Innovative Approaches to Cross-Disciplinary Applied Data Science Research: Undergraduate Course-Based Projects, REU Initiatives, and Alignment With High-Impact Practices

At Embry-Riddle Aeronautical University (ERAU), undergraduate research in cross-disciplinary applied data science serves as a dynamic platform for experiential learning, combining course-based projects and Research Experiences for Undergraduates (REU) to provide students with hands-on opportunities to tackle real-world problems. This presentation outlines ERAU's innovative strategies for integrating undergraduate research across multiple disciplines, focusing on the structure of projects, assessment metrics, and alignment with the High-Impact Practices (HIP) taxonomy. By examining both course-based and REU research initiatives, we will explore how these methods foster deeper learning, enhance cross-disciplinary collaboration, and prepare students for success in diverse professional and academic settings. The talk will detail the development and application of metrics to assess student progress and outcomes, ensuring these research opportunities contribute meaningfully to personal and professional growth. Additionally, the presentation will offer insights into best practices for aligning cross-disciplinary undergraduate research with the HIP taxonomy, highlighting how ERAU’s approaches create impactful and inclusive learning experiences in the field of applied data science.