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A Multi-institutional Study of Peer Instruction in Introductory Computing

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Published:17 February 2016Publication History

ABSTRACT

Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants in the classroom. Over the past five years, there have been a number of research articles regarding the value of PI in computer science. The present work adds to this body of knowledge by examining outcomes from seven introductory programming instructors: three novices to PI and four with a range of PI experience. Through common measurements of student perceptions, we provide evidence that introductory computing instructors can successfully implement PI in their classrooms. We find encouraging minimum (74%) and average (92%) levels of success as measured through student valuation of PI for their learning. This work also documents and hypothesizes reasons for comparatively poor survey results in one course, highlighting the importance of the choice of grading policy (participation vs. correctness) for new PI adopters.

References

  1. C. H. Crouch and E. Mazur. Peer instruction: Ten years of experience and results. American Journal of Physics, 69, 2001. Google ScholarGoogle ScholarCross RefCross Ref
  2. D. Duncan. Tips for Successful "Clicker" Use, 2008. Accessed 8/24/15.Google ScholarGoogle Scholar
  3. M. Guzdial. A media computation course for non-majors. ACM SIGCSE Bulletin, 35(3):104--108, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. R. R. Hake. Interactive-engagement vs. traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 1998. Google ScholarGoogle ScholarCross RefCross Ref
  5. C. B. Lee, S. Garcia, and L. Porter. Can peer instruction be effective in upper-division computer science courses? Transactions on Computing Education, 13(3):12:1--12:22, Aug. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Porter, C. Bailey Lee, and B. Simon. Halving fail rates using peer instruction: A study of four computer science courses. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. L. Porter, C. Bailey-Lee, B. Simon, and D. Zingaro. Peer instruction: Do students really learn from peer discussion in computing? In 7th Annual International Computing Education Research Workshop, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. L. Porter, S. Garcia, J. Glick, A. Matusiewicz, and C. Taylor. Peer instruction in computer science at small liberal arts colleges. In Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. L. Porter and B. Simon. Retaining nearly one-third more majors with a trio of instructional best practices in cs1. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. B. Simon, M. Kohanfars, J. Lee, K. Tamayo, and Q. Cutts. Experience report: Peer instruction in introductory computing. In Proceedings of the 41st SIGCSE technical symposium on computer science education, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. B. Simon, J. Parris, and J. Spacco. How we teach impacts student learning: Peer instruction vs. lecture in cs0. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C. Wieman. Clicker Resource Guide. CWSEI - Carl Wieman Science Education Initiative at the University of British Columbia, 2015. Accessed 8/24/15.Google ScholarGoogle Scholar
  13. D. Zingaro. Peer instruction contributes to self-efficacy in cs1. In Proceedings of the 45th ACM technical symposium on Computer Science Education, pages 373--378, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D. Zingaro, C. Bailey Lee, and L. Porter. Peer instruction in computing: The role of reading quizzes. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. D. Zingaro and L. Porter. Peer instruction in computing: The value of instructor intervention. Computers & Education, 71:87--96, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. A Multi-institutional Study of Peer Instruction in Introductory Computing

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      cover image ACM Conferences
      SIGCSE '16: Proceedings of the 47th ACM Technical Symposium on Computing Science Education
      February 2016
      768 pages
      ISBN:9781450336857
      DOI:10.1145/2839509

      Copyright © 2016 ACM

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      New York, NY, United States

      Publication History

      • Published: 17 February 2016

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      SIGCSE '16 Paper Acceptance Rate105of297submissions,35%Overall Acceptance Rate1,595of4,542submissions,35%

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