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Learning Networking by Reproducing Research Results

Published:23 June 2020Publication History

ABSTRACT

Reproducing research is key to continued scientific progress, especially in fields that are engineering- and application-focused. In the past eight years, the graduate computer networking course at Stanford University has asked students to reproduce research results for a different reason: to teach students engineering rigor and critical thinking-qualities that are essential for careers in networking research and industry. In this talk, I share our experience with teaching over 500 students the art of reproducing results from over 50 networking papers. Over the past eight years, we have observed through many anecdotes that the process of reproducing research can both teach much-needed skills and provide students with a means to contribute to the networking community. I will close by discussing how to teach the importance of reproducibility through project-based learning and how to implement this project in different computing fields.

References

  1. L. Yan. Tools to Understand How Students Learn. PhD thesis, Stanford University, 2019.Google ScholarGoogle Scholar
  2. L. Yan and N. McKeown. Learning Networking by Reproducing Research Results. SIGCOMM Comput. Commun. Rev., 47(2):19--26, 2017.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Learning Networking by Reproducing Research Results

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        cover image ACM Conferences
        P-RECS '20: Proceedings of the 3rd International Workshop on Practical Reproducible Evaluation of Computer Systems
        June 2020
        38 pages
        ISBN:9781450379779
        DOI:10.1145/3391800

        Copyright © 2020 Owner/Author

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 23 June 2020

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