Monthly Archives: March, 2015

PLE (Personal Learning Environment)

I am responding to this post by my colleague, Francesca Giannetti, from the RUteaching blog that I just became aware of.  The discussion there is about the PLE, or personal learning environment.  I think it’s interesting to reflect on, because most of the time I am just marinating in my PLE rather than conscious of it.

I find that I use different communication mechanisms for different purposes, and they have different time scales and impacts on my thinking.  Enough generalities, let’s jump in!

  • Listservs and mailing lists – mostly keeping up on “official” business, whether from work or my membership organizations (IASSIST, American Statistical Association).  I experience this as a continuous flow of incremental information.
  • RSS – I am committed to this antique technology because I find it is there just when I want it.  A feed reader is a like a faithful servant that doesn’t bother you when you are busy with other things, but keeps everything ready for you when you return.  I monitor my journal TOCs, academic blogs, job postings, and some general news via RSS.  Since Google Reader went belly up, I have been using Liferea for Linux with satisfaction.
  • Blogs  – Interesting to skim, but there are only a few of regular value for me, such as R-bloggers to keep me up to date on new R developments.
  • Email – this is problematic because I am like many who struggle with e-mail.  My e-mail queue becomes my de facto to-do list too often, and I often fail to prioritize the right things.  Too many different kinds of activities end up in e-mail.  I definitely do not like to read long e-mails.
  • PDFs – for long-term thoughtful academic reading, I prefer to accumulate folders full of interesting PDF articles and books, and then devour them on quiet days.
  • Books – My print books tend to be heavy tomes on math, statistics, or literature.  After seeing these in piles for a couple of years making me feel guilty, I feel the necessary pressure to plow through them.  Books express some of my grander (and more unrealistic?) ambitions.
  • Websites and bookmarks – I track these, try to organize my bookmarks, keep them in Libguides, and more, but I find that I don’t return to websites nearly as often as I think I will.  This is primarily because my list of substantive readings in the other formats above are plenty enough to fill all of my time.  So, unless a website is in my face, or a really good aggregator, like R-bloggers, it tends not to get my attention.
  • Videos – I have appreciated some video tutorials (in addition to producing a few of my own), especially in structured courses on Coursera and other sites.  But Youtube is an oceanic resource, but no matter what I go to it for, I always end up in K-pop, so it is dangerous from a productivity perspective [has anyone developed a “serious-only” filter for YouTube?].  I dislike sitting through an hour-long video talk with no associated text or slides to guide some skimming ahead.  If necessary, I will download the video and play it at double speed in VLC.
  • Conference Talks and Presentations – These tend to be more useful for me as a continual update to the current landscape in librarianship, helping to set directions for more focused reading and exploration. Again, I prefer skimmable formats to be made available, even for things I might be attending in person.

Benford’s Law

I somehow skipped through life up to now without encountering Benford’s Law.  Now that I have, I am flabbergasted that it is not more widely known, or maybe I’ve just been hanging with wrong crowd.  Here’s a hint.  If I have a set of measurements, like the population of countries, or a list of atomic weights, how often would you expect the first digit of the measurement to be 1?  Well, it can’t start with a zero, but any of the other 9 digits is possible, right?  If you think the answer is 1/9, think again. The wikipedia post, MathWorld, and this DataGenetics blog posting are good starting points to understand why.  It turns out this is useful in many areas of data analysis.