@grimalkina@mastodon.social
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grimalkina

@grimalkina@mastodon.social

Social & Evidence Scientist. Defender of the mismeasured. 🦄🏳️‍🌈 she/they

Studying how developers thrive. My focus areas include how people form beliefs about learning and build strategies for resilience, productivity & motivation. Quant Psych PhD (but with a love for qual) and VP of Getting Tech to Do Real Open Science.

Founder of the Developer Success Lab ❤️
Neighborhood Cool Science Aunt

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grimalkina, (edited ) to random
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This one doesn't bother me but "systems thinking" does or just saying "systems" about everything is the pervasive label I notice 🤣

Very true point ime though I've really been observing this "everything is community" move too

https://akademienl.social/@chartgerink/112591053538125480

grimalkina, to random
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Actually if I weren't working with software teams right now what I wouldn't give to do research on doctors' understanding of and evaluations about causality and the diagnostic and care access consequences of this, it would be fascinating

grimalkina, to random
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Ok enough me complaining about research that I want to read not existing (https://mastodon.social/@grimalkina/112576085634643142), let's do something actionable.

So you're in an engineering org using something like Copilot. You want tips from science so YOU feel you are using them in a way that is efficient & grows your skills vs muting them. Or you want to help colleagues.

(Even if you profoundly disagree w/these tools, there is benefit in a harm reduction approach & knowing what helps the humans right here right now)

grimalkina,
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Don't judge a problem or solution too early. This is just an absolutely foundational thing: we all struggle to stay "engaged" in working a problem. That does NOT mean "grinding" or being exhausted. It means not being distracted by early errors and being able to overcome them well enough to see a solution. Here, perhaps generative tools could be used as a quick check on certain rabbit holes of error triage. Compare and contrast that with the other methods you have for error triage!

grimalkina,
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Elevate the human skills involved in all software work -- this recognition strengthens belonging culture. Being explicit about EFFORT is something many of us don't do enough, particularly if you're in a very "output" driven workplace, making that effort visible might be important advocacy.

Also is a counterbalance: is a tradeoff not being voiced? "this changed how I did x but I saw to make x work we needed y" (like more code...more pressure on colleagues to code review type stuff)

grimalkina,
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Honestly -- most software developers are strongly committed to being lifelong learners, but we are STRUGGLING to have learning CULTURES on teams. Tying learning time, effort, and goals to technological innovation is really key I feel. The moment of generative coding tools could be a moment to make this very clear inside of an org. We see learning culture-high devs report higher team effectiveness and productivity. Learning culture isn't a magical thing it comes from deliberate choices

grimalkina,
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Let's start with some basics that can help you across MANY situations: misconceptions we have about learning!

Think of using these tools as "active learning," not passive. Passively consuming content over and over again is fundamentally inefficient. We "rob ourselves" of the opportunity to learn in the future every time we don't actively reconstruct. Try generating a part of a solution and then writing the next part yourself, and then seeing if the tool generates something similar.

grimalkina,
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Learners with great self-regulation practice reflection. This is another thing we avoid, but where a tiny investment pays off wildly.

Taking fifteen minutes for reflection can wildly strengthen your metacognitive skills. This is how you figure out what your own "deliberate practice" could be. This can be simple. List a small number of things copilot was great at and a small number it wasn't. Explain it to someone else. You'll start to force yourself to be aware of your own mental models

grimalkina,
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Because we often FEEL like it's good to "consume a lot of information" (reading a million stackoverflow threads/throwing prompt after prompt into a window), we can waste a ton of time & exhaust ourselves. Kind of like the work version of browsing social media. Instead, choose small targeted effort over hours of meandering and browsing. This is often called "deliberate practice" and planning WHAT and WHY you are practicing a thing is far more effective. Do it sooner than you feel like

grimalkina,
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Diagnosing our own knowledge gaps is actually half the battle. Experts aren't people without knowledge gaps -- they're people who excel at recognizing them and solving them early!

