With a rapidly aging US population, smart healthcare technologies are critical to the well-being and quality of care among the elderly and disabled. Unfortunately, there are well-documented challenges in equipping students with the technical and professional competencies for developing user-centered solutions during the engineering innovation process. This project aims at initiating boundary-spanning research for enhancing empathic innovation abilities, which will support user-centeredness during the engineering design process. In this project, the research team will examine how undergraduate engineering students learn empathic innovation over time and how this learning is affected by the nature of community-based learning projects and curricula. The results will provide insights into effective teaching of empathic innovation at the undergraduate level. Guided by the research findings, teaching and learning techniques can be better designed to help students thrive and gain valuable STEM knowledge and skills. Through knowledge dissemination and community outreach, this research will impact multiple stakeholders and institutions. Ultimately, this research will help successfully prepare students for careers in an ever-evolving healthcare industry, which demands a workforce from one eighth of the U.S population, consumes nearly one fifth of the U.S. gross domestic product, and spends about $2.7 trillion annually.
Specific research questions for this project are (1) how do undergraduate engineering students' empathic design tendencies and abilities evolve during an engineering design project; and (2) to what extent, do undergraduate engineering students' empathic designs relate to their engineering innovation on various user-centered smart health engineering design projects. For this research study, the research team will apply a mixed-methods approach. The quantitative measures include individual empathic tendencies, innovative tendencies, empathic design abilities, and team-based innovation potential. Qualitative data collection involves surveys, real-time observations, and videotaping of design review sessions. The team will exploit a suite of statistical analysis methods, including structural equation modeling with latent variables in passive longitudinal designs. The qualitative analysis will employ thematic, content, and discourse analyses. The research team will work with community project partners and domain experts to design and evaluate individual and team-based performance evaluation tasks. This project will inform our understanding of an individual's tendencies in innovative behaviors in relationship to their empathic tendencies, examine how team-based innovation potential is related to empathic design abilities presented by each member of the team, and support current efforts in smart healthcare engineering by better equipping students with the ability to innovate.
