Major Choice
Our team has three current projects that examine how students in community colleges choose a major or program of study. The first examines how information about the labor market influences community college students’ decisions regarding program choice. The second examines a multi-stage model of major choice and asks whether there are differences between groups of students (gender, age, ethnicity) in the kinds of majors they know about, and which they would consider choosing. The third study uses degree data from the California Community College Chancellor's Office and course-taking data from FHDA to examine how institutional policies affect student course taking patterns.
Labor market influences on major choice
We have surveyed community college students at various points in their program (including those who have just started and not declared a program) to ascertain how much information they have about employment and earnings across fields. The survey asks students about their intended program choice in school and their career aspirations, focusing on what factors are important to them in making such choices. This survey is the first to ask these questions of community college students. It will provide evidence on how accurate these students are when forecasting labor market returns, and which factors are most important to students in choosing a field. We will utilize the information we gather from this survey to develop an intervention designed to provide students with accurate, timely and user-friendly labor market information intended to facilitate their selection of program.
Multi-stage model of major choice
We have surveyed community college students to ascertain the majors students know about, and from this set the majors they would consider choosing. Academic fields, and thus career fields, are segregated by gender, socioeconomic status and race. This segregation has implications for wages gaps and continued and growing economic inequality. Classic models of choice, which assume awareness and consideration of all options, run the risk of obscuring important features of the decision process that could explain continued segregation. This study applies a more plausible model of decision making to the study of college major choice by focusing on the awareness and consideration sets of students and attempts to explain differences in size and composition. Findings from this study could provide insight into the stage at which demographic differences are most pronounced or amenable to intervention.
The effects of structured transfer programs on student course taking
This study examines the effects of structured transfer programs on student course taking patterns. It provides preliminary evidence that the introduction of Associates Degrees for Transfer had an effect on the behavior of students in California Community Colleges: departments that offered these degrees saw bigger than expected increases in the number of degrees they granted. Untreated departments were not affected, which could mean that the legislation induced students who were already planning to transfer to pick up a degree “on the way” as opposed to switching majors. There has been little research on the success of transfer and articulation agreements. Longitudinal data on transfer rates, number of degrees and course taking—from before and after transfer policies are enacted—is needed to persuasively assess the effect of transfer policies. Most states do not have such data; many data collection systems were enacted as the result of transfer policies. As a result, much of the extant research has relied on between-state variation in transfer policies. These types of studies cannot provide causal estimates, but they can provide suggestive evidence. As a policy intervention with impressive legislative support, it is important to understand the effects of structured transfer programs.
Digital learning
There is a great deal of interest—locally and nationally—in how digital education can best be implemented to meet the needs of different kinds of students. FHDA has longstanding experience in online offerings, with approximately 25% of enrollments at Foothill and 10% of enrollments at De Anza already online. FHDA’s longitudinal data and experience in this area presents a unique opportunity to inform California and beyond about what works in online higher education. Not only does FHDA have unusually high online enrollments, nearly all of FHDA’s online classes are also offered in the classroom, presenting an opportunity to compare online and face-to-face learning, and how they can best be complementary.
Research in digital learning also offers a chance to study the tension between two policy goals: college access and completion. While online courses can increase access (by lowering time and financial costs and providing versatile accessibility), they are also associated with decreased completion (students tend to have lower success rates in online classes). We have explored success in online versus in-person classes at FHDA in two White Papers and multiple additional analyses:
Institutional Research
Institutional Research (IR) is becoming increasingly important for helping to measure institutional quality and inform institutional change, as witnessed by new reporting requirements from federal and state governments. We argue that in addition to surveys of inputs (how many projects were completed?) and satisfaction (how did people feel about the work?), institutional researchers should study measurable outcomes. Faculty are expected to evaluate not only what they have taught, but also what their students have learned; shouldn’t institutional researchers do the same? To address this, Stanford researchers conducted interviews with top leadership at FHDA to provide feedback for the IR department on (1) Whether information received from IR is useful for decision-making, presented in a way that is easily understood and applied, and (2) How specifically leadership uses information received from IR to make decisions. Findings from these interviews are detailed in a report: