Posts tagged ‘computing education’
The New York Times ran a pair of articles on computing education yesterday, one on Computational Thinking (linked above and quoted below) and one on the new AP CS Principles exam. Shriram and I are quoted as offering a more curmudgeonly view on computational thinking. (Yes, I fixed the name of my institution in the below quote, from what how it is phrased in the actual article.)
Despite his chosen field, Dr. Krishnamurthi worries about the current cultural tendency to view computer science knowledge as supreme, better than that gained in other fields. Right now, he said, “we are just overly intoxicated with computer science.”
It is certainly worth wondering if some applications of computational thinking are trivial, unnecessary or a Stepford Wife-like abdication of devilishly random judgment.
Alexander Torres, a senior majoring in English at Stanford, has noted how the campus’s proximity to Google has lured all but the rare student to computer science courses. He’s a holdout. But “I don’t see myself as having skills missing,” he said. In earning his degree he has practiced critical thinking, problem solving, analysis and making logical arguments. “When you are analyzing a Dickinson or Whitman or Melville, you have to unpack that language and synthesize it back.”
There is no reliable research showing that computing makes one more creative or more able to problem-solve. It won’t make you better at something unless that something is explicitly taught, said Mark Guzdial, a professor in the School of Interactive Computing at Georgia Tech who studies computing in education. “You can’t prove a negative,” he said, but in decades of research no one has found that skills automatically transfer.
C.P. Snow got it right in 1961. Algorithms control our lives, and those who don’t know what algorithms are don’t know what questions to ask about them. This is a powerful argument for universal computing education. I like the below quote for highlighting that a better term for the concern is “model,” not “algorithm.”
Discussions about big data’s role in our society tends to focus on algorithms, but the algorithms for handling giant data sets are all well understood and work well. The real issue isn’t algorithms, it’s models. Models are what you get when you feed data to an algorithm and ask it to make predictions. As O’Neil puts it, “Models are opinions embedded in mathematics.”
There was interest in our slides from the 2017 SIGCSE Panel, “The Role of CS Departments in The US President’s “CS for All” Initiative.” They are linked above, and summarized below.
In January 2016, US President Barack Obama started an initiative to provide CS for All – with the goal that all school students should have access to computing education. Computing departments in higher education have a particularly important role to play in this initiative. It’s in our best interest to get involved, since the effort can potentially improve the quality of our incoming students. CS Departments have unique insights as subject-matter experts to inform the development of standards. We can provide leadership to inform and influence education policy. In this session, we will present a variety of ways in which departments and faculty can support CS for All and will answer audience questions about the initiative. Our goal is to provide concrete positive actions for faculty.
Barbara Ericson spoke on influencing our incoming students and using outreach to improve the number and diversity of students and to improve the number and quality of teachers.
Rick Adrion spoke on CS faculty providing subject-matter expertise to standards efforts. A key role for CS faculty is to help teachers, administrators, and public policy makers to understand what CS is.
Megean Garvin spoke on how CS faculty can provide a leadership role. Faculty have a particular privileged position to draw together diverse stakeholders to advance CS Education.
There is a ton of CS Ed at SXSWEdu March 6-9. An entire list has been posted here: http://tinyurl.com/CSatSxSWedu
Aman Yadav and Steve Cooper have the CACM Viewpoints Education column this month. They raise the questions of how learning computing can lead to greater creativity, and how we can design computing education experiences to draw students in to greater depth.
Computing has the potential to provide users opportunities to extend their creative expression to solve problems, create computational artifacts, and develop new knowledge. The pervasive nature of computing and accessibility of digital tools is also transforming K-12 education as students move from being mere consumers of content to engaging in the subject matter by creating computational artifacts. Take Scratch, for example, which is one of the many tools designed to teach kids to code, and comes with varying levels of support for educators implementing them in both formal and informal learning settings. Scratch provides students with an opportunity to express their creativity through stories, games, and animations. While Scratch has the potential to be a powerful tool, it is often used as little more than a presentation tool in the classroom. Studies of Scratch users show that few projects use variables or control flow data structures. While the Scratch environment provides a ‘low floor, high ceiling’ that allows beginners to dive into the environment without frustration, many students do not advance to a higher level. Tools like Scratch can empower students to showcase their creativity like never before; however, the way these tools are taught by teachers and used by students significantly influences whether students move along the creativity continuum. While Scratch is widely used, we know little about how it influences students’ creative thinking.
Julie Flapan and Jane Margolis had a piece last month in Education Week saying that the Trump administration should support CS education. Their piece starts with an argument that we should not scapegoat immigrants, and given the recent immigrant ban, seems amazingly prescient.
Julie and Jane point out that CS education is important to the values of the new administration. It’s good to see that the House is re-affirming the importance of STEM education in their new priority statement. We need to make the argument that computing education is not a previous adminstration issue, but is instead about bipartisan issues and values.
Computer science isn’t just about operating a computer or a cellphone. It’s about reimagining how computers are a part of what we do every day. Rather than being passive users of technology, students need to learn how to be responsible creators of it. Computer science teaches algorithmic thinking, problem-solving, and creativity as students learn how to build apps, design a web page, and understand how the internet actually works.
Beyond jobs, this past year revealed other reasons why learning computer science is important in a democracy. Whether it be through thinking critically to distinguish fake news from real news, understanding algorithms that are used to target its users, considering cybersecurity and the role it played in email scandals, or amplifying marginalized voices through social media, we can see the power of technology in our everyday lives. Becoming digitally literate, critical, and constructive thinkers about how to use technology responsibly should be required learning for everyone.
With the uncertainty of President Donald Trump’s education agenda and the future policy decisions under the Every Student Succeeds Act, one thing is clear: We need to continue to support public education and the inclusion of computer science as part of the new law’s call for a “well-rounded education.”
We encourage the new administration to continue to support the former administration’s national agenda to promote computer science for all, which prioritizes the needs of students underrepresented in computer science, including girls, low-income students, and students of color. Many education leaders support this national initiative at the local level.