Social, Behavioral, and Academic Linkages throughout the Undergraduate Experience

高等教育的结果是个人的个性特征和大学经历的许多方面的结果。加州理工学院队列研究（CCS）将在数年内追踪加州理工学院（Caltech）的整个本科生群体。它使用重复的、激励的调查来引出行为代理：风险规避、战略复杂性、竞争力、社会行为等。结果将与客观结果相结合：学术、社会和经济。该项目将考察学生在大学期间性格特征的演变、社会互动的形成，以及最终某些性格特征是如何相互作用产生教育成果的。CCS也为回答关于激励调查和实验室实验的外部有效性的基本问题提供了一个理想的环境。CCS有四个独特的特点。首先，加州理工学院规模小，可以长期跟踪几乎整个学生群体（90%的学生完成了前三个调查）。其次，调查设计允许测量每个人的大量行为特征。第三，这项研究的重复性使得在最小的选择偏差的情况下追踪这些特征的稳定性成为可能。第四，所引出的一系列行为特征可以与现实世界的行为和结果联系起来。这些要素的结合对于大量的基础社会科学问题来说是无价的。本研究具有改善美国高等教育教育过程的潜力。了解影响社会和学业成绩的因素将有助于设计大学教育的某些方面，旨在提高幸福感和学习成绩，以及促进性别和种族平等。该提案侧重于三个方面。首先，数据集的纵向性质将允许仔细检查一系列行为属性的稳定性（或缺乏稳定性）。其次，随着时间的推移，不同层次的互动（社会的、学术的和地理的）的丰富数据与得到的综合属性相结合，将使我们能够研究网络形成过程。最后，这些数据可以与加州理工学院的实验实验室数据进行交叉核对，以检查选择对实验的影响，以及实验室内外反应的差异。该调查还将允许对其他平台和人群的反应进行比较。最终，收集到的详细的纵向数据有可能揭示学业成绩的预测因素（所选专业、成绩和毕业），以及影响不同特征演变的渠道。

The outcomes of higher education are a consequence of individuals' personality traits and manydimensions of the university experience. The Caltech Cohort Study (CCS) will track the entireundergraduate student body of the California Institute of Technology (Caltech) over several years. Ituses repeated, incentivized surveys to elicit behavioral proxies: risk aversion, strategic sophistication,competitiveness, social behavior, etc. The results will be married with objective outcomes: academic,social, and financial. The project will examine the evolution of attributes over college years, theformation of social interactions, and ultimately how certain attributes interact to produce educationaloutcomes. The CCS also serves as an ideal environment for answering fundamental questions aboutthe external validity of incentivized surveys and laboratory experiments.The CCS has four unique features. First, Caltech's small size makes it possible to track nearlythe entire student body over time (90% of students completed the first three surveys). Second, thesurvey design allows measurement of a large set of behavioral traits for each individual. Third,the repeated nature of the study makes it possible to track the stability of these traits across timewith minimal selection bias. Fourth, the array of behavioral traits elicited can be tied to real-worldbehaviors and outcomes. The combination of these elements should be invaluable for a large batteryof basic social science questions.The proposed study has the potential to improve the educational process in US higher education.Understanding what impacts social and scholastic outcomes will help design certain aspects of collegeeducation aimed at increasing well-being and academic performance, as well as furthering gender andracial equality.The proposal focuses on three areas. First, the dataset's longitudinal nature will allow for a carefulinspection of the stability (or lack thereof) of a wide array of behavioral attributes. Second, the richdata on different layers of interactions over time (social, academic, and geographic) combined withthe comprehensive set of elicited attributes will allow us to study network formation processes. Last,the data can be cross-checked against Caltech's experimental laboratory data to examine the impactsof selection into experiments as well as the differences in responses occurring in the lab and outside.The survey will also allow for a comparison of responses across other platforms and populations.Ultimately, the detailed longitudinal data that will be collected have the potential to uncoverpredictors of academic outcomes (chosen major, grades, and graduation), and the channels affectingthe evolution of different traits.