This piece is the follow-up to the authors’ previous piece, Inclusive and equitable tech reskilling at LaunchCode in St. Louis.
Given technological advances spurred by the pandemic, the skills gap will likely continue to grow, which will have a disproportionate impact on persons of color, and this impact will remain unless new reskilling models are scaled up. One of the most common reskilling programs in technology are bootcamps, which often involve intensive, rapid skills training adapted to meet local labor market demands.
While the bootcamp model creates opportunities to learn new skills, many participants, especially those of color, face barriers due to inadequate recruitment and retention strategies, as well as implicit and explicit biases in the employment process. Further, research has not yet confirmed whether these models increase future earnings of program participants. Recognizing these shortcomings, an organization based in St. Louis—LaunchCode—combined its education program with an apprenticeship program in an effort to create a more efficient and equitable transition to the labor market, as students learn new skills and then apply them with a local employer. In this blog, we explore the impact of this model and share some lessons learned.
The LaunchCode Program
LaunchCode offers flexible programming where participants can complete the program part-time in roughly six months by attending evening courses. Upon successful completion of the program and determination of workforce readiness by LaunchCode staff, participants can start a paid, full-time apprenticeship, which can potentially lead to a permanent position. This approach provides LaunchCode graduates an opportunity to supplement their technical skills with soft skills in the workplace. It also subsidizes the cost of the education program, making it free for all students—a characteristic that can be especially important for increasing diversity.
While bootcamps and similar programs are becoming increasingly more commonplace among non-degree education programs, especially in technology, little research has explored the impact of these programs on economic outcomes. For example, some research has explored the impact of these programs on technology employment, but not on earnings. Moreover, for research that has explored the impact of these programs, it is unclear whether or not the associated outcomes are a product of the courses alone or—for programs like LaunchCode—the apprenticeships that these programs provide. In the next section, we delve into the findings of the program conducted by the Social Policy Institute, especially its effectiveness in improving economic outcomes for participants.
Impact on Economic Outcomes of Students
Researchers at the Social Policy Institute launched a large-scale program survey that collected employment, income, and optimism measures for 1,006 individuals—including 567 who were accepted into the program, as well as 426 who were not accepted into the program—across nine cohorts from January 2017 to May 2020.
Optimism measures were based on the Cantril Ladder:
“Please imagine a ladder with steps numbered from zero at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step do you think you will stand about five years from now?”
We first compare estimated averages of income and optimism, as well as predicted probabilities of employment, across program admission status. These estimates are derived from regression models that compared those who were accepted into the program to those who were not accepted—also known as “intent-to-treat” models. Here, it is important to note that those who were accepted into the program include individuals who did not complete the course (“course enrollers”), individuals who completed the course but did not complete the apprenticeship (“course completers”), and individuals who completed the course and the apprenticeship (“apprenticeship completers”). In addition to controlling for cohort, our results also control for prior outcome measures. For example, our income estimates over the past 12 months control for an applicants’ income prior to applying to LaunchCode. As a result, our results can be interpreted as the impact of LaunchCode admissions on economic outcomes.
When accounting for income prior to applying to LaunchCode, the average income for those who were accepted was $45,669.33 at the time of the survey, compared to $41,386.12 for those not accepted into the program. The differences were statistically significant. When accounting for prior STEM employment (STEM employment prior to applying to LaunchCode), those who were accepted into LaunchCode had an 81.5 percent chance of being employed in STEM at the time of the survey, compared to only a 72.8 percent chance for those who were not accepted. When accounting for prior optimism measures, those who were accepted had a mean optimism score of 8.2 at the time of the survey, compared to 7.9 for those who were not accepted.
To get a more nuanced understanding of the program, we also compared individuals who were not accepted to course enrollers, course completers, and apprenticeship completers. As these models account for actual program participation (“treatment on treated”), these results can be interpreted as the impact of LaunchCode’s program on economic outcomes.
As indicated in Figure 1, for those who completed the program through the apprenticeship, their average income in the past 12 months is $66,406, compared to $41,242 for those who were not accepted. There were no significant differences for course enrollers and completers when compared to those who were not admitted. Here, it appears that one of the most important mechanisms for increasing earnings in LaunchCode’s program is the apprenticeship.
Additionally, when controlling for whether students had previous employment in STEM fields prior to applying to LaunchCode (Figure 2), apprenticeship completers had a 99.7 percent chance of being employed in STEM, course completers had an 88.6 percent chance of being employed in STEM, and course enrollers had a 55.4 percent chance of being employed in STEM at the time of the survey, compared to 75.4 percent of those who were not admitted. This demonstrates an increase in STEM employment for both apprenticeship completers and course completers.
The mean optimism scores for course enrollers and completers were 8.1 and 8.2 at the time of the survey, compared to 7.9 for those not accepted, but no significant difference was found between those who completed the apprenticeship and those who were not accepted. As course enrollers and completers had higher levels of optimism than those not accepted, we can infer that increased optimism may be largest during the ascent phase.
Given the novel and rapidly changing nature of the labor market, learning new skills quickly will become an increasingly important aspect of workforce development and social mobility. Indeed, our findings demonstrate the positive impact of being admitted to reskilling programs: increased employment, earnings, and optimism across admitted applicants. These programs can also help fill the STEM pipeline, which can have positive effects on competitiveness at both a local and national level.
However, our research also demonstrates that courses alone will not lead to widespread social mobility, as apprenticeships appear to be an integral part of this workforce training model. Furthermore, apprenticeships are not only vehicles to improve efficiency in workforce development; equity is also critical, as apprenticeships allow programs like LaunchCode, to be offered for free. By doing so, LaunchCode can more serve low-income persons and persons of color—whose circumstances may prohibit them from enrolling in paid courses or working in non-paid internships. Support for apprenticeships should be a priority for communities seeking to facilitate more efficient and equitable pathways to employment. As many of the people who can benefit from these types of programs may have little or no experience in these industries, apprenticeships also allow these individuals to learn both hard and soft skills while adapting to new workplace cultures and norms.
Moving forward, more federal agencies and local programs should integrate meaningful internships and apprenticeships into their programs. This will require joint efforts across education, employment, and workforce development organizations. By doing so, program participants – especially those entering or returning to the workforce – will benefit.