I participate peripherally on a listserve for middle- and high-school science teachers. Sometimes questions about graphing or data analysis come up. I never miss an opportunity to advocate for R. However, the teachers are often skeptical that their students would be able to issue commands or write a little code; they think it would be too difficult. Perhaps this stems from the Microsoft- and spreadsheet-centered, pointy-clicky culture prevalent in most US public schools. Then again, I have little experience teaching this age group, besides my own kids and my Science Olympiad team, so I respect their concerns and expertise. I don't know yet what software they generally use, but I suspect MS Excel and SPSS. Now I have to put my money where my mouth is. I've offered to visit a high school and introduce R to some fairly advanced students participating in a longitudinal 3-year science research class. I anticipate keeping things very simple: --objects and the fact that there is stuff inside them. str(), head(), tail() --how to get data into R --dataframes, as I imagine they will mostly be using single, "rectangular" datasets --a lot of graphics (I can't imagine that plot(force, acceleration) is beyond a high-schooler's capability.) --simple descriptive statistics --maybe t-tests, chi-square tests, and simple linear regression. Alas, probably more than we would have time to cover. Has anyone done anything with R in high schools? Thanks. --Chris Ryan SUNY Upstate Medical University Binghamton Clinical Campus
In addition to whatever feedback you may get here, you might subscribe to the SIG-Teaching list for another interested population. Michael On Tue, Apr 17, 2012 at 10:46 PM, Christopher W Ryan <cryan at binghamton.edu> wrote:> I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that ?plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. > > Alas, probably more than we would have time to cover. > > Has anyone done anything with R in high schools? > > Thanks. > > --Chris Ryan > SUNY Upstate Medical University > Binghamton Clinical Campus > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
Hi Chris, I am not sure, whether introducing R to High School students would be a good idea as I feel we should encourage students to sketch the graphs in paper to get their concepts right. Excel is fine, but - if I write an equation on the board, will the student be able to visualize its graph? Allowing students to use software to plot graphs at a very early age may hinder that learning. What I would focus on (as the teacher pointed out - that they may not be able to write code) - is being able to write simple codes to get a grasp on programming (they can use QBASIC which is one of the simplest programming softwares). R to my mind should be introduced at an undergraduate level - where they are able to use its real power (vectors, matrices, graphics etc.). Thats my view :) Regards, Indrajit ________________________________ From: Christopher W Ryan <cryan@binghamton.edu> To: R-help <R-help@r-project.org> Sent: Wednesday, April 18, 2012 8:16 AM Subject: [R] introducing R to high school students I participate peripherally on a listserve for middle- and high-school science teachers. Sometimes questions about graphing or data analysis come up. I never miss an opportunity to advocate for R. However, the teachers are often skeptical that their students would be able to issue commands or write a little code; they think it would be too difficult. Perhaps this stems from the Microsoft- and spreadsheet-centered, pointy-clicky culture prevalent in most US public schools. Then again, I have little experience teaching this age group, besides my own kids and my Science Olympiad team, so I respect their concerns and expertise. I don't know yet what software they generally use, but I suspect MS Excel and SPSS. Now I have to put my money where my mouth is. I've offered to visit a high school and introduce R to some fairly advanced students participating in a longitudinal 3-year science research class. I anticipate keeping things very simple: --objects and the fact that there is stuff inside them. str(), head(), tail() --how to get data into R --dataframes, as I imagine they will mostly be using single, "rectangular" datasets --a lot of graphics (I can't imagine that plot(force, acceleration) is beyond a high-schooler's capability.) --simple descriptive statistics --maybe t-tests, chi-square tests, and simple linear regression. Alas, probably more than we would have time to cover. Has anyone done anything with R in high schools? Thanks. --Chris Ryan SUNY Upstate Medical University Binghamton Clinical Campus ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]]
Christopher, I suggest that you look at R through Excel. This is a Springer book that Erich Neuwirth and I wrote. It is designed as a computational supplement to any introductory Statistics book. It uses Erich's RExcel to give either menu access to R from Excel (using Rcmdr embedded into the Excel menu system), or by placing any R function inside the Excel automatic recalculation model. RExcel is available either in the RExcelInstaller package from CRAN, or fully integrated into a complete R system from rcom.univie.ac.at. Go to the Downloads page and download the current RAndFriends installer. We have discussions on using RExcel in the classroom in the Literature and presentations section on the Wiki page at the rcom site. Several of the links are to papers at the UseR! conferences. This one specifically addresses teaching: http://www.r-project.org/useR-2006/Slides/BaierEtAl.pdf Baier, T., Heiberger, R., Neuwirth, E., Schinagl, K., Grossmann, W. (2007). Using R for teaching statistics to nonmajors: Comparing experiences of two different approaches. Paper presented at the UseR 2006, Vienna. Rich On Apr 17, 2012, at 22:46, Christopher W Ryan <cryan at binghamton.edu> wrote:> I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. > > Alas, probably more than we would have time to cover. > > Has anyone done anything with R in high schools? > > Thanks. > > --Chris Ryan > SUNY Upstate Medical University > Binghamton Clinical Campus > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
