Expert blind spot

We’ve just finished an advanced one-week short course in systems genetics, and as always, the course was illuminating and invigorating. My role was organizational in nature, with the teaching left to the experts. After reading about how student knowledge organization affects learning, I’m pondering ways that the course faculty might better meet the students where they are rather than teaching over their heads. I also wonder just how much of the advanced content sinks in for students whose understanding is limited, sparse or superficial.

Participants are a diverse group. Some arrive with plenty of statistics and computing knowledge, however, many others have only a basic statistics understanding and little or know computer programming skill. From the start, the course content assumes programming and statistical understanding that many do not possess. It progresses rapidly to complicated topics and includes hands-on computing sessions each day. The diversity in participants’ understanding and skill is apparent in the kinds of questions asked and in the difficulties that some face with hands-on sessions. The faculty are responsive and helpful to students, however, many students will not ask questions or express confusion for fear of losing face before others.

One answer to this problem would be to admit only those with the requisite computing and statistics knowledge. That would assure that participants are able to keep up with the course and extract as much as possible from the experience. This would limit, however, the participant pool to the point that the course might not be viable. Another might be to alert potential participants to prerequisites beforehand, and point them toward helpful resources for review before arrival. This might also limit the participant pool by scaring off many.

A full day of tutorials to provide computing and statistics background would best prepare participants for content to follow. Those who already possess requisite knowledge and skills could be offered advanced training in computing and statistics concepts at the same time. Participants would self-select for the tutorials that would best meet their needs. In addition to providing prerequisite material up front, a graphic describing course organization would help participants to understand where each topic and lecture fits into the overall picture. Examples that demonstrate deep features of problems, even when problems seem only superficially related, would be helpful for students’ knowledge organization. The faculty are already very good about clearly explaining how new concepts relate to older ones. I intend to work with them to provide the bigger picture and to highlight deep or cross-cutting features of problem or design.

Written on October 23, 2016