Community Data Science Workshops (Fall 2014)/Reflections: Difference between revisions

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== Afternoon Sessions ==
 
Projects are done in breakout sessions in a series of three rooms. The general problem was that insisted on teacher per topic and topics were very unequal in their popularity. Next time, we will likely prepare to have multiple teacher for multiple rooms on topics we know will be more popular.
'''Mining research interests/goals.'''
Could we help match up people with similar interests?
 
next time maybe mine the registration for a list of research questions
 
 
'''How can we support self-directed projects?'''
 
Can we give participants more guidance to support their project interests?
It’s easier to do that if people are pre-clustered.
 
Bring up people’s ideas at the end.
 
The size of the breakout workshops varied and that means different degrees of engagement were feasible.
 
The BIG feedback from the first series of workshops: Bring people back together more often. Bringing people together in the end was effective this time. We need a go between for each session to remind people to reconvene. An emcee.
 
- post examples of code used in teh lectures
 
showcase what students ahve accomplished and places people can change things and do things differently
 
e.g., the fergeson thing with the exmaple from ha=rry party
 
 
- public healtha nd epi data session
 
We would love to create a session on '''basic statistical analysis in Python''' and at least ten participants would have been enthusiastic to take it.
 
 
show and tell at the end was very effectively
 
we need a designated mc who can go =between rooms
 
ideomatic ptyhon
 
talk to chris to try to fix those things
 
Several changes we hope to make include:
 
* As we refine this process, we were also interested in thinking of trying to select or refine breakout sessions so that they are more closely tailored to individuals and their interests. Next time, we will consider mining the registration for a list of research questions we might use.
* We want to emphasize bringing people back together more often. In particular, we found that bringing people together back together share work several time during each session and then once in the end to show of achievements or interesting results was effective. We also need to designate a person to a person to go between for each session to remind people to reconvene and to create a program of important or inspiring achievements for presenting to the group at the very end.
* There seemed to be broad interest in examples or projects that are focused on public health and/or epidemiological data.
* We would love to create aan afternoon project for sessionSession on3 '''basic statistical analysis in Python''' and at least ten participants would have been enthusiastic to take it.
 
== Session 0: Python Setup ==
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