Journal of East China Normal University(Natural Science) >

2024 , Vol. 2024 >Issue 5: 11 - 19

DOI: https://doi.org/10.3969/j.issn.1000-5641.2024.05.002

Learning Assessment and Recommendation

OpenRank contribution evaluation method and empirical study in open-source course

  • Jie WANG ,
  • Wenrui HUANG ,
  • Shengyu ZHAO ,
  • Xiaoya XIA ,
  • Fanyu HAN ,
  • Wei WANG ,
  • Yanbin ZHANG
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  • 1. School of Data Science and Engineering, East China Normal University, Shanghai　200062, China
    2. School of Electronic and Information Engineering, Tongji University, Shanghai　201804, China

Received date: 2024-07-08

  Online published: 2024-09-23

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Abstract

This study presents an OpenRank-based method for evaluating open-source contributions, designed to address the challenge of quantifying student contributions in open-source projects. Taking the “Open-Source Software Design and Development” course as a case study, we developed a method to assess student contributions in open-source practice. The OpenRank algorithm, which is based on developer collaboration networks, evaluates student contributions in discussions, problem-solving, and coding. Experimental results indicate that OpenRank not only aligns with traditional grading methods but also provides a more comprehensive view of student contributions. Combining OpenRank with traditional grading offers a more scientific and thorough evaluation of student contributions and skills in open-source projects.

Key words： open-source collaboration; open-source contribution; contribution evaluation; empirical research

Cite this article

Jie WANG , Wenrui HUANG , Shengyu ZHAO , Xiaoya XIA , Fanyu HAN , Wei WANG , Yanbin ZHANG . OpenRank contribution evaluation method and empirical study in open-source course[J]. Journal of East China Normal University(Natural Science), 2024 , 2024(5) : 11 -19 . DOI: 10.3969/j.issn.1000-5641.2024.05.002

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