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We consider the case in which the number of seats in a program is limited, such as a job training program or a supplemental tutoring program, and explore the implications that peer effects have for which individuals should be assigned to the limited seats. In the frequently-studied case in which all applicants are assigned to a group, the average outcome is not changed by shuffling the group assignments if the peer effect is linear in the average composition of peers. However, when there are fewer seats than applicants, the presence of linear-in-means peer effects can dramatically influence the optimal choice of who gets to participate. We illustrate how peer effects impact optimal seat assignment, both under a general social welfare function and under two commonly used social welfare functions. We next use data from a recent job training RCT to provide evidence of large peer effects in the context of job training for disadvantaged adults. Finally, we combine the two results to show that the program's effectiveness varies greatly depending on whether the assignment choices account for or ignore peer effects.
Nearly half of students who enter college do not graduate. The majority of efforts to increase college completion have focused on supporting students before or soon after they enter college, yet many students drop out after making significant progress towards their degree. In this paper, we report results from a multi-year, large-scale experimental intervention conducted across five states and 20 broad-access, public colleges and universities to support students who are late in their college career but still at risk of not graduating. The intervention provided these “near-completer” students with personalized text messages that encouraged them to connect with campus-based academic and financial resources, reminded them of upcoming and important deadlines, and invited them to engage (via text) with campus-based advisors. We find little evidence that the message campaign affected academic performance or attainment in either the full sample or within individual higher education systems or student subgroups. The findings suggest low-cost nudge interventions may be insufficient for addressing barriers to completion among students who have made considerable academic progress.
Hundreds of colleges have changed their names to signal higher quality. We estimate how this affects college choice and the labor market performance of college graduates. Administrative data show that name-changing colleges enroll higher-aptitude students, with larger effects for attractive-but-misleading name changes and among students with less information. A resume audit study shows that employer callbacks respond to the increased aptitude of recruited students at these colleges. We broaden these results using scraped online text data, survey data, and other administrative data. Our study demonstrates that signals designed to change beliefs can have real, lasting impacts on market outcomes.
We assess whether a light-touch intervention can increase socioeconomic and racial diversity in undergraduate Economics. We randomly assigned over 2,200 students a message with basic information about the Economics major; the basic message combined with an emphasis on the rewarding careers or financial returns associated with the major; or no message. Messages increased the proportion of first generation or underrepresented minority (URM) students majoring in Economics by five percentage points. This effect size was sufficient to reverse the gap in Economics majors between first generation/URM students and students not in these groups. Effect sizes were larger and more precise for better-performing students and first generation students. Extrapolating to the full sample, the treatment would double the proportion of first generation and underrepresented minority students majoring in Economics.
This paper presents evidence that women and men benefit from having a higher percentage of female peers in post-secondary vocational STEM programs. I use idiosyncratic variation in gender composition across cohorts within majors within branches (campuses) for identification. Having a higher percentage of female peers positively affects students in STEM majors, decreasing women's dropout rates and increasing GPA. The peer effect seems to be mediated by the gender of the instructors: as female students have fewer female instructors, the effect of having more female peers intensifies. For men, a higher percentage of female peers reduces dropouts and increases GPA to a lesser extent, suggesting that policies that increase the representation of women need not entail a trade-off for male STEM students.
In-person college advising programs generate large improvements in college persistence and success for low-income students but face numerous barriers to scale. Remote advising models offer a promising strategy to address informational and assistance barriers facing the substantial majority of low-income students who do not have access to community-based advising, yet the existing evidence base on the efficacy of remote advising is limited. We present a comprehensive, multi-cohort experimental evaluation of CollegePoint, a national remote college advising program for high-achieving low- and moderate-income students. Students assigned to CollegePoint are modestly more likely (1.3 percentage points) to attend higher-quality institutions. Results from mechanism experiments we conducted within CollegePoint indicate that moderate changes to the program model, such as a longer duration of advising and modest expansions of the pool of students academically eligible to participate, do not lead to larger program effects. We also capitalize on across-cohort variation in whether students were affected by COVID-19 to investigate whether social distancing required by the pandemic increased the value of remote advising. CollegePoint increased attendance at higher-quality institutions by 3.2 percentage points for the COVID-19-affected cohort. Acknowledgements.
