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SurveyMonkey (2015)

Workshop presentation from the 2015 NYSAAA Annual Conference, Saratoga, NY

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SurveyMonkey (2015)

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  1. SurveyMonkeyThe End of Reply All Jim Wright, Ed.D., CMAA South Huntington UFSD

  2. Why do a Survey? • To see if you are first • Does anyone have a goose-chasing dog? • To get information • Contracts • Trainers • To back-up a current policy • Athlete suspensions • Hazing • Concussion Management • To initiate change • AHA program effectiveness • League placement

  3. Why…..con’t • To compare similar size schools • Size does matter • To ascertain trends • Has there been an increase in social media issues at your school? • Has there been an increase in ACL tears? • To refute a premise • Rumors have no place in decision-making • To produce a presentation • Using the data collected

  4. What we do now • Someone has a question, usually a superior • A bulk email goes out • Replies come in…..usually to everyone • The recipient now has 50 responses that need to be collated • Hopefully, everyone has all the replies • Maybe someone only hit Reply • We send a “Stop with the Reply All” email…. • After hitting Reply All

  5. Being First • What drove the need to be first? • Ego • Competitiveness • Even negative publicity is considered good • Something is not working properly or someone is attempting innovation • Concussion management seems to be the no-brainer but who was first? • Most times being first is done without research • Knee-jerks and Board agendas • Remember that the level of effectiveness of being first is relative to the data collected • You have an assumption but don’t guess • Moneyball • “The first one through the wall always gets bloodied”

  6. Collecting Information (Data) • Who, What, When, Where, Why, How • What is the problem? • Demographics • School • Zone, Conference, etc. • Developing questions • How many? • What type? • Multiple choice • Multiple multiple choice • Likert scales

  7. Collecting Data (con’t) • Determining ranges • Salary • Enrollments • Days • Be careful of broad ranges (BMI #’s) • Defining variables • What’s the keyword? • What subgroups are a part of the issue? • Keeping it simple and user-friendly • Easy to read

  8. How to Read the Data • Filtering results • What question leads you to the answers you need? • Data that doesn’t fit the premise • SAT scores in North Dakota • Example of Data report

  9. Taking a Survey • www.surveymonkey.com • https://www.surveymonkey.com/s/AAASurvey2015 • https://www.surveymonkey.com/results/SM-T5Y7MPN7/

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