Step 85: Teach Technical Writing

One of Oxy’s graduation requirements is that students must complete a “discipline-specific writing” course in their major. The exact implementation of this requirement is up to the department: Cognitive Science considers passing any upper-level course to be sufficient, Physics requires students to submit lab reports to a portfolio, while students in Mathematics must take a two-unit Junior Colloquium. For Computer Science, we decided that a junior seminar course would work best – students simply do not write enough in other courses to compile a portfolio.

Since I will likely teach the first offering of the Junior Seminar next Spring, I have been thinking about the writing errors that students make. By coincidence, all three of the courses I taught this past semester required some writing. Students in Intro to Cog Sci had to write two ~1800 word papers; students in Topics in AI had to write short essays as part of their homework; and even students in Data Structures had to write to justify their complexity analysis and explain their choice of data structure for an application. This trend will continue into the Fall, as I will be teaching the writing-based Cognitive Science Senior Comprehensive projects as well.

(Separately, how common is it for students to be writing in Data Structures or any other computer science course? Outside of Software Engineering Practicums and more so Senior Capstones, I don’t remember writing much in my undergraduate CS courses. Teaching Data Structures though, I am confused why I didn’t – the programming projects provided technical depth, while writing addresses some of the breadth of Data Structures. But that’s a topic for another post.)

I struggled to find overarching patterns in students’ writing more descriptive than general writing advice (eg. be specific, be concrete, signpost, etc.). If I had to identify the single biggest problem though, it would be that students don’t know how to make “arguments”. I don’t mean the strength of their evidence or how their essay is structured, but the kind of claims that they make and how to tie that back into their thesis. I put “arguments” in quotes because this does not apply only to building persuasive essays, but also the composition of explanatory pieces.

I have two examples from this semester. First, one paper in Intro to Cog Sci asks students how Marr’s levels of analysis lead to “a coherent understanding of human visual perception”. Anticipating that this prompt will be challenging, I required students to submit an outline two weeks before the final due date. From these works in progress, it was clear that many students did not address the “coherent” part of the topic. Instead, most students listed different applications for each of the levels of analysis, but remained silent on how the levels integrate with each other. A few students strengthened their argument in the final essay, but most papers remained weak even after receiving feedback.

The second example is from Topics in AI, where I asked students to take a popular-media article about some AI application, then research and explain how the underlying algorithm works. Students did do this, but not to the specificity that I want. For example, several students found applications of deep learning, but did not explain that training involves modifying the weights, nor what format the inputs and outputs were. These oversights are similar to the ones my previous students made when applying reinforcement learning. In both cases, I felt the final essays did not demonstrate the technical understanding that students had of the subject.

The second example, in particular, made me wonder how much the students’ true inability is in writing or argumentation. The first example might be considered a philosophy of science paper, while the second asked for computer science knowledge. These essays are necessarily discipline-specific, even the one for the introductory course, and students likely do not have the requisite argument content knowledge (to draw parallels with pedagogical content knowledge). Such a hypothesis would imply that even if students are already capable writers, they would need additional training to learn the acceptable types of arguments for each discipline – and that we as instructors must teach them to do so.

I consider myself a decent writer, but I have never been trained as a writing instructor and I’m still learning what works and what doesn’t. Providing feedback on outlines and leaving time for peer review helps, but not to the degree I want. In the future, I might adopt the extremely detailed grading rubric for philosophy papers that went viral recently. I have been thinking of going one step further – I would like to create examples of disciplinary writing of varying quality, together with an analysis of the strengths and weaknesses, to provide a reference for students. It’s unclear whether this effort needs to be duplicated for each type of writing (eg. an informative piece as compared to a project proposal), but I hope that more practice teaching writing courses will help me understand what best helps students.

Step 85: Teach Technical Writing

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