Abstract
Peer Instruction (PI) is an active learning pedagogical technique. PI lectures present students with a series of multiple-choice questions, which they respond to both individually and in groups. PI has been widely successful in the physical sciences and, recently, has been successfully adopted by computer science instructors in lower-division, introductory courses. In this work, we challenge readers to consider PI for their upper-division courses as well. We present a PI curriculum for two upper-division computer science courses: Computer Architecture and Theory of Computation. These courses exemplify several perceived challenges to the adoption of PI in upper-division courses, including: exploration of abstract ideas, development of high-level judgment of engineering design trade-offs, and exercising advanced mathematical sophistication. This work includes selected course materials illustrating how these challenges are overcome, learning gains results comparing these upper-division courses with previous lower-division results in the literature, student attitudinal survey results (N = 501), and pragmatic advice to prospective developers and adopters. We present three main findings. First, we find that these upper-division courses achieved student learning gains equivalent to those reported in successful lower-division computing courses. Second, we find that student feedback for each class was overwhelmingly positive, with 88% of students recommending PI for use in other computer science classes. Third, we find that instructors adopting the materials introduced here were able to replicate the outcomes of the instructors who developed the materials in terms of student learning gains and student feedback.
- Beatty, I. D., Gerace, W. J., Leonard, W. J., and Dufresne, R. J. 2006. Designing effective questions for classroom response system teaching. Amer. J. Phys. 74, 1, 31--39.Google ScholarCross Ref
- Caldwell, J. E. 2007. Clickers in the large classroom: Current research and best-practice tips. CBE-Life Sci. Educ. 6, 1, 9--20.Google Scholar
- Carter, P. 2009. An experiment with online instruction and active learning in an introductory computing course for engineers: JiTT meets cs. In Proceedings of the 14th Western Canadian Conference on Computing Education. Google ScholarDigital Library
- Chesñevar, C. I., Maguitman, A. G., González, M. P., and Cobo, M. L. 2004. Teaching fundamentals of computing theory: A constructivist approach. J. Comput. Sci. Technol. 4, 2.Google Scholar
- Crouch, C. H. and Mazur, E. 2001. Peer instruction: Ten years of experience and results. Amer. J. Phys. 69, 970--977.Google ScholarCross Ref
- Cwsei - Carl Wieman Science Education Initiative at the University of British Columbia. 2012. Clicker resource guide. http://cwsei.ubc.ca/resources/clickers.htm.Google Scholar
- Dimitriadis, Y. A., Martinez, A., Rubia, B., and Gallego, M. J. 2001. Cooperative learning in computer architecture: An educational project and its network support. In Proceedings of the 31st Annual Frontiers in Education Conference. T4B-13-18. Google ScholarDigital Library
- Djordjevic, J., Milenkovic, A., Todorovic, I., and Marinov, D. 1999. CALKAS: A computer architecture learning and knowledge assessment system. In Proceedings of the Workshop on Computer Architecture Education (WCAE-5'99). Google ScholarDigital Library
- Gramond, E. and Rodger, S. H. 1999. Using jflap to interact with theorems in automata theory. In Proceedings of the 13th SIGCSE Technical Symposium on Computer Science Education. 336--340. Google ScholarDigital Library
- Hake, R. R. 1998. Interactive-engagement vs. traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. Amer. J. Phys. 66, 1.Google ScholarCross Ref
- Knight, J. K. and Wood, W. B. 2005. Teaching more by lecturing less. Cell Biol. Educ. 4, 4, 298--310.Google ScholarCross Ref
- Mcluhan, M. 1964. Understanding Media: The Extensions of Man. McGraw Hill, New York.Google Scholar
- Pargas, R. P. and Shah, D. M. 2006. Things are clicking in computer science courses. In Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education. Google ScholarDigital Library
- Patterson, D. A. and Hennessy, J. L. 2008. Computer Organization and Design: The Hardware/Software Interface. Morgan-Kaufmann, San Fransisco. Google ScholarDigital Library
- Porter, L., Bailey-Lee, C., Simon, B., Cutts, Q., and Zingaro, D. 2011a. Experience report: A multi-classroom report on the value of peer instruction. In Proceedings of the 16th Annual Conference on Innovation and Technology in Computer Science Education. Google ScholarDigital Library
- Porter, L., Bailey-Lee, C., Simon, B., and Zingaro, D. 2011b. Do students really learn from peer discussion in computing? In Proceedings of the 7th International Computing Education Research Workshop. Google ScholarDigital Library
- Rodger, S. 2009. JFLAP. Automata simulation software, version 7.0. http://www.jflap.org.Google Scholar
- Simon, B. and Snowdon, S. 2011. Explaining program code: Giving students the answer helps - But only just. In Proceedings of 7th International Computing Education Research Workshop. Google ScholarDigital Library
- Simon, B. 2012. Getting started with peer instruction in computing: The details. http://cseweb.ucsd.edu/∼bsimon/PI/.Google Scholar
- Simon, B., Kohanfars, M., Lee, J., Tamayo, K., and Cutts, Q. 2010. Experience report: Peer instruction in introductory computing. In Proceedings of the 41st SIGCSE Technical Symposium on Computer Science Education. Google ScholarDigital Library
- Sipser, M. 2006. Introduction to the Theory of Computation 2nd Ed. PWS Publishing.Google Scholar
- Smith, M., Wood, W., Adams, W., Wieman, C., Knight, J., Guild, N., and Su, T. 2009. Why peer discussion improves student performance on in-class concept questions. Sci. 323, 5910, 122--124.Google Scholar
- Turing, A. M. 1936. On computable numbers, with an application to the entscheidungs problem. In Proceedings of the London Mathematical Society. s2-42.Google Scholar
- Yehezkel, C., Ben-Ari, M., and Dreyfus, T. 2005. Computer architecture and mental models. In Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education. Google ScholarDigital Library
- Yurcik, W., Wolffe, G. S., and Holliday, M. A. 2001. A survey of simulators used in computer organization/architecture courses. In Proceedings of the Summer Computer Simulation Conference (SCSC'01). Society for Computer Simulation International, 524--529.Google Scholar
- Zingaro, D. 2010. Experience report: Peer instruction in remedial computer science. In Proceedings of the 22nd World Conference on Educational Multimedia, Hypermedia and Telecommunications.Google Scholar
Index Terms
- Can peer instruction be effective in upper-division computer science courses?
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