Despite its increasing importance for educational practices, broadband is not equally accessible among all students. In addition to oft-noted last-mile barriers faced by rural students, there can be wide variation in in-home access between proximate urban and suburban neighborhoods ostensibly covered by the same telecommunications infrastructure. In this paper, we investigate the connection between these disparities and earlier redlining practices by spatially joining two current measures of broadband access with Depression-era residential security maps that graded neighborhoods for real estate investment risk from “Best” to “Hazardous” based in part on racist and classist beliefs. We find evidence that despite internet service providers reporting similar technological availability across neighborhoods, access to broadband in the home generally decreases in tandem with historic neighborhood risk classification. We further find differences in in-home broadband access by race/ethnicity and income level, both across and within neighborhood grades. Our results demonstrate how federally developed housing policies from the prior century remain relevant to the current digital divide and should be considered in discussions of educational policies that require broadband access for success.
Many novice teachers learn to teach “on-the-job,” leading to burnout and attrition among teachers and negative outcomes for students in the long term. Pre-service teacher education is tasked with optimizing teacher readiness, but there is a lack of causal evidence regarding effective ways for preparing new teachers. In this paper, we use a mixed reality simulation platform to evaluate the causal effects and robustness of an individualized, directive coaching model for candidates enrolled in a university-based teacher education program, as well as for undergraduates considering teaching as a profession. Across five conceptual replication studies, we find that targeted, directive coaching significantly improves candidates’ instructional performance during simulated classroom sessions, and that coaching effects are robust across different teaching tasks, study timing, and modes of delivery. However, coaching effects are smaller for a sub-population of participants not formally enrolled in a teacher preparation program. These participants differed from teacher candidates in multiple ways, including by demographic characteristics, as well as by their prior experiences learning about instructional methods. We highlight implications for research and practice.
How have changes in the costs of enrolling for full-time study at public 2-year and 4-year colleges have affected the decisions about whether and where to enroll in college? We exploit local differences in the growth of tuition at community colleges and public 4-year colleges to study the impact of public higher education costs on the postsecondary enrollment decisions of high school graduates over three decades. We model prospective students’ decisions about whether to attend community college, a public 4-year university in their state of residence, other colleges, or no college at all as relative costs change. Unlike institutional analyses, our contribution is not to model how enrollment changes at a particular college or type of college as costs change. But, we draw from the institutional literature to help identify enrollment impacts by instrumenting college costs using policy variation imposed by state appropriations and tuition caps. We estimate that in counties where local community college tuition doubled (about average for the study period), the likelihood of post-secondary enrollment fell by about 0.06, on a mean of about 0.80. In addition to reducing college enrollment overall, rising costs at community colleges diverted other students to 4-year colleges. Rising relative costs of 4-year public colleges similarly diverted some students toward community colleges, but did not limit college attendance in the aggregate. We also find evidence of endogeneity in cost setting at the institution level. Our preferred estimates rely on a control function approach that instruments intertemporal changes in institutional costs using state and local appropriations and state policies to restrict tuition growth.
The COVID-19 pandemic led to an abrupt shift from in-person to virtual instruction in Spring 2020. Using two complementary difference-in-differences frameworks, one that incorporates student fixed effects and another that leverages within-course variation on whether students started their Spring 2020 courses in-person or online, we estimate the impact of this shift on the academic performance of Virginia’s community college students. With both approaches, we find modest negative impacts (four to eight percent) on course completion. Our results suggest that faculty experience teaching a given course online does not mitigate the negative effects of students abruptly switching to online instruction.