Social, Behavioral, and Academic Linkages throughout the Undergraduate Experience

高等教育的结果是个人的人格特质和大学经历的许多方面的结果。加州理工学院队列研究（CCS）将在几年内跟踪加州理工学院（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：学术，社会和财务相结合。该项目将研究属性在大学期间的演变，社会互动的形成，以及最终某些属性如何相互作用以产生教育成果。CCS还为回答激励调查和实验室实验的外部效度的基本问题提供了理想的环境。首先，加州理工学院的规模很小，这使得它可以随着时间的推移跟踪几乎整个学生群体（90%的学生完成了前三次调查）。其次，调查设计允许测量每个人的大量行为特征。第三，研究的重复性使得在最小选择偏差的情况下跟踪这些特征的稳定性成为可能。第四，由此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。这些因素的结合对于一系列基础社会科学问题来说应该是非常宝贵的。这项拟议中的研究有可能改善美国高等教育的教育过程。了解什么会影响社会和学术成果，将有助于设计大学教育的某些方面，旨在提高福祉和学术成绩，以及促进性别和种族平等。这项建议侧重于三个领域。首先，数据集的纵向性质将允许对广泛的行为属性的稳定性（或缺乏稳定性）进行仔细检查。第二，随着时间的推移，不同层次的互动（社会，学术和地理）的丰富数据与综合的一套引发属性相结合，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室数据进行交叉检查，以检查实验选择的影响以及实验室内外的反应差异。该调查还可以比较其他平台和人群的反应。最终，收集的详细纵向数据有可能揭示学术成果的预测因素（选择专业、年级、毕业），以及影响不同特质演变的渠道。

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.