Japan plans to make programming mandatory at schools as a step to foster creativity: What if it doesn’t work?
Japan is planning to make programming mandatory in all their schools because it will help their children to think logically and creatively. Except, we don’t have evidence that it does. We know a little about how to use programming as a medium for developing thinking skills, but I know of no efforts to make it replicable and scalable. I don’t know of anyone using programming in order to improve creativity. I know of no evidence that learning to program improves creativity.
This is a nation-size gamble. I’m interested in how Japan goes about this — they face the same challenges as NYC does in their initiative, at an even larger scale.
It is essential that computer programming to be taught in schools will lead to improving children’s ability to think logically and creatively.
Annie Murphy Paul is talking about inclusive teaching here, but she could just as well be talking about active learning. The stages are similar (recall the responses to my proposal to build active learning methods into hiring, promotion, and tenure packages). These are particularly critical for computing where we have so little diversity and CS teachers are typically poor at teaching for diverse audiences.
Stages of Inclusive Teaching Acceptance
Denial: “I treat all my students the same. I don’t see race/ethnicity/gender/sexual orientation/nationality/disability. They are just people.”
Anger: “This is all just social science nonsense! Why won’t everyone just get over this PC stuff? When I went to grad school, we never worried about diversity.”
Bargaining: “If I make one change in my syllabus, will you leave me alone?”
Depression: “Maybe I’m not cut out to teach undergraduates. They’re so different now. Maybe I just don’t understand.”
Overwhelmed: “There is so much I didn’t know about teaching, learning, and diversity. How can I possibly accommodate for every kind of student?”
Acceptance: “I realize that who my students are and who I am influences how we interact with STEM. I can make changes that will help students learn better and make them want to be part of our community.”
It’s just plans and campaign promises, but it’s nice to see.
Invest in Computer Science and STEM Education by:
Providing Every Student in America an Opportunity to Learn Computer Science: To build on the President Obama’s “Computer Science Education for All” initiative, Hillary will launch the next generation of Investing in Innovation (“i3”) grants, double investment in the program, and establish a 50% set-aside for CS Education.
Engaging the Private Sector to Train up to 50,000 Computer Science Teachers: Hillary will launch an initiative to expand the pool of computer science teachers—both through recruiting new teachers into the field, and through helping current teachers in other subjects gain additional training.
Encouraging Local STEM Education Investments: Hillary’s Department of Education will support states and districts in developing innovative schools that prioritize STEM, implementing “makerspaces,” and build public-private partnerships.
The Connected Learner is an interesting project led by Mary Lou Maher at the University of North Carolina Charlotte. Her blog post quoted below points to one of the difficulties in talking about teaching among CS faculty.
It seems relatively uncommon for research-track CS faculty to discuss their teaching at conferences and research meetings (no, I’m not saying it never happens, but it is rarely the focus, except at CS education conferences like SIGCSE and ICER). So, while we are likely aware of our colleagues’ research projects, we may not realize that our colleagues are experimenting with innovative teaching methods, trying out new learning technologies or adapting some best practices related to active learning. Because we don’t talk about it, we may think it’s not happening and this can lead to us not wanting to talk about our own innovations. We think our colleagues only value core research, so that is what we focus our own discussions on.
Casey Fiesler and Miranda Parker did a wonderful remix of the original computer engineer Barbie (see Guardian article about that). Great to see that Mattel did a better job the next time around, and Casey loves it. I love the point she makes below, which echoes a concern I’ve voiced about open source software.
This is particularly important is because as much as we don’t want to suggest that girls can’t code, we also don’t want to suggest that coding is the only path to working with computers or games. Sometimes other parts of computing—like design or human-computer interaction—are delegitimized, considered less rigorous or less important. Or maybe they’re delegitimized in part because they happen to be the parts of computing where there are more women present (in other words, more inclusive), which is even worse.
Interesting and relevant for this list. There’s a lot in the NSF big ideas document (see link here) about using technology for learning, but there’s also some on what we want students to know (including about computing technology), e.g., “the development and evaluation of innovative learning opportunities and educational pathways, grounded in an education-research-based understanding of the knowledge and skill demands needed by a 21st century data-capable workforce.”
The six “research” ideas are intended to stimulate cross-disciplinary activity and take on important societal challenges. Exploring the human-technology frontier, for example, reflects NSF’s desire “to weave in technology throughout the fabric of society, and study how technology affects learning,” says Joan Ferrini-Mundy, who runs NSF’s education directorate. She thinks it will also require universities to change how they educate the next generation of scientists and engineers.
I’ve talked about Kamau Bobb’s work in this blog previously, when he wrote a depressing but deeply-insightful op-ed about the state of mathematics education in Atlanta public schools. He’s recently been interviewed in a three part series in Black Enterprise about his role as an NSF program officer. The below quote is from Part II — I recommend the whole series.
The most significant challenge facing STEM education and the workforce is the capacity of the U.S. educational system to produce interested and qualified participants in the STEM enterprise. Here is where the racial and socio-economic challenges facing the nation are most glaring.
According to the National Center for Education Statistics National Report Card, there are some damning realities that significantly challenge STEM education and the STEM workforce. In 2015, only 33% of all eighth grade students in the U.S. were proficient or better in mathematics. Only 13% of black eighth graders and 19% of Hispanic eighth graders were proficient or better in mathematics, which is in contrast to 43% of white students and 61% of Asian students. For students who live in poverty and qualify for the National School Lunch Program, only 18% were proficient in eighth grade mathematics.
According to the College Board, only 16% of black students are college or career ready by the time they take the SAT in eleventh grade. For Hispanic students, 23% are ready. For Asian and white students, 61% and 53%, respectively, are ready for higher education or to take on meaningful work. This landscape is a problem.