The Role of Emotion in Computing Education, and Computing Education in Primary School: ICER 2017 Recap

I wrote my Blog@CACM post in August about the two ICER 2017 paper awards:

• Danielsiek et al’s development of a new test of student self-efficacy in algorithms classes;
• Rich et al.’s trajectories of K-5 CS learning, which constitute an important new set of theories about how young students learn computing.

Rich et al.’s paper is particularly significant to me because it has me re-thinking my beliefs about elementary school computer science. I have expressed significant doubt about teaching computer science in early primary grades — it’s expensive, there are even more teachers to prepare than in secondary schools, and it’s not clear that it does any longterm good. If a third grader learns something about Scratch, will they have learned something that they can use later in high school? Katie Rich presented not just trajectories but Big Ideas. Like Big Ideas for sequential programming include precision and ordering. It’s certainly plausible that a third grader who learns that precision and ordering in programs matters, might still remember that years later. I can believe that Big Ideas might transfer (at least, within computing) over years.

I was struck by a recurring theme of emotion in the papers at ICER 2017. We have certainly had years where cognition has been a critical discussion, or objects, or programming languages, or student’s process. This year, I noticed that many of these papers were thinking about beliefs and feelings.

• Most obvious is the Chairs Award paper by Danielsiek et al on a measure of self-efficacy, what students believe about their own success in algorithms.
• The next most obvious is the paper out of Michigan State on Students’ Emotional Reactions to Programming Projects in Introduction to Programming: Measurement Approach and Influence on Learning Outcomes
• A paper out of New Zealand looked at what students drew when asked to draw what programming meant to them. Lots of dollar signs in these pictures. (The ‘Art’ of Programming: Exploring Student Conceptions of Programming through the Use of Drawing Methodology.)
• Even James Prather et al’s paper about novice interactions with compiler error messages (definitely a programming language related issue) spent time considering issues of frustration.
• Thomas Price et al’s paper about when students ask for help dealt significantly with the students beliefs about whether a human or a computer tutor was more likely to be able to help them.
• When Brian Dorn presented the paper by Tracie Evans Reding and himself about the teacher experience in CS professional development, he used a roller coaster as a visual metaphor at the start of his talk. It was all about the rise and fall in teacher confidence and beliefs.
• As I mentioned in my earlier blog post, the paper by Thayer and Ko on bootcamps talked about what bootcamp attendees believed going into the camp, their deep frustration with the camp, and the pain of being unable to find a job afterwards.

I find this set of papers interesting for highlight an important research question: What’s the most significant issue influencing student success or withdrawal from computer science? Is it the programming language they use (blocks vs text, anyone?), the kind of error messages they see, the context in which the instruction is situated, or whether they use pair programming? Or is the most significant issue what the students believe about what they’re doing? And maybe all of those other issues (from blocks to pairs) are really just inputs to the function of student belief?

(Be sure to check out Amy Ko’s summary of ICER 2017.)