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.
My Blog@CACM post for this month is about imagining the remedial teaching techniques of a school-based “Computing Lab” in the near future.
It’s becoming obvious that computing is a necessary skill for 21st Century professionals. Expressing ideas in program code, and being able to read others’ program code, is a kind of literacy. Even if not all universities are including programming as part of their general education requirements yet, our burgeoning enrollments suggest that the students see the value of computational literacy.
We also know that some students will struggle with computing classes. We do not yet have evidence of challenges in learning computation akin to dyslexia. Our research evidence so far suggests that all students are capable of learning computing, but differences in background and preparation will lead to different learning challenges.
One day, we may have “Computing Labs” where students will receive extra help on learning critical computational literacy skills. What would happen in a remedial “Computing Lab”? It’s an interesting thought experiment.
I list several techniques in the article, and I’m sure that we can come up with many more. Here’s one more each DO and DON’T for “Computer Lab” for struggling computationalists.
- DO use languages other than industry standard languages. As I’ve mentioned before in this blog, CS educators are far too swayed by industry fads. I’m a big fan of Livecode, a cross-platform modern form of HyperCard. An ICER 2016 paper by Raina Mason, Simon et al. estimated Livecode to have the lowest cognitive load of several IDE’s in use by students. If we want to help students struggling to learn computing, we have to be willing to change our tools.
- DON’T rely on program visualizations. The evidence that I’ve seen suggests that program visualizations can help high-ability students, and well-designed program visualizations can even help average students. I don’t see evidence that program visualizations can help the remedial student. Sketching and gesture are more effective for teaching and learning in STEM than diagrams and visualizations. Sketching and gesture encourage students to develop improved spatial thinking. Diagrams and visualizations are likely to lead remedial students into more misconceptions.
The CS K-12 Framework was released Monday. This has been an 11 month long process — see first blog post about the framework, first blog post on the process, and the post after my last meeting with the writers as an advisor. The whole framework can be found here and a video about the framework can be found here:
A webinar about the Framework will be held on Wednesday, October 19, at 12 PM Pacific / 3 PM Eastern. Visit https://www.youtube.com/watch?v=wmxyZ1DFBwk for more details and to watch the webinar on the 19th.
I believe that this framework is about as good as we can expect right now. Pat Yongpradit did an amazing job engaging a broad range of voices in a short time. The short time frame was forced on the process by the state policymakers who wanted a framework, something on which they could hang their state standards and curricula. The NGSS veterans did warn us what could happen if we got it wrong, if we went too fast. Maybe the framework process didn’t go too fast.
The framework document is impressive — comprehensive, carefully constructed, with a rich set of citations. It’s teacher-centric, which may not be the best for a document to inform state standards, but that’s the constituency with the strongest voice in CS Ed today. There are too few CS Ed informed policymakers or district administrators to push back on things that might not work work. The CS Ed researchers are too few and too uncertain to have a strong voice in the process. Computer scientists (both professional and academic) generally ignored the process. The CS teachers had the greatest political influence.
I predicted in January that this would be a “safe list,” a “subset of CS that most people can agree to.” I was wrong. There’s a lot in there that I don’t see as being about computation. Like “Create team norms, expectations, and equitable workloads to increase efficiency and effectiveness” — that’s a high school computing recommendation? Like “Include the unique perspectives of others and reflect on one’s own perspectives when designing and developing computational products” — you can achieve that in high school?
Those “aspirational” statements (Pat’s word) mean that the writers went beyond defining a consensus document. They tried to push future CS education in the ways that they felt were important. Time will tell if they got it right. The framework fails if schools (especially under-resourced schools) decide that it’s too hard and give up, meaning that underprivileged kids will continue to get no CS education. If teachers and administrators work harder to provide more and better CS education because of this document, then the framework writers win.
This is an important document that will have a large influence. Literally, millions of schoolchildren in several states are going to have their CS education defined by this document.
Typing that statement gives me such a sinking feeling because we just don’t have the research evidence to support what’s in the framework.
When I went to meetings, I too often heard, “Of course, teachers and students can do this, because it works in my program.” So few computing education programs (e.g., packages of curriculum, professional development, assessment, and all the things teachers need like pacing guides and standards crosswalks) have scaled yet in diverse populations. Maybe it works in your program. But will it work when it’s not your program anymore? When it’s a national program? When states and districts take it over and make it their own? Will it still work?
And we want schools and districts to make things their own. That’s at the heart of the American educational system — we’re distributed and diverse, with thousands of experiments going on at once. I worry about how little knowledge about computing and computing education is out there, as guidance when schools and districts make it their own.
