Collaborative Research: Personalized and Collaborative Approaches to Integrating Data Science in Molecular Bioscience Education

This project aims to serve the national interest by enhancing molecular bioscience education through implementing evidence-based teaching practices, and developing personalized, adaptable educational resources that improve student engagement, workforce readiness, and faculty teaching capacity in data science. Harnessing the magnitude of existing and potential data, and appropriately contextualizing it are crucial for advancing research and innovation within molecular biosciences. Students in this field require comprehensive training in both technical and durable data science skills, especially in understanding the cascading impacts of decisions made when interpreting data in complex ways, partially due to the prevalence of "black box" approaches that require greater scrutiny. Addressing this gap in content requires targeted educational initiatives that focus on both technical proficiency and contextual application of data science skills while accounting for external factors impacting student success. This initiative introduces the use of learner personas to develop multimodal, best-practice-informed educational materials tailored to student and faculty needs. Ultimately, these resources foster improved understanding, engagement, and application of data science in molecular biosciences. The primary goal of this project is to improve molecular bioscience education by developing learner-centered, data science–infused curricula, supporting faculty development, and strengthening students' preparation for a data-driven workforce. The project implements learner personas to tailor instruction, enhance student engagement, and support student centered teaching practices across diverse institutional contexts. A central component, the Molecular Data Education Hub (MDE-Hub), hosts open-access modular curricular resources, instructional guides, and case studies grounded in real-world molecular bioscience research. Faculty professional development workshops provide training in technical data science competencies and strategies for integrating data science into existing courses and curricula, while fostering a sustainable network of educators. A comprehensive evaluation plan examines the effectiveness of these curricular materials and professional development activities in improving student learning outcomes, faculty practices, and broader instructional impact. Through collaborative partnerships with Research-1 and predominantly undergraduate institutions, the project ensures that outcomes are scalable, providing long-term benefits for both molecular biosciences educators and students in teaching and learning data science. Overall, this project addresses prevalent issues of training students and faculty in technical and durable data science methods and prepares a more competent and workforce-ready cohort of molecular bioscientists. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.