[R-sig-teaching] Convincing other colleagues to use R in the classroom
Randall Pruim
rpruim at calvin.edu
Fri Jan 18 18:01:59 CET 2013
Robert's message provides a nice segue to my previously advertised post regarding the mosaic package.
Here are three things that I think are important in getting R to have wider usage:
1) Having a perceived advantage because R can do something other systems in use cannot
2) Making R look as simple/clear as possible when it is first introduced.
3) PATIENCE
I've spent several hours with a colleague in engineering this week. He was already using R, but his R skills were weak, he lacked a strong understanding of the methods he wanted to use, and he had never seen RStudio and the extras it provides. I think his impression of R and his future use of R will be much better for our recent interaction. This is the "low hanging fruit" -- improving the experience for those already attracted to R. It has side effects of making R more attractive to others as well. It is really easy to write really bad R code that will do more harm than good at winning the hearts and minds of those not yet using R. So any time invested in improving how others use R is time well spent if your goal is to grow the R user base. [One immediate outcome of this is that he has abandoned the Word document he was preparing for an article submission and moved over to using knitr -- he's thrilled. His previous method was to use cat() and trap lots of ASCII output in a file which was then copied and pasted into Word, and I don't know if he had been using any plots. For those who don't know LaTeX and don't want to learn it, the RMarkdown tools in RStudio are a first step in this direction and really easy to use.]
Regarding (2), I think the guiding principle at the start needs to be "Less Volume, More Creativity" (from a poster hung in the war room of the Green Bay Packers by head coach Mike McCarthy). While there are many ways to skin cats in R, newbies need to have someone teach them a systematic cat-skinning approach that generalizes to dog-skinning, mouse-skinning, etc, etc. The mosaic package provides some utilities to make this possible in one particular way. One of our goals was to simplify the high level view of R commands so that most things can be done with one paradigm:
functionname( y ~ x | z, data = ..., other options )
If you are familiar with lattice graphics, you can guess that we use only lattice graphics. We have written additional functions so that things like mean( age ~ sex, data=HELPrct ) gives the mean ages for each sex. And, of course, linear models work in this same way. Tables can be created using our tally() function and similar formulas. Depending on your intended topics, you can probably teach an entire intro course without mentioning the $ operator if you want to. Further more if you can get students to think of y ~ x | z as y depends on x (perhaps differently for each z), that is a useful thinking habit that works for graphics, numerical summaries, and linear models.
The package contains a vignette with one minimal set of R commands sufficient for an intro course and a sampler of their usage.
For more information, you might check out the slides available at
http://www.calvin.edu/~rpruim/talks/
several of which were used for presentations either at the Joint Mathematics Meetings last week or at a workshop I did at George Washington University in November.
---rjp
On Jan 18, 2013, at 11:27 AM, Grant, Robert wrote:
> Dear all
>
> This is a really interesting issue and one taxing a lot of faculty right now. I am this year introducing a little R into computer stats workshops alongside mostly SPSS. I saw Andy Field (author of Discovering Statistics Using R) give a talk on this last year, and he identified the problem of being the only person in the institution who can advise students on R: you're going to get swamped with requests for help. Also, your colleagues have carved out little territories for themselves and changing away from their beloved SPSS is scary. I think it will happen, top-down, because of the money saving and demand from students, but it needs a small group of faculty to work together in the institution to make it possible (the R Team?). Once that is in place, some of the SPSS fans will join you because they don't want to be left behind, but until we each have an R team, the SPSS fans remain a safe majority; why should they change?
>
> One more thing- we need to constantly challenge the dominant narrative that SPSS (or SAS or Stata) is easy to learn. It isn't, it just has comforting menus and icons.
>
> Best wishes
> Robert
>
> Sent from Samsung Mobile
>
> Robert Grant, Senior Research Fellow
> St George's University of London & Kingston University
> --
> tinyurl.com/helpwithstats
> robertgrantstats.wordpress.com
> www.animatedgraphs.co.uk
> --
>
>
>
> -------- Original message --------
> From: Paula Grafton Young <paula.young at salem.edu>
> Date:
> To: bob at statland.org
> Cc: R-sig-teaching <r-sig-teaching at r-project.org>
> Subject: [R-sig-teaching] Convincing other colleagues to use R in the classroom
>
>
> Re: the post from bob at statland.org: As one of those people who uses R in
> introductory statistics courses, I hope that this list does not go away. I
> agree that most of the posts I see are off-topic but the ones that are
> on-topic have been helpful to me in the classroom. Perhaps a name change
> would be in order to avoid the confusion relayed by the previous post
> on reading
> large data sets--maybe R-sig-ClassroomTeaching or something like that to
> make it clearer.
