Using Technology to Engage Students and Enhance Learning . Roxy Peck Cal Poly, San Luis Obispo firstname.lastname@example.org. Overview. Use of technology in teaching introductory statistics: Technology for Data Analysis Now the norm Use the best available technology - PowerPoint PPT Presentation
Using Technology to Engage Students and Enhance Learning
Using Technology to Engage Students and Enhance Learning Roxy PeckCal Poly, San Luis Obisporpeck@calpoly.eduOverviewUse of technology in teaching introductory statistics:Technology for Data Analysis Now the normUse the best available technologyTechnology for Developing Conceptual UnderstandingWidely used for some things (such as sampling distributions and simulation to estimate probabilities)Lots of missed opportunitiesOther Uses of TechnologyOnline HW and classroom management systemsCommunication (instructor-student, student-student)Classroom assessment (clickers, poll everywhere)Technology for Developing Conceptual Understanding Central Concept: Sampling Variability
AcknowledgeDescribeUnderstandTake into account when drawing conclusionsThe Usual Approach without TechnologyWait until week X when you get to the dreaded sampling distributions
ThenAsk students to imagineShow a static picture of the distribution ofPray that they understand the relevance and importance (they dont).Hope they can get through the rest of the course devoted to inference (some can, but usually by following rote proceduresthe logic escapes them, but oh well)
The Usual Approach with TechnologyWait until week X when you get to the dreaded sampling distributions
ThenShow the students an applet (there are lots of good ones out there). Technology replaces the imagine part of the no technology approach.Pray that they understand the relevance and importance (some do with less left to imagination!).Hope they can get through the rest of the course devoted to inference (some can, but usually by following rote proceduresthe logic escapes them, but oh well)I.M.H.O.Sampling variability and sampling distributions are central to understanding statistics.These are the most abstract concepts we ask students to grapple with.SOWhy do we keep this hidden until we spring it on students in a one-hour lecture and expect them to get it?!?Wouldnt it be better to develop and nurture this idea from the beginning?There is a BIG Payoff BUT much easier to do if
Plan for it in a thoughtful way.
Have access to technology to facilitate this type of consistent development.
The Missed OpportunitiesWeek 1: Sampling MethodsWeek 3: Graphical MethodsWeek 4: Numerical Summary MeasuresWeek 5: RegressionWeek 7: Sampling DistributionsWeek 9: Confidence IntervalsWeek 10: Hypothesis TestingActivities Based on Random SamplerEvery student gets a different random sample form the same population.
Students engage with the data and with other students to build understanding.Random SamplersMany possibilitiesCensus@School data base has a random sampler(http://www.amstat.org/censusatschool/)Random sampling applets(one example: http://www.rossmanchance.com/applets/OneSample.html )Textbook resourcesStatistical software packages with random sampling capabilities (such as JMP and Minitab)ActivitiesExamples that follow are based on sampling from specific populations but can be easily adapted to any population.
The important point is what you ask the students to do and when.
Week 1: SamplingSample from a population of adults. Each student gets a different random sample of 20.
Variables: number of text messages sent in a typical day, response to have you ever sent a text message while driving?
Week 3 Graphical MethodsEach student gets a different random sample of size 50 from a population of adults
Variables: Gender, age
Big PayoffsIllustratesEffect of choice of bins on appearance of histogram.Even with different bins and different random samples, there are similarities and they still resemble the population distribution in key ways.Even with different types of graphical displays and different random samples, tend to draw the same conclusions.All this and we are weeks away from formal treatment of sampling distributions!Follow up Activity
Week 5--RegressionEach student gets a different random sample from a population of adults.
Variable: Number of text messages sent, age
IllustratesSampling variability in the slope of the regression line
Potential impact of sampling variability on predictionsWeek 7Sampling DistributionsStudents are ready for these ideas!
In fact, they have already done what you will now formalize several times and are comfortable with the idea of sampling variability.And it ContinuesConfidence intervals
Back to TechnologyTechnology is a tool that enables students to engage with the ideas of sampling variability
EARLY AND OFTEN!Thanks for Attending this Session.Questions?Comments?