The demand for qualified bioinformaticians has been growing for many years, as high-throughput experiments have been producing unprecedented quantities of data. At the same time, non-life-science industry demand for programmers has reduced the pool of people with strong computational skills.
Since bioinformatics lies at the interface between Biology and Computer Science, aspiring students are an admixed population and are, loosely speaking, as likely to come from a biological as a computer science or engineering background. The biological students are intellectually necessary, in order to ensure the field stays focused on the right biological questions. Bioinformatics educators therefore universally face the challenge of training an incoming class of students whose computational skills vary over a wide range.
I wish to develop teaching techniques which will raise the computational proficiency of the more biologically oriented students, and also adjust the bioinformatics coursework so that the entire class can absorb the material and become productive. The approaches include remedial coursework, standardizing to a single programming language, pre-and post-course assignments, in-class tutorial support, student choice in project work, improvements in the physical learning environment, and teacher training. I will apply the findings in my work leading the Research School in Medical Bioinformatics, in upcoming MS teaching, and in summer courses for Chinese and other international undergraduate students.
Pedagogical ambassdor is Samuel Flores at the Department of Biochemistry and Biophysics.