>
> I do actually have a question that I hope is relevant. I chose to adopt R
> for all the reasons most people adopt it--open source, accurate,
> extensible, platform independent. I thought that I would be able to convince
> my colleagues in other departments to at least consider using R (with
> something like RKWard or another GUI). I have failed miserably in
> doing so. I've
> offered workshops, invited colleagues to attend the R labs for my classes,
> and have had minimal response (one political scientist, one ecologist).
> Even having students from my classes do demonstrations of phenomenal graphical
> representations of data sets didn't convince colleagues to even download R
> (except for again, the political scientist; the ecologist already had it).
>
> I teach at a very small college with a very small IT budget and no
> departmental budgets for software. The sociologists, economists and
> business administration faculty won't let go of SPSS n the classroom;
> the biology
> faculty use Excel and SPSS, with the exception of the ecologist mentioned
> previously; the psychology faculty will only use calculators and tables.
>
> So, what I would like to hear from some of you at other institutions is what
> can I do to convince/encourage my colleagues in other departments to adopt
> R and save our institution a significant amount of money in licensing?
>
> Thank you in advance for your insights and advice.
>
> ---
> Dr. Paula Grafton Young
> Associate Professor of Mathematics
> Chair, Curriculum Committee, 2011 - 2013
> Chair, Strategic Planning Steering Committee, 2012 - 2013
> paula.young at salem.edu
> 336.721.2747 (O)
> 336.721.2653 (F)
>
> <http://www.facebook.com/SalemCollege><http://www.twitter.com/SalemCollege>
>
>
>
> On Fri, Jan 18, 2013 at 10:12 AM, Bob <bob at statland.org> wrote:
>
>>
>> I am one of the people who lobbied for the creation of this list long
>> ago. I am not sure R is a great choice for a first course in
>> statistics, but I thought that if someone chose to use it, then they
>> and their students might need all the help they could get to make it
>> easier for the class. But right from the beginning, the bulk of the
>> posts to the list were like this latest one quoted below -- questions
>> about how to do something with R that has no obvious connection to
>> pedagogy or to using R in a first course. This means that those of us
>> interested in the actual topic of this list get lots of off-topic
>> messages, while those who post the messages reach only a small
>> audience that may not be interested in their question. Some off topic
>> posts are answered, some ingnored, and some posters get redirected
>> (even scolded) toward a more appropriate list. I see only losers in
>> this process.
>>
>> So my question is whether this list really serves any useful purpose,
>> or does it just siphon off queries that should have gone elsewhere?
>> Those who post those queries would be likely to get an answer, and get
>> it sooner, if they posted to an appropriate list in the first place.
>> My own answer is that this list is not useful at the present time.
>> Possibly in the future more people will be interested in R for an
>> introductory course and then they might be glad if this list were
>> still alive, but so far...
>>
>> So I am wondering what others on the list think.
>>
>> Here's the official description of this list.
>>
>> Special Interest Group (SIG) on teaching statistics with R. The
>> primary purpose of the group is to provide a forum where instructors
>> using R in their statistics courses can share ideas, teaching
>> materials, and experiences. One particular focus of the SIG is to
>> provide helpful support to instructors new to R who are teaching
>> introductory statistics courses populated with students with little
>> experience in statistics, statistical software, and command line
>> interfaces.
>>
>> Here is where most posts to this list really should have gone.
>>
>> R-help
>>
>> The ?main? R mailing list, for discussion about problems and
>> solutions using R, announcements (not covered by ?R-announce? or
>> ?R-packages?, see above), about the availability of new
>> functionality for R and documentation of R, comparison and
>> compatibility with S-plus, and for the posting of nice examples
>> and benchmarks.
>>
>> Forwarded message:
>>>
>>> Hi Everyone,
>>>
>>> I am a little new to R and the first problem I am facing is the dilemma
>>> whether R is suitable for files of size 2 GB's and slightly more then 2
>>> Million rows. When I try importing the data using read.table, it seems to
>>> take forever and I have to cancel the command. Are there any special
>>> techniques or methods which i can use or some tricks of the game that I
>>> should keep in mind in order to be able to do data analysis on such large
>>> files using R?
>>
>>
>> -------> First-time AP Stats. teacher? Help is on the way! See
>> http://courses.ncssm.edu/math/Stat_Inst/Stats2007/Bob%20Hayden/Relief.html
>> _
>> | | Robert W. Hayden
>> | | 142 Main Street
>> / | Apartment 104
>> | | Jaffrey, New Hampshire 03452 USA
>> | | email: bob@ the site below
>> / | website: http://statland.org
>> | x / phone: (603) 532-7224 (home)
>> ''''''
>>
>> _______________________________________________
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>> https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
>>
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