We have to teach where the students are: Response to “How We Teach Should Be Independent Of Who We Are Teaching”
Valerie Barr has great insights into computing education, especially with regards to diversity (e.g., see the blog post last CS Ed Week about alternative ways to view data about diversity in computing). I like what she has to say in her most recent Blog@CACM blog post, but I think the title is somewhat misleading.
“How we teach should be independent of who we are teaching” is clearly not true. No one would argue for teaching Linux kernel developing via all day long bootcamps in C to middle school students. Few people use CS Unplugged with machine learning graduate students. What Valerie is explicitly addressing in her blog post is an issue called essentialism.
As we continue efforts to diversify computing, we cannot afford to paint any group in a monochromatic way. We have to embrace the richness of today’s student population by making what we teach meaningful and relevant to them. There are women who want to geek out about hard-core tech, and there are men who care deeply about computing for the social good. There are students of all genders and ethnic and racial backgrounds who will be happy with an old-fashioned lecture, and those who will thrive on active learning with examples drawn from a range of cultures and application areas. Many students will be motivated by knowing how the techniques and subject matter they’re learning fit into their future workplace or life goals.
Here’s a definition of essentialism (from the Geek Feminism Wiki):
The concept of Essentialism states that there are innate, essential differences between men and women. That is, we are born with certain traits. This is often used as an explanation for why there are so few women in science and technology.
In contrast, the critical issue is who is in your classroom, what do they know, and what are their motivations. As How People Learn describes it:
There is a good deal of evidence that learning is enhanced when teachers pay attention to the knowledge and beliefs that learners bring to a learning task, use this knowledge as a starting point for new instruction, and monitor students’ changing conceptions as instruction proceeds.
This is hard to do. We can’t redesign every class for each new student population. What I think Valerie is admonishing us to do is to actually check and not assume certain interests and motivations because of the demographics of the students. When we were developing Media Computation, we did focus groups with students to get their feedback on our developing designs. We surveyed the students to get a sense of what they were interested in and what motivated them. Great work like Unlocking the Clubhouse suggested our starting point, but we did not assume that the majority-female class would have stereotypical responses. We checked with our student population, and we provided different kinds of media interactions to attract different kinds of students within our population.
It would be best if we could provide educational opportunities that meet each student’s needs individually. Short of that, we can design for the students who enter our classrooms, not for the stereotypes that we might expect.