On Tue, Apr 17, 2012 at 10:46 PM, Christopher W Ryan <cryan at binghamton.edu> wrote:> I participate peripherally on a listserve for middle- and high-school > science teachers. Sometimes questions about graphing or data analysis > come up. I never miss an opportunity to advocate for R. However, the > teachers are often skeptical that their students would be able to > issue commands or write a little code; they think it would be too > difficult. Perhaps this stems from the Microsoft- and > spreadsheet-centered, pointy-clicky culture prevalent in most US > public schools. Then again, I have little experience teaching this age > group, besides my own kids and my Science Olympiad team, so I respect > their concerns and expertise. > > I don't know yet what software they generally use, but I suspect MS > Excel and SPSS. > > Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that ?plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression. >I have some experience in this and would have to agree with Indrajit that this is not a good idea. When I tried to teach R to a high school student it was not very successful. Certainly based on that experience the list above is way too complex. Don't teach anything on that list at all. The number of concepts involved in that is simply overwhelming. Also avoid teaching anything that requires complex installation if you want them to be able to carry it forward by themselves. I would expect the reaction would be that most will have no interest and the ones that do will be frustrated by the large number of concepts needed to get going. The only part that seemed to trigger any interest was when I showed the large list of colors available in colors() and then playing with inserting different colors in: colors() plot(1:5, col = "violetred") Assuming you are committed to this and go ahead, I would divide it into two parts: 1. a graphics demo -- make it clear its a demonstration so they have an appreciation of what is possible and you are not actually teaching anything in this portion. 2. Teach them how to install R, run the above two commands (substituting in different colors), how to exit and point out that there are many tutorials in: http://cran.r-project.org/other-docs.html and they can pick one they like (since the official documents will be over their head). If you do that then perhaps a small number will have sufficient interest to try it some more at home but I wouldn't be surprised if none do and that most or all would prefer something with more immediate gratification. -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com
> Now I have to put my money where my mouth is. I've offered to visit a > high school and introduce R to some fairly advanced students > participating in a longitudinal 3-year science research class. > > I anticipate keeping things very simple: > --objects and the fact that there is stuff inside them. str(), head(), tail() > --how to get data into R > --dataframes, as I imagine they will mostly be using single, > "rectangular" datasets > --a lot of graphics (I can't imagine that ?plot(force, acceleration) > is beyond a high-schooler's capability.) > --simple descriptive statistics > --maybe t-tests, chi-square tests, and simple linear regression.I think those are good topics to cover, but the order is wrong - start with graphics. They are immediately useful and you can start with built in datasets (although I'd recommend finding a package with more interesting/bigger datasets than the base packages). Once you've shown them how to use graphics to understand data you can talk more about how it works - what is a dataframe, how you load data in R, etc. That's the path I follow when I teach R (http://stat405.had.co.nz/, http://vita.had.co.nz/papers/assessment.html), and I find it to be successful at keeping students motivated enough to work through the initial frustrations of learning a new language. R is not too difficult for high-school students to learn, but you need to make sure you provide them with tools to do things that they're interested in - finding interesting problems that they _want_ to solve is most of the battle. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/
Bert, What you are saying - is a problem with people who are using Excel. It is not Excel's problem that people are sending data in an unstructured way. I agree - Excel may not be the right tool when you are doing some complicated data analysis (like for e.g. statistical modeling) - but that is not what Excel was built for. The power of Excel lies in being able to use it to explore data, represent and present your analysis. When exploring data, yes it may not be very useful beyond univariates and bivariates - but that is your starting point in EDA where you need to generate hypotheses about your data. I have been in the field of analytics for almost 7 years now, though we have embraced technologies like SAS, R, SPSS, Spotfire, etc., the power and importance of Excel in our lives has never been lost to us. Its a question of whether are you capable enough to use it. Regards, Indrajit ________________________________ From: Bert Gunter <gunter.berton@gene.com> Cc: Rolf Turner <rolf.turner@xtra.co.nz> Sent: Sunday, April 22, 2012 11:07 AM Subject: Re: [R] introducing R to high school students I would like to slightly clarify and echo Rolf's comment: Excel is a terrible tool for data analysis. Maybe it's a good tool for keeping track of your car's repair history... but not for data analysis. I could go on at great length why, but let me just focus on one aspect that drives me and other statisticians in my group crazy when we deal with scientists who send us data in Excel: the data are frequently a mess! By this I mean that they are often stored in crazy ways, with plots and summaries sprinkled around, capital letters and small letters mixed, missing values coded arbitrarily e.g.(99999 ), and so forth. As someone I know once commented, it's a puzzle to get the data extracted in a form susceptible to analysis. Why is this? -- because Excel enforces no structure. It's **cell-based** (duhhhh), so users can throw in the data anyway they see fit, which frequently is pretty unfit. This is not just a minor issue, imho. Not having data in a reasonable structure limits what one can do for data analysis and graphics. This promulgates the inadequate and frequently awful paradigms that one sees throughout science (e.g. bar charts with 1 se bars sticking up out of them). The widespread use of Excel for "serious' scientific and engineering data analysis is a near tragedy. All IMHO, of course. Cheers, Bert On Sat, Apr 21, 2012 at 9:45 PM, Indrajit Sengupta> Why do you think Excel is a terrible tool? In what ways have you tried to use Excel and it has failed you? > > Regards, > Indrajit > > > ________________________________ > From: Rolf Turner <rolf.turner@xtra.co.nz> > > Cc: R-help <R-help@r-project.org> > Sent: Sunday, April 22, 2012 9:25 AM > Subject: Re: [R] introducing R to high school students > > On 22/04/12 15:29, Indrajit Sengupta wrote: > > <SNIP> >> 1. At school we seldom deal with lot of data - the focus is more on concepts. Excel is an excellent tool > That is at best debatable, and IMHO just plain incorrect. I firmly believe > that Excel is a ***TERRIBLE*** tool. >> and no matter how much we love or hate it - we will be using Excel a lot in our lives. > > This is not (unfortunately IMHO) debatable. It is all too sadly true. For most > people at least. (Not for my very good self. I can get away with eschewing > Excel. Most people are not lucky enough to have that option.) > > <SNIP> > > I think much of the remainder of the post was highly disputable as well, > but I will desist at this point. > > cheers, > > Rolf Turner > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm [[alternative HTML version deleted]]
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