Social, Behavioral, and Academic Linkages throughout the Undergraduate Experience

Princeton University, Princeton NJ

Investigators

Abstract

The outcomes of higher education are a consequence of individuals' personality traits and many dimensions of the university experience. The Caltech Cohort Study (CCS) will track the entire undergraduate student body of the California Institute of Technology (Caltech) over several years. It uses 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, the formation of social interactions, and ultimately how certain attributes interact to produce educational outcomes. The CCS also serves as an ideal environment for answering fundamental questions about the external validity of incentivized surveys and laboratory experiments. The CCS has four unique features. First, Caltech's small size makes it possible to track nearly the entire student body over time (90% of students completed the first three surveys). Second, the survey 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 time with minimal selection bias. Fourth, the array of behavioral traits elicited can be tied to real-world behaviors and outcomes. The combination of these elements should be invaluable for a large battery of 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 college education aimed at increasing well-being and academic performance, as well as furthering gender and racial equality. The proposal focuses on three areas. First, the dataset's longitudinal nature will allow for a careful inspection of the stability (or lack thereof) of a wide array of behavioral attributes. Second, the rich data on different layers of interactions over time (social, academic, and geographic) combined with the 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 impacts of 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 uncover predictors of academic outcomes (chosen major, grades, and graduation), and the channels affecting the evolution of different traits.