Coaching my kids’ sports teams has changed how I think about learning. When I first started coaching, my instinct was to point out what kids were doing wrong. It felt direct, efficient—even helpful. But I’ve learned that it rarely leads to improvement.
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What works better is focusing on specific adjustments. Instead of just saying, “That’s wrong—do it this way,” I try to create a path from where they are to where they need to be. I show the adjustment, break it down, make sure they understand it, and give them something they can actually do in the moment. So when John makes the same mistake again, I don’t say, “You’re doing it all wrong.” I just remind him: make the adjustment.
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I’ve started to carry that idea into my work with students. Of course, there are right and wrong ways of doing things—correct answers, better approaches—but learning doesn’t come from simply being told which is which. It comes from finding a path toward understanding and staying with it. Our role isn’t just to identify errors, but to help students see the next step—and to be curious, even excited, to encounter the one after that.
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Coming Up in the Faculty Hub
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Tuesday, April 21 & Wednesday, April 22
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Craig Mod argues that AI tools like Claude Code are collapsing the gap between idea and implementation, making it possible for individuals to build highly personalized software without formal engineering expertise. Instead of relying on generic, subscription-based tools, he describes a shift toward “software for one”—tools designed around a single person’s workflow, data, and goals. The result is a new kind of creative and scholarly agency, where researchers and creators can prototype, automate, and shape their own systems rather than adapt to existing ones. Read Mod's essay on going software bonkers here.
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Program Spotlight: Leveraging AI Workflows To Support Scholarship
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Building on what Craig Mod describes in "Software Bonkers" as “software for one” is quickly becoming a practical reality for researchers. Have you ever thought, “If only I had a software developer…”? New AI tools like Claude Code and OpenAI Codex are making it possible for researchers to prototype, build, and automate their own workflows—no formal programming background required. In this session, we’ll explore how these tools can support your research process: from cleaning and analyzing data, to building custom tools, to streamlining repetitive tasks. The goal is not just efficiency, but expanding what’s possible in your scholarly work. Join us for Leveraging AI Workflows To Support Scholarship on Thursday, May 14, from 10 to 11:50 a.m. to see what this new layer of “AI-assisted development” might unlock in your own research.
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We are always looking for new and exciting projects and collaborations. Feel free to contact us.
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