Jenna Butler is, at her core, a teacher – a learning guide who loves to engage her student in critical though and challenge and support them in a warm and supportive classroom environment. A recent recipient of the USC Alumni Teaching Award, Butler was acknowledged for the truly interactive context she was able to establish in the Computing for Life Sciences/Scientists course offered by the Department of Computer Science. Originally designed by her supervisor, Dr. Mark Daley a cross-appointee in Biology, Neuroscience and Computer Science, this course was designed to equip students with a basic skill set needed to effectively use computational tools to analyse the Big Data associated with most scientific research.
The course offered a series of problem-based learning opportunities. Listening to a 5- to 10-minute lecture followed by an active hands-on learning activity, students were able to grasp concepts and apply them to real problem-solving situations – working independently or with their peers – with the ever present support and guidance of Butler and two Teaching Assistants who volunteered to attend every class to further support student learning. This approach allowed Butler to provide the students with challenging assignments. “I got to know my students and was invested in them” commented Butler, and as a result, she was keenly aware of the students’ capacity.
“Our world is very data-driven and there isn’t a single area anymore that hasn’t been impacted by the computer. Our whole world is being driven toward the interconnectivity of things” said Butler, “and that’s why this class is so valuable. It makes the average science student more marketable when they can both gather and use 21st century computational tools to analyse data efficiently” she added. Butler has taught four classes over the course of her graduate studies. She clearly cares about her students and her passion for learning in nothing less than contagious.
Butler is a Bioinformatics PhD candidate, whose research focuses on modeling early cancer growth in the body and attempting to simulate the effect of combination drug therapies on tumours.