ACRL statistical literacy
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This roundtable aims to transform perspectives on teaching statistical literacy in library instruction. Participants will discuss concepts like mean vs. median and statistical significance through an in-person and virtual dialogue. Special focus will be placed on contextualizing data within scholarly literature. The goal is to inspire new approaches for teaching basic statistical reasoning to students in a library setting. Objectives include providing tools for helping students understand statistics in everyday life, integrating statistical literacy into one-shot sessions, and discussing how to transform understanding of statistics at large scale.
ACRL statistical literacy
- 1. #StatLit #ACRL2017 "This roundtable aims to transform existing notions about statistical literacy in library instruction. We will facilitate an in- person and real-time virtual dialogue via Twitter and Periscope about teaching students concepts such as mean vs. median, and the real implications of "statistical significance." Special emphasis will be placed on how data is contextualized within the journal literature. The goal is to inspire transformational thinking for teaching basic statistical reasoning to students within a library context."
- 6. Q3 - What is the gold standard of research
- 7. Q3 - What is the gold standard of research # Answer % Count 1 Experimental research 100.00% 7 2 Guessing 0.00% 0 3 Making assumptions off of limited data 0.00% 0 Total 100% 7
- 8. Q4 - Why does the size of N matter in research?
- 9. Q4 - Why does the size of N matter in research? # Answer % Count 1 Because small samples are the most accurate 0.00% 0 2 Because the larger the sample the less probability of error 100.00% 7 3 Because it looks better in a bigger font. 0.00% 0 Total 100% 7
- 10. Objective 1: In-person and virtual participants in the roundtable will leave with at least 3 active learning tools or techniques that could help students appreciate the context and complexities of how basic statistics are used in everyday life. (20 minutes) Objective 2: In-person and virtual participants will gain understanding of how to integrate basic statistical literacy into an existing one-shot library class. (15 minutes) Objective 3: In-person and virtual participants will share ideas about transforming existing understanding of basic statistical concepts at scale. (15 minutes)
- 12. How do you define “statistical literacy?”
- 13. What tools and techniques have you employed in the classroom to help student appreciate the context and complexities of how basic statistics are used in everyday life?
- 14. What are efficient tactics to integrate basic statistical literacy into a 50 minute one-shot instruction session?
- 15. Research suggests that statistical literacy is a problem across the country How can we integrate stat lit into our existing information literacy framework and scale up across an entire institution? Nationally?
Editor's Notes
- #3: https://www.sciencedaily.com/releases/2012/06/120619225941.htm Resveratrol, an antioxidant found in red wine, has beneficial effects on cardiac and skeletal muscle function, similar to the effects of endurance exercise training.• Combining resveratrol supplementation with exercise training augments the beneficial effects of exercise alone.• We show that endurance capacity is enhanced in rats whose diet includes resveratrol during a 12 week endurance-training programme.• Increased endurance was associated with increases in skeletal muscle force, cardiac function, and oxidative metabolism.• Our results establish that resveratrol is an effective ergogenic aid that enhances exercise performance over exercise alone. But now this is immediately generalized without looking at sampel
- #4: Money ball uses data and statistical inference to analyze inefficiency in the game. Substituted the eye test for OBP.
- #5: The NBA has gamed the math and realized that it is 3’s and layups. They also realize that statistics can help forecasting, and find effective underused players.
- #7: Just a start of what we are doing, ignore data size, not generalizing
- #10: Small sample size but we are starting to see our students are retaining this.
- #13: How do you define it in librarianship.
- #14: Reference baseball, money ball, and politics. Lots of students are in medical studies, e.g., reflect on limitations in replication of studies.
- #15: Compare two articles One s low quality, low N Vs high quality statistical inference Think pair share.
- #16: Potential ideas: Statistical literacy conference. Potentially a journal. A core section of the framework.