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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
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ImprovingInferentialStatisticsTeachingMethods to AccommodateMillennialLearningStyles Dr. Buddy Bilbrey
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
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
Difficulties from THIS year • Variables hard to control over multiple semesters • Technology • Communication with Math Department • Lack of Excel Skills • OFAT for this experiment
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
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”
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
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?