Gen AI's revolutionary growth creates new challenges for UX research. How best to add value faced with:
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Rapid change
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Lack of expertise
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Lack of basic vocabulary or mental models
My tactics for impactful Generative AI research include:
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Structure connected research to occur regularly and flexibly to provide timely data to make key decisions
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Focus on core needs and challenges first, then extend research to how AI might play a role in solving these
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Over time get more and more granular assuming that by later sessions, core participants will understand new AI concepts and be better able to provide contextual feedback
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AI-DRIVEN LEARNING HUB
Backgound
El Sol Neighborhood Education Center engages and deploys highly trained lay workers as community health workers (CHWs) to bridge community and social service agencies in the US, Latin America, Australia, and Africa. Yet, barriers to accessing El Sol tools and resources, family assessments, and shared learnings and best practices prevented CHWs from confidently and effectively serving their communities.
I led a mixed-methods research project to identify and address the pain points faced by Community Health Workers (CHWs). The primary aim was to determine if a Central Learning Hub backed by generative AI could effectively enhance their ability to serve community families.



The Task
My task involved designing and leading the comprehensive research to uncover CHWs’ needs, connecting that initial research to rolling research to determine if generative AI served these needs, and consulting on the design and implementation of the learning hub based on these findings while evaluating its effectiveness. The project aimed to improve resource accessibility, enhance CHW collaboration, and increase confidence and preparedness in their roles, while addressing cultural, accessibility, and technical needs presented by various global communities.



Actions
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Research and Discovery:
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Championed and conducted thorough qualitative research, including interviews, surveys, and focus groups with CHWs and stakeholders. We identified that the main obstacles were the lack of a central place for resources and isolation due to the absence of peer connections.
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Incorporated Google's People + AI Guidebook research methods, best practices, and case studies to facilitate research and co-creation workshops, guide best practices and design patterns, and educate our team on responsible and ethical AI design.
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Analyzed data to highlight key pain points and validated these findings through the CHW advocacy panel.
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Design and Development:
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Collaborated with stakeholders, including the Executive Director, Directors of Engineering, IT, and Training, UX Designers, AI Engineers, and Product Managers.
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Partner with the product, UX, and engineering team to design the CHW/P Learning Hub, incorporating feedback from CHWs. The platform featured educational modules, printable resources, interactive forums, games, and personalized dashboards for tracking progress.
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Leveraged Microsoft Azure services for enhanced training modules, data analytics, and infrastructure support.
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Pilot and Implementation:
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Launched the learning hub pilot in three diverse regions: San Bernardino, CA; Mexico City, Mexico; and Mobmasa, Kenya.
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Provided onboarding and training to CHWs on using the platform, ensuring ease of access and utilization.
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Collected real-time feedback and usage data to refine the platform.
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The Results
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User Engagement:
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Increased monthly active users by 25% within the first three months.
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Average session duration reached 35 minutes, with high engagement in viewing multiple pages and resources.
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Resource Utilization:
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High rates of resource downloads and views, particularly for printable sheets, videos, and interactive games.
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Active participation in forums, fostering a sense of community and knowledge sharing.
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Learning and Development:
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Completion rate of learning modules exceeded 85%.
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Significant improvements in CHW knowledge, evidenced by pre- and post-assessment scores.
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Over 70% of participating CHWs achieved new certifications, boosting their confidence and capabilities.
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Networking and Community Building:
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Hundreds of new connections made through the platform, enhancing peer support and collaboration.
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Positive user feedback highlighted increased satisfaction and a sense of belonging.
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Organizational Impact:
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Multiple CBOs utilized technical assistance resources, demonstrating the platform's broader impact.
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Frequent use of dashboards and reports by CBOs, leading to better decision-making and operational efficiency.
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