So, yeah, I’m one of those uncertain researchers, mumbling in the corner of this process, worrying, “This could go so wrong.” Maybe it won’t. Maybe this will be the first step towards providing a computing education for everyone.
The die is cast. Let’s see what happens.
Insightful interview with Richard Tapia. He understands issues about broadening participation in computing and talks about them frankly.
You have said, “Underrepresentation is a much greater danger to the health of the nation than to the health of the discipline.” Can you explain what you meant by that?
The disciplines of math and science are in good shape and will continue to flourish without the involvement of women and underrepresented minorities. Of course many of the applications will be impacted by the presence of women and minorities in these application areas. But the theory will continue to be healthy without the involvement of these groups. However, the backbone of America has been mathematics, science, and engineering. We have historically led the world in these areas. Our changing demographics show that the country is becoming not only more Hispanic but significantly more. If we do not involve women and minority groups in our backbone activity, we will have no one to do the work and the nation will most certainly suffer and lose global competitiveness.
Source: People of ACM – Richard Tapia
I’ve only just started reading this new report from National Academies Press, but am finding it useful and interesting. What do we mean when we say that we want people to be scientifically literate? It’s an important question to ask when considering the goal of computational literacy.
Science is a way of knowing about the world. At once a process, a product, and an institution, science enables people to both engage in the construction of new knowledge as well as use information to achieve desired ends. Access to science—whether using knowledge or creating it—necessitates some level of familiarity with the enterprise and practice of science: we refer to this as science literacy.
Science literacy is desirable not only for individuals, but also for the health and well-being of communities and society. More than just basic knowledge of science facts, contemporary definitions of science literacy have expanded to include understandings of scientific processes and practices, familiarity with how science and scientists work, a capacity to weigh and evaluate the products of science, and an ability to engage in civic decisions about the value of science. Although science literacy has traditionally been seen as the responsibility of individuals, individuals are nested within communities that are nested within societies—and, as a result, individual science literacy is limited or enhanced by the circumstances of that nesting.
Science Literacy studies the role of science literacy in public support of science. This report synthesizes the available research literature on science literacy, makes recommendations on the need to improve the understanding of science and scientific research in the United States, and considers the relationship between scientific literacy and support for and use of science and research.
I’m not a big fan of the method in this paper — too little was controlled (e.g., what was being taught? how?). But I applaud the question. Where are things working and where are they not working when using coding to help students learn something beyond coding? We need more work that looks critically at the role of introducing computing in schools.
Nevertheless, there is a lack of empirical studies that investigate how learning to program at an early age affects other school subjects. In this regard, this paper compares three quasi-experimental research designs conducted in three different schools (n=129 students from 2nd and 6th grade), in order to assess the impact of introducing programming with Scratch at different stages and in several subjects. While both 6th grade experimental groups working with coding activities showed a statistically significant improvement in terms of academic performance, this was not the case in the 2nd grade classroom.
Maryland school district showcases computer science education at all levels: ECEP’s role in Infrastructure
The Expanding Computing Education Pathways (ECEP) Alliance, funded by NSF to support broadening participation in computing through state-level efforts, is one of the more odd projects I’ve been part of. I don’t know how to frame the research aspect of what we’re doing. We’re not learning about learning or teaching, nor about computer science. We’re learning a lot about how policy makers think about CS, how education is structured in different states (and how CS is placed within that structure), and how decision-making happens around STEM education.
It’s not the kind of story that the press loves. We’re not building curriculum. We don’t work directly with students or teachers. We fund others to do summer camps and provide professional development. We help states figure out how to measure what’s going on in their state with computing education. We help organize (and sometimes fund) meetings, and we get states sharing with each other how to talk to policy makers and industry leaders.
So it’s nice when we get a blurb like the below, in a story about the terrific efforts to grow CS for All in Charles County, MD. It’s amazing how much Charles County has accomplished in providing computing education in every school. I’m pleased that ECEP’s role got recognized in what’s going on there.
Expanding Computer Education Pathways (ECEP) provided grant funding for summer camp computer programs. CCPS’s facilitators participate in their Train-the-Trainer webinars to design and plan an effective workshop, build an educator community, increase diversity in Computer Science and teach Computer Science content knowledge. ECEP also funded the Maryland Computer Science Summit in a joint effort with Maryland State Department of Education to bring over 200 attendees from every county in Maryland to share and set priorities for Computer Science education.