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Peer Instruction in Computing: A Focus on Student Learning (Abstract Only)

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Published:17 February 2016Publication History

ABSTRACT

Recent work in computing has converged on a collection of complementary findings suggesting the value of the Peer Instruction (PI) pedagogy. Compared to lecture, PI has been shown to decrease fail rates, increase final exam grades, and increase engagement and enjoyment. In PI, students work together to exchange perspectives and use clickers to answer challenging conceptual questions in the presence of a knowledgeable instructor.

In our efforts to mentor potential PI adopters, we note difficulties bootstrapping PI uptake at new institutions and new departments. In this workshop, our main goal is to support potential adopters in the process of shifting from lectures to PI. In recent months, we have contributed materials for many freely-available PI courses, and led a successful 3-day NSF-funded PI workshop. We will work with participants and their existing lecture-based resources to begin considering the ways that PI can enhance student learning.

Instructors interested in increasing engagement in any CS course may attend. Participants are encouraged to bring current lecture materials. Laptop optional.

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  1. Peer Instruction in Computing: A Focus on Student Learning (Abstract Only)

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    • Published in

      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 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 17 February 2016

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      Acceptance Rates

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

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