaching methods can be assigned to learning theories and can benefit from the empirical findings of the learning theories. Moreover, the result is an important contribution to the development of a theory of teaching methods for computer science education, which is still lacking.

Index Terms—Computer science education, instructional methods, teaching methods, theories of learning, act of learning.

The author is with Universiyt of Education Ludwigsburg, Germany (e-mail: zendler@ph-ludwigsburg.de).


Cite: Andreas Zendler, "Teaching Methods for Computer Science Education in the Context of Significant Learning Theories," International Journal of Information and Education Technology vol. 9, no. 7, pp. 470-476, 2019.

Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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