I've observed in my research that when exploring an unexpected friction or "break" experts do a lot of "anchoring" -- choosing a piece of the codebase or a causal relationship they feel they deeply understand and iterating in tiny steps out from there. This is in line with good learning science!

grimalkina, to random
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Relatedly there needs to be better language for this, like the What Gets On The Plaqueness of a cause of death label which becomes the final line of the intro para of a Wikipedia bio which therefore becomes the summed regurgitation of a generative llm

https://mastodon.social/@grimalkina/112591431146716505

grimalkina,
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Relatedly? I saw a critique shared in a meme from a fellow complex patient about how surgeons only allow themselves to perceive "current imaging" as your medical history will mean nothing in an OR; I experience this contextless medicine with unevenly weighted labels constantly. If you can imply that you have What Gets on The Plaqueness around your doctors care unlocks like a mechanical animation in a heist movie

grimalkina, to random
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So many "developers produce more quantities of code with copilot" studies so few "the patterns of interleaving and retrieval change depending on active vs passive consumption of generated solutions and we have like fifty years of research on this in learning science and so maybe we can apply it to make good recommendations about the best usage of generated work output" studies

grimalkina,
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Actually we could be bringing in loads of useful stuff from edtech research into disparities in how new tech usage is even allowed: for instance, the SAME tools rolled out to people with higher power are often used (and people are rewarded for using them) in completely different ways from people with lower power. HOW we are using a tool is a necessary question, and whose usage gets seen as "smart" vs not. The psychological context sets the interpretation of any tool moment.

grimalkina,
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But you know, as long as software journals don't even want to allow the reporting of participant demographics, we cannot possibly begin to scratch the surface on any of this. I think it is important to consider the selection effects of what we hear about, the long chains of pipe we've laid down that dictate who is heard in this moment, and what complexity is compressed into legible summaries that treat all "developers" like a neutral blank slate, interchangeable "personas."

grimalkina,
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It is not shocking that using Copilot to "creatively iterate" in an agentic way, and for exploratory tasks, is far different from using it in a confirmatory way, for tasks where you lack the skills to evaluate or whether you do test and retest (in a learning sense, not a software sense). The absolute lack of operationalization clarity in this research is really holding us back. WHAT is "using copilot"? We could be drawing from decades of work on how people consume content and active learning

grimalkina,
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Why! (jk I know why: those large tech companies that dominate the studies we hear about mostly would not hire anyone with a social science, cognitive science, or real solid learning science background to do software research even if that person was right in front of them because that is seen as less relevant than a CS degree with a vague hobby 'interest' in human behavior, ask me how I know)

grimalkina,
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@glyph every single research paper I've submitted to a software journal or conference, the reviewers have pushed back on participant demographics -- collecting them at all, or reporting them. It is neither standard nor behind-the-scenes understood imho. I imagine this might vary quite a lot depending on if you have a pool of reviewers you always get sent to or whatever vs kind of random which is the unlucky position I've been in.

grimalkina, to random
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A simple core thesis for a lot of my work might be "our beliefs about things really matter for the world we create and they aren't as fixed as we think they are"

grimalkina,
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This is a messy post but with a lot of threads on this: https://www.drcathicks.com/post/expecting-success

grimalkina,
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"It’s this environment and the explanations that it encourages that has always fascinated me [...] we certainly have a responsibility to intervene on a bad environment that’s pushing the wrong sets of beliefs.

The thing is, other people matter. We matter to other people. Our explanations of our own success become judgments of other people--hence the runaway success of terribly maladaptive achievement beliefs like "only people born magical geniuses can succeed in STEM." "

grimalkina,
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Our beliefs about what it means to be smart. To be good. To have a certain professional identity. What we think communication is, what we think we owe each other (or not). Whether or not we believe other people will see it like we do and what we think will happen if they don't.

grimalkina, to random
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This paradox remains wild to me. I think about my experiences working with teachers who make so little money and suffer so much and yet frequently support each other's learning and directly see the value of their own learning so much. And with developers we have some of the best resourced knowledge workers in the world, fully bought in to the idea of lifelong learning, and absolutely hiding it in the middle of their workplaces that rest on that learning

https://mastodon.social/@grimalkina/112576399100763600

grimalkina, to random
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This incredible story of this incredible student 😭

https://www.universityofcalifornia.edu/news/transfer-students-triumph-class-2024#manuel

I am so so so proud of @analog_ashley for funding, creating and leading the STARTneuro program. Incredible to see this amazing program have its first graduates.

"“STARTneuro is the best thing I’ve ever done in my life,” says Vasconcelos. “I love what I am doing, and I wouldn’t be where I am now if not for this program.”"

grimalkina,
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But guess what -- you can donate to this program if you wish!!

You can learn more about the program overall here: https://ugresearch.ucsd.edu/programs/all-urh-programs/start-neuro/index.html

They have a fund through UCSD: https://giveto.ucsd.edu/giving/home/gift-referral/8dfa8984-7da2-4d59-b762-92621fa6228e

I'm not involved in any way (except for sometimes hosting the scholars at a bbq at our house haha...and a lot of support to the program director), I just think this program is absolutely beautiful and more people should know about it. The future of science is for everyone.

@analog_ashley

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