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The Department of Science Teaching
Weizmann Institute of Science
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  5. Teaching Reduction as an Algorithmic Problem-Solving Strategy

Teaching Reduction as an Algorithmic Problem-Solving Strategy

  • General background
  • Chemistry
  • Computational approaches in Science Education
  • Computer Science
    • About
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    • Teaching resources
    • Books (in Hebrew)
  • Earth Science
  • Interdisciplinary Science Education
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Leading team:

  • Prof. Michal Armoni
  • Dr. Iris Gaber, The Academic College of Tel-Aviv Yaffo
  • Dr. David Statter, Afeka Academic College of Engineering

Brief

Reduction is a powerful tool in computer science. This study examines a new strategy for teaching reduction in an explicit fashion, as part of an undergraduate Algorithms course.

 

 

The relevance of reduction, a fundamental idea and a powerful tool in computer science, spans multiple contexts across the field of CS, including algorithmic design, data structures, computability theory, and complexity theory. However, in most CS curricula, reduction is insufficiently emphasized and limited to some specific contexts. This project examines the applicability and effectiveness of a new instructional strategy for teaching reduction in an undergraduate course on algorithmic design.

Further reading:

  • Armoni, M., & Gal-Ezer, J. (2005). Teaching reductive thinking. Mathematics and Computer Education, 39(2), 131-142.
  • Armoni, M., Gal-Ezer, J., & Tirosh, D. (2005). Solving problems reductively. Journal of Educational Computing Research, 32(2), 113-129.
  • Armoni, M., & Gal-Ezer, J. (2006). Reduction – an abstract thinking pattern: The case of the computational models course. In Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education (SIGCSE’06), Houston, TX, USA, 389-393.
  • Armoni, M., Gal-Ezer, J., & Hazzan, O. (2006). Reductive thinking in undergraduate CS courses. In Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE’06), Bologna, Italy, 133-137.
  • Armoni, M., Gal-Ezer, J., & Hazzan O. (2006). Reductive thinking in computer science. Computer Science Education, 16(4), 281-301.
  • Armoni, M. (2008). Reductive thinking in a quantitative perspective: The case of the algorithm course. In Proceedings of the 13th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE08), Madrid, Spain, 53-57.
  • Armoni, M. (2009). Reduction in CS: A (mostly) quantitative analysis of reductive solutions to algorithmic problems. Journal on Educational Resources in Computing, 8(4), 11:1-30.
  • Gaber, I., Armoni, M., & Statter, D. Teaching Reduction as an Algorithmic Problem-Solving Strategy. Accepted to the 3rd International Conference on Computer Science and Technologies in Education (CSTE 2021), Beijing, China.
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