Albyn Jones wrote:
I should have noted this at the beginning of the thread rather than
now, but forthe record, there is an R special-interest-group mailing
list called R-sig-teaching where this might also be of interest.
albyn
On Fri, Mar 06, 2009 at 11:28:41AM -0600, Andrew Zieffler wrote:
Hello Everyone,
I hope this email finds you all well. I have been asked to write a paper
that discusses some suggested practices based on learning theory and
cognition research for using R in teaching statistics. In thinking about
framing this paper I have been considering all of the instructional
choices that have to be made. For example, should one use the base
graphics, lattice, ggplots, etc? Should there be instructional sessions
just devoted to R or should it be completely integrated and students
introduced to functions and the like as they need it? What additional
supplemental materials should be made available to students to help them
learn R? And there are many more of these types of questions and
decisions that need to be made.
As I have looked at many of the texts that have incorporated R they all
seem to have a similar approach of introducing simple operators such as
addition, subtraction, etc Then moving to assignment; the idea of
vectors; functions etc. It is unclear to me if there is a reason for
this pattern or if it is based on tradition? Maybe this lends itself to
developing better skills for students who will go on and do more
programming in R, but --- at least in our courses --- there are also a
host of students who will only ever use R as a data analysis tool.
All of this is a very long-winded way of asking for your help. I would
love to hear your thoughts on the following:
1) What are the instructional decisions that a person needs to make if
they are going to be teaching statistics using R?
2) What decisions have you yourself made and what were your reasons?
3) How do you teach with R? Do you have sessions on R and other sessions
where content is taught? Is the computing fully integrated with the
content? Or some combination?
4) If you have the heterogeneous group of students (some going on to
program in R, others just trying to get through, etc.) how do we deal
with this? Do we need to have different types of assignments and
materials for the different students?
Thank you in advance.
Andy
--
Andrew Zieffler, Ph.D.
Educational Psychology
University of Minnesota
167 Educational Sciences Building
56 East River Road
Minneapolis, MN 55455
Email: [email protected]
http://www.tc.umn.edu/~zief0002
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Dear Andrew,
as it seams to me that you will be interested in teaching data analysis
and/or Resgression analysis let me point you at
Julian Faraway's excellent and free book 'Practical Regression and
ANOVA using R' .
Faraway uses defined examples for using the various data analysis tools
within R and comments on their use, rather than
talking too much about variables, functions...
That might be a good start for you. There's also a package 'faraway'
that includes the examples... very great work!
You can find all that directly in the CRAN or just google 'faraway book'
Cheers Markus
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