1 / 11

Purpose of the work

Improving Inferential Statistics Teaching Methods to Accommodate Millennial Learning Styles Dr. Buddy Bilbrey. Purpose of the work. Create a method that reaches the students in a way that enforces learning

makoto
Télécharger la présentation

Purpose of the work

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ImprovingInferentialStatisticsTeachingMethods to AccommodateMillennialLearningStyles Dr. Buddy Bilbrey

  2. Purpose of the work • Create a method that reaches the students in a way that enforces learning • Quantifychanges to drive process improvement in teaching inferential statistics

  3. Motivations from last year • Session last year two striking methods for instruction were proposed 1) skip early inferential statistics 2) write/use software to provide tools for students • Both methods were driven by the lack of time to cover the undergraduate topics inferential statistics • AACSB constraint – cover topics in detail reasonable to industry expectations

  4. Difficulties from THIS year • Variables hard to control over multiple semesters • Technology • Communication with Math Department • Lack of Excel Skills • OFAT for this experiment

  5. Traditional Method • Assign homework relative to the lectures • Homework will be done on students’ time • Lecture with examples and notes • Homework is designed to test knowledge, not teach the material • All work graded after submission

  6. What was happening? • Students were bored/uninterested in class • Life is MUCH more interactive for them today • Communications are instant • Immediate access is the “norm” • Examples: Facebook, texting, Snapchat, etc. • Preconceived notion that “Statistics is hard”

  7. New Approach • Students are asked questions for the problems during class – answers are unknown and problems are algorithmically generated • Forces students to follow and keep up with the class • Use end lecture time for hands-on problems (Short extra credit problems to encourage effort) • Can’t lean on neighbors for answers

  8. Preliminary Resultsvariance reduced

  9. Preliminary ResultsTotal Points – Normalized by Max Pts

  10. Current Problems – Future Work • Noticed that the students won’t draw the normal curve • Homework is broken down into very small problem sets vs. the traditional (Spring 2018) • Trying to guess the solutions instead of working the problems • Which data to remove? Dropped students? • Online lectures?

  11. Questions?

More Related