These days I've been really keen on qualitative studies, where scientists work on building a better understanding of software instead of trying to validate theo

These days I've been really keen on qualitative studies, where scientists work on building a better understanding of software instead of trying to validate theories. Some examples of that: https://link.springer.com/article/10.1007/s10664-016-9464-2 https://link.springer.com/article/10.1007/s10664-016-9464-2 — scientists followed a team of developers for three years and recorded all of their sprint retrospectives and people kept forgetting what they already learned. https://jlubin.net/assets/oopsla21.pdf https://jlubin.net/assets/oopsla21.pdf — researchers compiled 23 hours of Zoom sessions and 15 hours of Twitch programming livestreams to study how people write code in static FP languages. In addition to that, there's a lot of good work on how we teach programming. "Commonsense Computing" [1] found that students understand concurrency a lot faster when presented as a "human" problem, such as selling tickets in a concert. I'd recommend reading Teaching Tech Together (http://teachtogether.tech http://teachtogether.tech), which references a lot of empirical papers on teaching programming. [1]: https://cseweb.ucsd.edu/classes/fa08/cse599/Papers/ICERConcurrencyFINAL.pdf https://cseweb.ucsd.edu/classes/fa08/cse599/Papers/ICERConcu...