Improving College Choice in Centralized Admissions: Experimental Evidence on the Importance of Precise Predictions

IF 1.7 3区 教育学 Q2 ECONOMICS
Xiaoyang Ye
{"title":"Improving College Choice in Centralized Admissions: Experimental Evidence on the Importance of Precise Predictions","authors":"Xiaoyang Ye","doi":"10.1162/edfp_a_00397","DOIUrl":null,"url":null,"abstract":"\n This paper provides the first experimental evidence of how admission outcomes in centralized systems depend on strategic college choice behaviors. Centralized college admissions simplify the application process and reduce students' informational barriers. However, such systems also reward informed and strategic college choices. In particular, centralized admissions can be difficult to navigate because they require students to understand how application portfolios and placement priorities map to admission probabilities. Using administrative data from one of the poorest provinces in China, I document that students made undermatched college choices that correlated with inaccurate predictions of admission probabilities. I then implemented a large-scale randomized experiment (N=32,834) to provide treated students with either (a) an application guidebook or (b) a guidebook plus a school workshop. Results suggest that informing students on choosing colleges and majors based on precise predictions of admission probabilities can effectively improve student-college academic match by 0.1 to 0.2 standard deviations among compliers without substantially changing their college-major preferences.","PeriodicalId":46870,"journal":{"name":"Education Finance and Policy","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Education Finance and Policy","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1162/edfp_a_00397","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 2

Abstract

This paper provides the first experimental evidence of how admission outcomes in centralized systems depend on strategic college choice behaviors. Centralized college admissions simplify the application process and reduce students' informational barriers. However, such systems also reward informed and strategic college choices. In particular, centralized admissions can be difficult to navigate because they require students to understand how application portfolios and placement priorities map to admission probabilities. Using administrative data from one of the poorest provinces in China, I document that students made undermatched college choices that correlated with inaccurate predictions of admission probabilities. I then implemented a large-scale randomized experiment (N=32,834) to provide treated students with either (a) an application guidebook or (b) a guidebook plus a school workshop. Results suggest that informing students on choosing colleges and majors based on precise predictions of admission probabilities can effectively improve student-college academic match by 0.1 to 0.2 standard deviations among compliers without substantially changing their college-major preferences.
改善集中招生中的大学选择:精确预测重要性的实验证据
本文提供了第一个实验证据,证明集中式系统的录取结果如何依赖于战略性大学选择行为。高校集中招生简化了申请流程,减少了学生的信息障碍。然而,这样的系统也会奖励明智而有策略的大学选择。特别是,集中式招生可能很难驾驭,因为它们要求学生了解申请组合和安置优先级如何映射到录取概率。我利用中国最贫困省份之一的行政数据,证明了学生选择的大学不匹配,这与对录取概率的不准确预测有关。然后,我实施了一项大规模随机实验(N=32,834),为接受治疗的学生提供(a)申请指南或(b)指南加上学校研讨会。结果表明,基于录取概率的精确预测告知学生选择大学和专业,可以在不改变学生大学专业偏好的情况下,有效地将学生与大学的学业匹配度提高0.1至0.2个标准差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.00
自引率
4.80%
发文量
46
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信