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An early software engineering approach to teaching cs1, cs2 and ai

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Published:12 March 2008Publication History

ABSTRACT

We propose the use of a new design-first approach called Problem Stereotypes and Solution Frameworks, for teaching CS1 and CS2. A problem stereotype is a category of problems that can be solved using similar techniques. A solution framework is a typical solution to a problem, parts of which can be reused to solve other problems of this stereotype. Students are introduced to a stereotype through a selection of related problems, and common features among these are identified. Homework problems are selected from the same stereotype, with students expected to follow the "recipe" provided by the given examples to generate their own solutions. Using this approach reduces the stress level for beginner students, and prevents them falling prey to the "CS is HARD" myth. We present the results of our experience with this approach in two introductory classes and an upper-division Artificial Intelligence (AI) class at SUNY Brockport.

References

  1. Barnes, D. J., Koelling, M., Objects First with Java: A Practical Introduction Using BlueJ, Upper Saddle River, NJ: Prentice-Hall, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bennedsen, J., and Caspersen, M.E., Programming in Context - A Model-First Approach to CS1, Proceedings of the 35th SIGCSE Technical Symposium on Computer Science Education, March 3--7th, 2004, Norfolk, VA, USA, pp.477--481. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bergin, J., Fourteen Pedagogical Patterns, 2000, http://csis.pace.edu/~bergin/PedPat1.3.html, retrieved January 17, 2007.Google ScholarGoogle Scholar
  4. Clements, P., Northrup, L., Software Product Lines: Practices and Patterns, Boston, MA: Addison-Wesley Professional, 2002.Google ScholarGoogle Scholar
  5. Luger, G. F., Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5th Edition, Boston, MA: Addison-Wesley, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Mitra, S., Rao, T.M., and Bullinger, T.A., Teaching Software Engineering Using a Traceability-Based Development Methodology, Journal of Computing in Colleges, 20(5), June 2005, pp.249--259. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Proulx, V. K., Gray, K. E., Design of Class Hierarchies -- An Introduction to OO Program Design, Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education, March 1-5-5-5th, 2006, Houston, TX, USA, pp. 288--292. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Rao, T.M. Using Java to teach AI, T.M. Rao, The Journal of Computing Sciences in Colleges, 18, 3 (Feb. 2003), 114--125. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Rao, T.M., Mitra, S., Canosa, R., Marshall, S., Bullinger, T., Problem Stereotypes and Solution Frameworks - A Design First Approach for the Introductory Computer Science Sequence The Journal of Computing Science in Colleges, 22, 6, (June 2007), 56--6 Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          SIGCSE '08: Proceedings of the 39th SIGCSE technical symposium on Computer science education
          March 2008
          606 pages
          ISBN:9781595937995
          DOI:10.1145/1352135

          Copyright © 2008 ACM

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          New York, NY, United States

          Publication History

          • Published: 12 March 2008

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