Seattle's Black community faces significant challenges in banking and finance, including a lack of trust, limited access, and systemic barriers. While FinTech presents potential solutions, concerns persist regarding data privacy and cultural sensitivity. In response to these issues, I took on a central role in facilitating a research project that aimed to co-design an inclusive FinTech solution directly with Black communities in Seattle. To create a participatory design approach and host collaborative sessions with a Black community advisory board, my research group worked closely with community leaders and stakeholders. This involved organizing focus group sessions, where we explored three key questions: 1) What challenges do Black Americans face in banking and FinTech? 2) How can FinTech revolutionize their economic outlook? 3) How can community members co-design a culturally sensitive virtual AI assistant for mobile FinTech? Throughout these sessions, I played an active role in observing and leading discussions to ensure that community members had a meaningful voice in shaping the solution. I also analyzed the data collected from these sessions using inductive and deductive coding techniques to identify key insights and inform the process and steps for the next focus group. We anticipate developing a prototype solution designed by and for Black communities, prioritizing trust, accessibility, and empowerment. Preliminary findings suggest that community engagement and co-design processes are crucial for creating effective and culturally sensitive FinTech solutions. Additionally, fostering understanding and collaboration between Black communities, financial institutions, and FinTech developers is essential for paving the way towards a more equitable financial future for all stakeholders involved.

International students are an essential part of the UW community as they are able to bring in a unique set of lenses and perspectives to perceive, approach, and solve problems. The UW International Student Service (ISS) is a place that provides information and guidance for the international students to legally live and study in the U.S. After encountering difficulties using the ISS system as an international student and a design researcher, I started to wonder how the ISS might improve to create a better user experience of their website and services. I began exploring this question in HCDE 417 in Autumn 2023. This application supports the continuation of that work, motivated by the following two research questions: 1) How well does the UW ISS website navigation work in terms of guiding international students to complete the correct tasks? 2) How might we improve the ISS system to better support the needs of the international students? My research is a usability study focused on understanding three attributes of usability for the UW ISS system: the usefulness, discoverability, and satisfaction. By carrying out initial usability testing sessions in HCDE 417 with international students and analyzing the transcript data using open coding and axial coding methods, I was able to take a deep dive into the problems with virtual advising services. My initial research surfaced several insights including the inconvenient drop-in only advising services, unreasonable student-to-advisor ratio, and less discoverable content. The impact of this study is that I took my initial research findings to ISS UX intern to discuss potential changes that could be made to the ISS to improve students' experience. As part of the community, I would like to use my design background to advocate for international students to be receiving more attention and resources from the UW ISS.

The latest developments in health applications for large language models (LLMs) have shown promising prospects in providing preliminary diagnoses based on user symptoms, especially appealing to patients with mild conditions who prefer online consultation over in-person clinic visits. However, the accuracy of these symptom-based decisions remains uncertain. This gap is more pronounced in mental health applications, where there is a noticeable lack of research on the efficacy of LLMs in offering effective treatment advice. Our study addresses this issue by evaluating systems through a combined analysis of LDA topic modeling, word frequency analysis, and cosine similarity analysis, examining how chatbots based on LLMs utilize data from the American Psychological Association to provide diagnostic information and the accuracy of their treatment advice. We found that while these chatbots can provide highly accurate diagnoses and corresponding treatment recommendations for virtual patients, they typically offer less information about the prescribed treatment needed compared to human psychologists; moreover, chatbots based on LLMs tend to mention common relevant words across all topics, whereas responses from psychology experts are more likely to cover most relevant words within a topic. This raises discussions about the significance and limitations of LLMs in mental health diagnosis and treatment advice, calling for a highly academic approach.

Teaching engineers about design processes is difficult. In a typical engineering curriculum, students get multiple experiences doing design but less often get to learn about design. Understanding the context and breadth of design is important. Therefore, in this work, we ask the question, “How might we offer a breadth of design perspectives to students?” To approach this problem, we created a resource by crowdsourcing attributes of “good” design. We invited design and engineering researchers and educators to respond to the prompt, “When you talk to someone and say “Good designers do ‘X’”, what are the top 4 or 5 things you list? I’m looking for ‘off the top of your head’ answers.” 34 people responded with 179 statements, resulting in a rich resource to show the breadth of design processes. We’ve used this in multiple spaces, and in this poster we’ll describe how we used this in a seminar of 25 undergraduate and master’s students from multiple majors. We engaged the students with an in-class activity with the statements and asked them to create a visual representation inspired by the collection. We performed an inductive thematic analysis of student reflections to that in-class activity, as well as their reflections at the end of that class. From our analysis we found that the collection of responses helped students (1) gain an interdisciplinary awareness that there are many possible perspectives and different ways of defining good design, (2) understand that learning and adaptability are important elements of design, and (3) experience the importance of deep and personal reflection about their own values and motivations. This collection helped students understand the breadth and personal nature of design processes. We offer this resource to support engineering educators who hope to broaden the way they teach design.