Departments of Biomedical Engineering and Otolaryngology Keywords: Biomedical engineering, neural Engineering, project-based, active learning Merging bio and engineering: project-based learning in undergraduate and graduate biomedical courses Suhrud M. Rajguru, PhD Departments of Biomedical Engineering and Otolaryngology University of Miami

Why? What problem are you solving? Improve involvement of undergraduate and graduate students in neural engineering and introduce mathematical concepts and engineering tools used to study neural function What are your educational objectives? Revise existing curricula to emphasize team science and real world applications. Develop course content that can be accessed by students with diverse backgrounds and learning styles. Combine in-depth discussions of neuroscience, physiology and computational / visualization methods into rigorous bioengineering curricula.

When? What is the developmental history of your innovation? Fall 2012, BME 470: Introduction to Biosignal Processing Help students form associations between theoretical concepts and translation to practice Added a practical component to supplement lecture material: Instrumentation lab, MATLAB programming and signal processing applications Students recorded and analyzed real biosignals and articulated their properties Continue to develop new and relevant examples and data into the course exercises based on data obtained from research and literature. Extend to BME 603: Neuroscience course open to both undergraduate (enrolled in 5-year BS/MS program) and graduate students (MS, PhD).

Where? Have you tried this in other institutions? Is this developed for a single class, a full course, or a curriculum? Full course(s) Education Levels: upper division undergraduate and graduate students Education Backgrounds: biomedical engineering, biology and the School of Medicine

What? EXPERIMENT COURSE OBJECTIVE EXPECTED OUTCOME Instrumentation for electrophysiological measurement BME 470   Introduction to signals, concepts related to data acquisition (sampling, reconstruction, ADC, DAC), signal averaging and signal-to-noise ratio Gain knowledge of technical requirements and challenges in measuring neural signals. Sharp microelectrode recordings from 8th nerve BME 603 Learn dissection, general electrophysiology methods Demonstrate in vivo experiment techniques Data analysis of neural recordings and statistical methods BME603 Threshold detection, effects of digitization on biosignal recording and post-processing, biostatistics General knowledge of signal processing. Ca2+ imaging Learn microscopy/ imaging techniques, signal detection and analysis Knowledge of noninvasive approaches to assay function / intracellular signals Computational models to fit experimental results Learn computational approaches and associated complexities Learn to develop models rooted in experimental findings

Prognosis? How are you documenting impact? Direct (student projects, presentations) Indirect assessment measures (surveys, interviews, course evaluation) What challenges are you currently facing? Difficulty in organizing group sessions and hands-on experiences for large class sizes What advice would you like from others at FOEE? How to scaling up this approach for larger classrooms How to keep students motivated and engaged Assessment tools you’ve used