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abstract

Teaching and Learning Under Pressure: Intensive (Accelerated, Block) Computer Science Courses (Abstract Only)

Published:08 March 2017Publication History

ABSTRACT

Many universities either have offered or are starting to offer computer science courses taught in a compressed time scale, often where students take only one course at a time. The pace of these classes can differ but often move at a speed where a day of an accelerated class is equivalent to a week of a typical semester class. This format has several advantages-more flexibility for collaborative work, better visibility into how students are spending their time (knowing that if a student is struggling it is not because of work in a different class), and less need for students to multitask between different courses. It also has many challenges. From the student perspective, there's the need to stay on top of things and not fall behind, having to catch up if there are absences due to illness or extra-curricular activities, and staying focused on one subject while working under constant time pressure (which often results in a tendency to rush through assignments to meet deadlines). Participants in this BoF will share their knowledge about teaching in this format. What kinds of assignments and assessments work and don't work during accelerated courses? How can we keep the workload reasonable for the students and for ourselves? What interesting pedagogy does this format facilitate? We invite participation both from faculty who are already teaching in this format and also from those considering an accelerated course who want to learn more about the advantages and disadvantages of this format.

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  1. Teaching and Learning Under Pressure: Intensive (Accelerated, Block) Computer Science Courses (Abstract Only)

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      • Published in

        cover image ACM Conferences
        SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
        March 2017
        838 pages
        ISBN:9781450346986
        DOI:10.1145/3017680

        Copyright © 2017 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: 8 March 2017

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        Qualifiers

        • abstract

        Acceptance Rates

        SIGCSE '17 Paper Acceptance Rate105of348submissions,30%Overall Acceptance Rate1,595of4,542submissions,35%

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