Follow-up questions (last minute, sorry!)
(1) One of the interviews contains the idea that it’s important to show your original hypotheses and predictions in the preregistration. My impression is that the hypotheses and predictions, the experiment, and the results all depend on each other, and their contents and connections all need to be clear for each one to be clear, so it’s important to have them clear enough before implementing an experiment. And so it seems to me that it’s for one’s own benefit, really, to have it as clear as possible before actual experimentation, and later tweaks are more of an issue for the quality of the research itself than for accountability for what was promised when. But maybe I’m missing something – what would be a practical example of changing hypotheses and predictions in a clear, meaningful and legitimate way after implementing an experiment?
2) The Nature article on student-advisor relationship brings an example of a student who felt like leaving from a shooting scene after having their writing handed back with lots of corrections. It’s proposed that, therefore, it’s better to be specific in requesting feedback (and just requesting feedback is like walking into a restaurant and asking for “food”). However, I’ve had so many experiences of just requesting general feedback, getting loads of corrections, and even if it all felt a bit intense or uncomfortable at times, I embraced that feeling and learned immensely from both the feedback and the feeling! So if my goal is learning as much as possible from the expertise of the advisor, isn’t it limiting to narrow down their feedback?
(1) One of the interviews contains the idea that it’s important to show your original hypotheses and predictions in the preregistration. My impression is that the hypotheses and predictions, the experiment, and the results all depend on each other, and their contents and connections all need to be clear for each one to be clear, so it’s important to have them clear enough before implementing an experiment. And so it seems to me that it’s for one’s own benefit, really, to have it as clear as possible before actual experimentation, and later tweaks are more of an issue for the quality of the research itself than for accountability for what was promised when. But maybe I’m missing something – what would be a practical example of changing hypotheses and predictions in a clear, meaningful and legitimate way after implementing an experiment?
2) The Nature article on student-advisor relationship brings an example of a student who felt like leaving from a shooting scene after having their writing handed back with lots of corrections. It’s proposed that, therefore, it’s better to be specific in requesting feedback (and just requesting feedback is like walking into a restaurant and asking for “food”). However, I’ve had so many experiences of just requesting general feedback, getting loads of corrections, and even if it all felt a bit intense or uncomfortable at times, I embraced that feeling and learned immensely from both the feedback and the feeling! So if my goal is learning as much as possible from the expertise of the advisor, isn’t it limiting to narrow down their feedback?