2025 ASEE Annual Conference & Exposition

This paper will explore how to meet the introduction of 2022’s CHIPS (Creating Helpful Incentives to Produce Semiconductors) and Science Act. There is a need to “ensure collaboration and coordination across federal agencies, the private sector, and with state and local governments to facilitate timely and effective reviews of all federally-funded projects.” One requirement includes “measures of the institution’s ability to attract and retain a diverse and nontraditional student population in the fields of science, technology, engineering, and mathematics, which may include the ability to attract women, minorities, and individuals with disabilities.” To retain the workforce enabled by this act, this criteria must also be applied to organizations that hire them. Here we show how to incorporate human-centered methods for broadening participation in institutions and organizations. To deliver engineering solutions that serve the spectrum of humanity, we must ensure all voices are heard and respected through rigorous qualitative research methods.

The engineering community benefits from rigorous research methods. Qualitative methods are frequently met with dismissiveness, perceived as less valid data sources than quantitative approaches. This public policy evolution of Indi Young's listening sessions and thinking styles methodology adapts a rigorous method to include aspects relevant to public sector work. Those working in both the public and private sectors will find this methodology useful.

Initiatives around diversity, equity, and inclusion are frequently met with derision and suspicion. As the CHIPS and Science Act requires broadening participation evidence to minimize the potential harms of emerging technologies, institutions and organizations need actionable measures to meet these requirements. Rigorous human-centered methodologies to prioritize the spectrum of humanity’s lived experiences and expertise are needed to ensure environments include broad perspectives. This methodology reduces human bias in the process, surfacing the voices of participants for inclusion in evaluation of problem and solution space research.