![\"Scott](\"http:\/\/biology.ucsd.edu\/_images\/people\/faculty\/sarifkin.jpg\")
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Scott Rifkin, UCSD<\/strong><\/p>\n I have tried several different approaches to using technology\u00a0to help students get a better intuitive understanding of statistical concepts.\u00a0Although statistical software has been used in introductory statistics classes\u00a0for quite some time, interfaces that facilitate discovery-based learning rather\u00a0than calculation are much newer.\u00a0[pullquote]or I could make an applet specifically\u00a0targeted towards this common question that will let her discover the answer for\u00a0herself[\/pullquote]<\/p>\n My initial attempt was to ask the students write simple\u00a0routines in R based on templates I provided.<\/span>\u00a0 <\/span>I prepared worksheets with explanations of what each\u00a0<\/span>variable in the code meant and with suggestions for how they could vary them\u00a0and plot the results. I thought that simulating null or bootstrap distributions\u00a0themselves would give them strong insight into these concepts. Unfortunately,\u00a0for most of my students, my hopes were derailed by few obstacles. Thinking that\u00a0a menu-driven interface would be more familiar to the students, I had them use\u00a0an R GUI that proved to be unstable in subtle ways \u2013 problems that I did\u00a0<\/span>not experience but that metastasized in the hands of 150 impatient new\u00a0<\/span>users.\u00a0 <\/span>After these problem cropped\u00a0up, I ditched the GUI and relied wholly on the command line. But the damage was\u00a0done \u2013 students didn\u2019t trust the software, didn\u2019t differentiate between\u00a0the GUI and the underlying R program, and many had never used and didn\u2019t\u00a0understand how to use a command-line interface. Instead of helping, the\u00a0software was a barrier to understanding simply because it competed for study\u00a0time and emphasized \u201cgetting things to work\u201d rather than \u201cusing it to\u00a0understand.” It was clear that the students needed something easier \u2013\u00a0something more plug-and-play.<\/p>\n \u00a0<\/span>R was too complicated. Minitab would not (easily) do simulation. I\u00a0shuddered when a colleague suggested Excel.<\/span>\u00a0 <\/span>I shied away from asking them to buy software specifically\u00a0<\/span>for this course. Then I discovered applets.<\/p>\n Applets are an excellent learning tool and, for motivated\u00a0students, a wonderful discovery tool.<\/span>\u00a0\u00a0<\/span>Most applets only have a few buttons or boxes, so it is usually fairly\u00a0obvious how to use them.\u00a0 <\/span>In fact,\u00a0they can be too easy to use. I\u2019ve had students comment that the applets are\u00a0nice and all, but they didn\u2019t really believe me that they could use them for\u00a0statistical tests out in the real world.<\/p>\n I\u2019ve primarily relied on the Rossman<\/span>-Chance\/ISI collection<\/a>\u00a0for hypothesis testing and the StatKey<\/span><\/a> set\u00a0for bootstrap confidence intervals. There are lots of other ones around the web\u00a0that are good for illustrating specific concepts. I\u2019ve been tempted to pick and\u00a0choose from these but have resisted for three reasons:\u00a0 <\/span>(1) each new interface is another thing\u00a0for students to struggle with; (2) many of these applets are written in Java which\u00a0lately has been too difficult to get to reliably run on 150+ computers; and (3)\u00a0sites disappear or go down unexpectedly, confounding lesson planning and\u00a0wreaking havoc with assignments.<\/p>\n Moreover, a new package for R called shiny<\/a> makes it quite easy to make nice-looking and\u00a0easy-to-use applets out of R code. My students were struggling with Type II\u00a0error in particular, and I found an applet that I thought would help them\u00a0understand. Unfortunately, it was written in Java \u2013 I had trouble\u00a0convincing my computer to allow it to run, and I knew that I would have to\u00a0field too many emails from students who couldn\u2019t get it to work.\u00a0 <\/span>I had wanted to learn how to use shiny\u00a0and three hours later, after modifying one of their examples<\/a>, I had my own Type I-Type II-Power applet<\/a>\u00a0that I could customize however I wanted.\u00a0 <\/span>I could tweak it based on feedback I got from my students\u00a0and add new features to address misconceptions. Shortly thereafter I added another one<\/a>, this time because my students were struggling to understand the\u00a0similarities and differences between null, sampling, and bootstrap\u00a0distributions.\u00a0 <\/span>A student recently\u00a0mentioned that she did not understand why the standard error of the mean should\u00a0necessarily be less than the population standard deviation (except for n=1). I\u00a0could explain it to her in words (and have in class); I could tell her (and\u00a0will in a week) a formula and point out the sqrt<\/span>(n)\u00a0in the denominator (but I think that leads to an understanding that<\/span> it\u00a0is less but not why<\/span> it is less), or I could make an applet specifically\u00a0targeted towards this common question that will let her discover the answer for\u00a0herself and that can be used by similarly puzzled students in my current and\u00a0future courses.\u00a0<\/span><\/p>\n \u00a0Targeted, interactive, accessible programs like applets are\u00a0a key tool in transforming statistics learning from memorization to exploration\u00a0and discovery. However, students still need to be encouraged and taught how to\u00a0use them that way. Lately I\u2019ve asked students to write down predictions about\u00a0what will happen if they change the number in a box or move a slider. If they\u00a0write it down, then they are committed to an answer and have to face whether\u00a0they were right or wrong. If they don\u2019t write it down, it\u2019s too easy to look at\u00a0the result and convince themselves that they expected it. Ten minutes playing\u00a0with an applet will give them more intuition for how various parameters affect\u00a0distributions than anything else. Once they have this intuition \u2013 once\u00a0they have internalized the patterns \u2013 it is a much shorter step to understanding\u00a0why the patterns come about.<\/p>\n I’d love to be able to move my course away from its current\u00a0lecture\/lab\/homework format to one where the students spend the bulk of their\u00a0time discovering statistical concepts for themselves \u2013 guided by targeted\u00a0applets and 5-15 minute videos that I would record \u2013 and then applying\u00a0them to real world problems. My role would be as a facilitator: tweaking the Scott Rifkin, UCSD I have tried several different approaches to using technology\u00a0to help students get a better intuitive understanding of statistical concepts.\u00a0Although statistical software has been used in introductory statistics classes\u00a0for quite some time, interfaces that facilitate discovery-based learning rather\u00a0than calculation are much newer.\u00a0[pullquote]or I could make an applet specifically\u00a0targeted towards this common question that […]<\/p>\n","protected":false},"author":18,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":["post-396","post","type-post","status-publish","format-standard","hentry","category-how-do-you-use-technology"],"_links":{"self":[{"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/posts\/396","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=396"}],"version-history":[{"count":6,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/posts\/396\/revisions"}],"predecessor-version":[{"id":474,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=\/wp\/v2\/posts\/396\/revisions\/474"}],"wp:attachment":[{"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=396"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=396"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.causeweb.org\/sbi\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=396"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\napplets and the exercises or making new ones to expose specific misconceptions
\nrevealed through conversations with students.\u00a0\u00a0 <\/span>Many components for such a course are already out\u00a0there \u2013 applets <\/a>and exercises <\/a>and explorations <\/a>and cases<\/a> \u2013 and the
\ntechnology is there to make this transition possible even for a large class.<\/p>\n","protected":false},"excerpt":{"rendered":"