你认识的人重要吗?揭示学生网络对学习成绩的影响

Tarun Jain, Nishtha Langer
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引用次数: 3

摘要

本文考察了学生的网络规模、距离、声望和与有影响力个人的联系对学业成绩的影响。更大、更紧密的网络促进了信息交换,但也可能增加干扰,降低生产力。为了解决这种模糊性,我们使用了来自商学院的管理数据,该数据的特点是将学生随机分配到多个重叠的同行集合,使我们能够计算每个节点的程度、亲密度、特征向量和卡兹-波纳奇中心性,以及一个明确定义的学术成就衡量标准。我们发现,以平均成绩衡量,网络中特征向量中心性的增加对学生的表现有负面影响,这表明协同效应的减少和信息处理成本超过了更多信息获取带来的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Does Who You Know Matter? Unraveling the Influence of Student Networks on Academic Performance
This paper examines the impact of students' network size, distance, prestige and connections to influential individuals on academic performance. Larger and closer networks facilitate information exchange, but may also increase distractions that decrease productivity. To resolve this ambiguity, we use administrative data from a business school setting that features both randomly assignment of students to multiple overlapping sets of peers, allowing us to calculate degree, closeness, eigenvector and Katz-Bonacich centrality for each node, as well as a cleanly defined measure of academic achievement. We find that increasing eigenvector centrality within the network has a negative effect on student performance as measured by grade point average, suggesting that synergy reduction and information processing costs outweigh benefits from greater information access.
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