關於這一集
Professor Mark Guzdial from the University of Michigan reminds us that field of “computer science” was first invented as a discipline or subject matter area that everyone should be taught. At the time, leading scholars deemed it vital to learn about computer science since it could facilitate the learning of other subjects and emerging disciplines. In addition, it could help reduce to obvious inherent danger in have such a powerful technology controlled by a select few people. Such concerns are not unlike those found in the myriad conversations today about generative forms of artificial intelligence (AI). As Guzdial has lamented, computing education, unfortunately, has not become a democratizing force that was first imagined some six decades ago in the 1960’s. Fast forward to the Year 2026 and computer science has a much narrower connotation than originally hoped leading to a world wherein only a privileged few truly understand and contribute to the world of computer science and computing education. Mark Guzdial pines for the original visions of the field and the more general goals for society. However, that would require changing how we teach about computing and what we mean when we refer to computer “programming.” With the ideas and insights of Mark Guzdial, in Episode #269 of Silver Lining for Learning (SLL), we will learn about the history of computing education. Mark will also inform us about a new initiative underway at the University of Michigan to develop computing education for those in the liberal Arts and Sciences; in the process, he will help us expand the common views and possibilities for computer education and computer science. In addition, Mark will be joined by his University of Michigan colleague, Barbara Ericson, who will discuss how instructors who teach programming classes are grappling with fast emerging technology like generative AI. As she has observed, students who are weaker in computer science are more likely to utilize and over rely on generative AI for their code production and other computer science related tasks without actually reflecting on the process or the results. The limited cognitive effort that results is quite alarming. In response, Dr. Ericson will share how innovative pedagogy with free and interactive ebooks, mixed-up code (Parsons) problems, forms of peer instruction, Process Oriented Guided Inquiry Learning (POGIL), and open-ended projects can make the learning of computer science more active, socially engaging, and collaborative where students are encouraged to think deeply and connect seemingly disparate ideas in this age of generative AI.
Mark Guzdial’s Bio: Mark Guzdial is a Professor in Computer Science & Engineering and Director of the Program in Computing for the Arts and Sciences at the University of Michigan. He studies how people come to understand computing and how to make that more effective. He was one of the founders of the International Computing Education Research conference. He was a lead on the NSF alliance “Expanding Computing Education Pathways” which helped US states improve and broaden their computing education. He received the 2019 ACM SIGCSE Outstanding Contributions to Education award. With his wife and colleague, Barbara Ericson, he received the 2010 ACM Karl V. Karlstrom Outstanding Educator award. He is a Fellow of the ACM and of AAAS. He has recently completed the second edition of Learner-Centered Design of Computing Education: Research on Computing for Everyone.
- Google Scholar: https://scholar.google.com/citations?user=iQV2L2IAAAAJ&hl=en
- Homepage: https://guzdial.engin.umich.edu/
- CV: https://guzdial.engin.umich.edu/wp-content/uploads/sites/402/2023/06/Guzdial-March2023.pdf
- LinkedIn: https://www.linkedin.com/in/mark-guzdial-9a33851/
Barbara Ericson’s Bio: Dr. Ericson got her PhD in Human Centered Computing in 2018 from Georgia Tech and is now an Associate Professor at the University of Michigan. She applies research results from educational psychology to help students learn to program. She creates free and interactive ebooks with new types of practice problems including some that leverage generative AI. Dr. Ericson is part of the Generative AI in CS Education Consortium and helped create materials for free CS1 and CS2 courses that leverage AI. She won the 2022 ACM SGICSE Award for Outstanding Contributions to Computer Science Education. She is also a distinguished member of the ACM.
- Homepage: https://www.si.umich.edu/people/barbara-ericson
- Google Scholar: https://scholar.google.com/citations?user=AHXNTMgAAAAJ&hl=en
- LinkedIn: https://www.linkedin.com/in/barbara-ericson-3bb6779/
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