Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, October 13–15, 2023, Xi’an, China

Research Article

Factors Influencing Unfair Behavior in Peer Assessment: Evidence from a Situational Experiment

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  • @INPROCEEDINGS{10.4108/eai.13-10-2023.2341083,
        author={Haijia  Liu and Yuqiang  Feng},
        title={Factors Influencing Unfair Behavior in Peer Assessment: Evidence from a Situational Experiment},
        proceedings={Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, October 13--15, 2023, Xi’an, China},
        publisher={EAI},
        proceedings_a={NMDME},
        year={2024},
        month={1},
        keywords={unfair behavior reviews helpfulness information framework score bias},
        doi={10.4108/eai.13-10-2023.2341083}
    }
    
  • Haijia Liu
    Yuqiang Feng
    Year: 2024
    Factors Influencing Unfair Behavior in Peer Assessment: Evidence from a Situational Experiment
    NMDME
    EAI
    DOI: 10.4108/eai.13-10-2023.2341083
Haijia Liu1,*, Yuqiang Feng1
  • 1: Harbin Institute of Technology
*Contact email: 1071606947@qq.com

Abstract

We explored the influence of different factors on unfair behavior in peer assessment and designed interventions aimed to reduce the occurrence of unfair behavior. Different peer information will affect students' attitudes and behavior toward peer assessment. We analyze the influence of different helpful reviews. Based on social value orientation theory, we developed novel information frameworks in combination with cooperation (e.g., your behaviors benefit others) and competition (e.g., your behaviors benefit yourself more than others). We invited real students who use peer assessment to a situational experiment, conducted a covariance analysis, . We tested peer reviews that provided different levels of helpfulness and found that high review helpfulness helped reduce the incidence of unfair behavior. Both the competition and cooperation frameworks can effectively reduce the occurrence of unfair behavior, with the competition framework more effective. Our work identifies the influence of peer information on unfair behavior in peer assessment, and the results suggest that use of an information framework could reduce this behavior. Our research extends studies of peer assessment and provides feasible practical methods.