Topic no. 2 for the roundtable session at the latest Instructor Hangouts (yep, we went way overtime), was welcoming and engaging students from as diverse a set of professional practices as possible. This conversation was in response to a thread I started on the SWC list the previous week, to discuss the comments submitted by a workshop student who left feeling insulted, belittled and disrespected when the instructor made a mockery of a particular analysis tool that this student had made a career of using for twenty years prior. Much was said on the SWC forum which I won’t rehash here; for Instructor Hangouts, I wanted to try something a bit different.
Software Carpentry instructors are all trained in the practice of imagining student profiles – creating short descriptions of who they imagine their learners to be as they come to the classroom. For example:
‘Gail is a second-year physics undergraduate; she has used a bit of MATLAB in her lab courses, and took a first year CS course in Java. She’d like to learn some C++, since she knows it will be useful for the high-performance analysis she’s likely to have to do in grad school.’
The idea being, the instructor can take this imagined canonical student’s knowledge, consider what the learning goals for the workshop are, and teach to the gaps between the two; if she’s guessed her student well, the instructor will have a properly targeted lesson to help bridge the gap – this is all presented as part of reverse instructional design. What I suggested instructors start doing (and what the other attendees came up with with no prompting from me), was to go through this exact exercise, but expand the scope to the experiential and emotional states of the students as well; in this way, we can anticipate better how our students will react to our attitudes, opinions, and demeanor. For example:
‘Michael is a tenured professor, who has been using a proprietary statistics package to do his work for his entire career. He’s heard a lot about R, but is feeling uncertain about how much of his time it will take to master that language to the same level of proficiency he already has with existing tools. It’s not clear whether giving up his previous practices would be a big boondoggle, or a necessary investment for advancing his work.’
It’d be pretty difficult at this point to take quite the dump on Michael’s proprietary statistics package that the anonymous feedback that started this all described; the issues are more subtle and more serious than simply prescribing something for a blanker slate. By expanding our practice of imagining students knowledge to imagining their experience, I think we can not only avoid the misfires that occurred with our one disgruntled student, but broaden the pool of people we offer something valuable to dramatically. As was largely agreed upon on the SWC thread: we’re here to teach ideas, not smash and trash tools; by learning to be mindful enough to welcome many different practices, we make science more open not just in terms of sharing and interoperability, but in terms of experience, too.