Using Artificial Societies to Understand the Impact of Teacher Student Match on Academic Performance: The Case of Same Race Effects

被引:8
作者
Montes, Guillermo [1 ]
机构
[1] St John Fisher Coll, Rochester, NY 14618 USA
来源
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION | 2012年 / 15卷 / 04期
关键词
NetLogo; Agent Based Simulation; Racial Disparities; Achievement Gap; United States; VALUE-ADDED ASSESSMENT; COMPLEX-SYSTEMS; ACHIEVEMENT; EDUCATION; MATTER; MODEL; VIEW;
D O I
10.18564/jasss.2064
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
This paper presents an agent-based model of the standard U.S. k-12th grade classroom using NetLogo. By creating an artificial society, we identify the casual implications of the same-race effect (a moderate sized academic boost to students whose teachers have the same race) on the national educational achievement trends. The model predicts sizeable achievement gaps at the national level, consistent in size with those documented by the US National Report Card (NAEP) stemming from moderate sized same race effects. In addition, matching effects are found to be a source of increased heterogeneity in academic performance for the minority group. These results hold for all teacher-student matching phenomena and have implications for educational policy at the aggregate level. Using artificial societies to disentangle the aggregate effects of hypothesized causes of the achievement gap is a promising strategy that merits further research.
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页数:14
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