The chapter delves into the upcoming 2024 survey concentrating on artificial intelligence, workplace environment, and platform engineering. It emphasizes the significance of comprehending developers' utilization of AI, workplace antecedents, and varying perceptions of platform engineering while acknowledging the complexities in defining these areas.
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In this week's episode, we welcome Derek DeBellis, lead researcher on Google's DORA team, for a deep dive into the science and methodology behind DORA's research. We explore Derek's background, his role at Google, and how DORA intersects with other research disciplines. Derek takes us through DORA's research process step by step, from defining outcomes and factors to survey design, analysis, and structural equation modeling.
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Discussion points:
- (3:00) Derek’s transition from Microsoft to the DORA team at Google
- (4:28) Derek talks about his connection to surveys
- (6:16) Derek’s journey to becoming a quantitative user experience researcher
- (7:48) Derek simplifies DORA
- (8:19) DORA - Philosophy vs practice
- (11:09) Understanding desired outcomes
- (12:45) Self reported outcomes vs objective outcomes
- (16:16) Derek and Abi discuss the nuances of literature review
- (19:57) Derek details survey development
- (27:55) Pretesting issues
- (29:30) Designing surveys for other companies
- (35:02) Derek simplifies model analysis and validation techniques
- (38:48) Benchmarks: Balancing data limitations with method sensitivity