Designing CS101: Failure-Driven Course Design

In Agile Education and the CS Principles Course, I criticized learning objectives like:

• "The student can analyze the effects of computing within economic, social, and cultural contexts." (Objective 4)
• "The student can use abstractions and models to solve computational problems and analyze systems." (Objective 5)

These appear to have no answer to Question #1 in the 6-question framework: What mistakes are people making that matter, and who cares? What goes wrong when people don't or can't do Objective 4? Outside of essays and exam questions in the CS Principles Course, where does this skill matter? Is there some subgroup for whom this skill is critical? Who and when?

With Objective 5, I can think of some people to whom it might matter: computer scientists and software developers. There are two problems though. First, this is a much narrower group than the CS Principles Course is being developed for. Second, I can only say "might" because I need to see typical examples of developers not using abstractions and models, and what the negative consequences are. What's the evidence that this occurs often enough to be of concern, and is harmful when it does occur?

All of the CS Principles learning objectives have this problem, except those directly about programming, such as

• The student can create a computational artifact through programming.

But the point of CS Principles was that there's more to CS that people should know besides programming.

So can we answer Question #1? Let's step back, as good Agile developers do, and ask "what's the goal of the CS Principles project?" Like many committee and community-built curricula, a number of goals have accrued. A summary of them can be found in the Open Letter to the Computer Science community.

One impetus certainly is the feeling by many in CS that most people, including students, teachers, parents, and so on, think computer science means programming, programming is boring, and therefore students choose not to pursue a career in computer science.

That feels like a real mistake, but Question #1 also asks who cares and why? I can think of 3 major groups:

• employers
• the government
• students

Employers care because they need good developers. But that's back to programming plus other developer skills. Not where the CS Principles initiative arose from.

The government, especially NSF, cares because they want the US to maintain a lead in research in new forms of information technology. That's good. A CS Principles Course about the big ideas, where they came from and where new ones are coming from, would help address a failure they care about.

Students should care. It's in their own best interests to know whether CS is a career they might actually enjoy and do well in.

So we can argue for a course on how to be a software developer or a computer scientist. But the proponents of CS Principles have a broader aim. Peter Denning in a number of essays on the Great Ideas in CS, Jeannette Wing in various essays and talks on Computational Thinking, and others, have said that a big mistake students make is not knowing how to approach problems in science, engineering, and social issues, from a computational perspective.

The relevant parts in the Open Letter are these two bullet points:

• With a concepts-rich curriculum that emphasizes computational thinking and problem solving students taking the course will be better prepared for most careers, given the role that computing plays in most sectors of American life.
• The population at large -- starting with present day high school students -- will become more knowledgeable and cognizant of computing and computational phenomena.

I'm unconvinced. Students certainly need to be tech-savvy. But they are, often more so, when it comes to social media, than most of the faculty in CS departments. But do they really need computational thinking? Where exactly, outside of programming and CS research, does it matter if someone doesn't apply computational thinking?

I can easily see "here's why it matters" arguments for subareas of computational thinking for subgroups of students. Students in biology should know about multi-agent simulations. Students in cognitive psychology should know about cognitive modeling. There are motivating examples of muddled thinking failures in those and other fields due to the inability to think computationally.

But I'm unable to see why poets, playwrights, and plumbers need to know about computational thinking. Without convincing examples of "why does this failure matter?" a course design is doomed. Students will view CS Principles as yet another irrelevant rite of passage, like learning the parts of a neuron, the lifecycle of stars, the dynasties of China, and so on.

So, I'll stick with the answer "students who don't know what CS is about miss out on a chance to find a career they'll really enjoy in software development or computer science." Phew! One question down, five more to go.

Agile Education and the CS Principles Course

One of the things about the Agile movement that attracted me from the beginning was how proponents would go back to the core goals of development, like "getting something working that the client really needs," and from that develop practices that turned standard development idea on their head. That resonated with my own experiences in how to attack problems like natural language understanding and the design of learning environments.

I recently gave an internal "brown bag" talk on how several of these upside-down Agile practices could be fruitfully applied to educational design and academic research.

Then I happened across the AP CS Principles course, and specifically their learning outcomes document (PDF). I have great respect for the goal, the people involved, and the effort invested, but that "requirements" document is wrong in so many ways that I felt a need to try and articulate why.

My own approach to designing courses and other learning experiences is based on the 6-question framework developed by Alex Kass, Ray Bareiss, Danny Edelson and myself in response to the many flawed designs we'd seen (or created) over the previous decade at the Institute for the Learning Sciences at Northwestern.

Question #1 in that framework, "What mistakes are people making that matter, and who cares?" is the most critical. It defines what you need to teach. It's where at least half the designs we saw failed, including the CS Principles learning outcomes. Pull out just the statements about what a student will learn to do. Here are two:

• "The student can analyze the effects of computing within economic, social, and cultural contexts."
• "The student can use abstractions and models to solve computational problems and analyze systems."

Try and find any outcomes that a student would say "I can't do that but I'd love to learn how!"

In case it's not clear why this matters, read the UW CSE120 blog on a pilot run of this course. Look where student engagement occurred. Without engagement, nothing else happens when it comes to learning

It's easy to criticize. That's the point of this blog. But it's not enough to criticize. What would a better answer look like? What would happen if I applied the 6-question framework to the course with the same intent as the CS Principles course?

That's my plan for the next several blog posts. Stay tuned.