Notes from Bransford’s Talk
John Bransford's Learning Sciences Guest Lecture
Book/research recommendations:
The Mind at Work by Mike Rose
Anders Ericsson (expert performance, experts resist automaticity)
Quality of Life issues -
health care, nutrition, finances, local environmental conditions (research within the LIFE Center)
Themes -
- adaptive expertise - recognizing adaptability (when do my schemas apply?)
- innovation
- efficiency
- schemas (i.e. SAT problem types)
- constructive nature of knowing - we build knowledge out of what we already know
- people knowledge - figure out what we need people to share to identify with and learn from
"Innovation is the sudden cessation of stupidity." (Bransford quoted someone else)
Learning from Others
people learn better from people they know
Thoughts
Research in the LIFE center seems really interesting; I should go explore that area some more to see if there are "informal learning environment" ties or analogies to what I'm working on.
Mark Newman’s talk
Kick off of Interdisciplinary Network Seminar
positions - may mean something, may mean nothing
questions: can spatial layout ever mean "nothing"? is it enough to say "be careful"? do we already know ho people would process spatial layouts, or does that need to be studied?
acyclic - no closed loops; ex. citation networks - a paper has to have been written before you can cite it, so you can't go backwards in time, no loops
look at the data, notice something about it, turn it into a mathematical statement to manipulate it
Amazon network - http://www.orgnet.com/divided.html
social network = network of people
thought: not sure that's enough to make something "social"
Mark Lombardi - art + political commentary + social networks
pierogi
story on NPR
CAIDA - cooperative association for internet data analysis - http://www.caida.org/
disease - person with 100 contacts is 100x100 more likely to spread because they're more likely to get it and to pass it on; averged squared degrees key
thoughts: maybe dissonance is about the characterization of connections; not all connections are the same; is there some way to characterize the edges to reflect those dissimilarities and differences in magnitude within the same diagram? when do what kinds of connections matter - something to ask in interviews
graph partitioning (from CS) vs. community structure (from SS and applied math) -
GP - specified number of groups; best answer whether or not it's good question: what?
ComStructure - clustering doesn't predetermine number or size of groups; natural lines; surprisingly few edges = interesting