Recent Projects*
*some of them!
An empirical intervention study (led by Dr. Carol Lee) that described a novel model for code review anxiety and tested an intervention to help developers face and manage anxiety around both giving and receiving code reviews.
What helps developers on software teams thrive? In this empirical observational study, we adapt four key measures of psychological affordances that have been shown to drive "virtuous cycles" for problem-solving and show that they associate with self-reported productivity for +1200 developers across 12+ industries and many demographics. In a mixed-methods design, we further explore the role of the Visibility and Value of software work and developers' perceptions of measurement in their workplaces.
In this quantitative observational study, we explore the experiences of 3000+ software engineers and developers across 12+ industries engaged in the transition to generative AI-assisted software work. We describe a model for AI Skill Threat -- a pervasive experience of worry and anxiety when developers imagine a future of software with AI assistance used in coding. We document emerging equity and opportunity gaps for software teams, and show that teams high in learning culture and belonging show more resilience in the face of AI Skill Threat.
In this scientific review paper I seek to provide a map, an entry point, and a call to action for improving the lives of the people who create software. I propose that the success of developer experience initiatives frequently hinges on the psychological affordances of the environment in which those initiatives are deployed. This paper tackles the psychological theory of social-psychological research on interventions, how the Mindset * Context model can be used to help software teams, and explores three developer-relevant examples to illustrate where intervention science can help technology teams thrive.
This report presents data from a qualitative research project with 25 software developers, who completed a “debugging” task and an in-depth interview reflecting on their learning, problem-solving, and feedback experiences while onboarding to a new collaborative codebase. Drawing from the themes in these qualitative interviews as well as the larger context of psychological theory on learning and problem-solving environments, I define the term "Learning Debt" as a grounded metaphor to describe the systematic effects of an environment that discourages learning which can dampen code writers' creativity and knowledge-sharing. From across the psychological literature and these interviews, I also surface practical recommendations for fostering a better learning culture.
