Engaging Discussions on Incorporating Large Data into Teaching

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Explore various perspectives on incorporating large data into teaching, including the minimum size needed for students to learn data management skills and the importance of relevance and specific skills. Delve into barriers and solutions, and discover engaging approaches like the EDDIE app. Join the conversation on leveraging data in education for student success.

  • Data Skills
  • Education
  • Teaching
  • Student Success
  • Incorporating Data

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  1. Icebreaker Who s in the Room? September 25, 2022

  2. In what time zone did you start the day yesterday? In what time zone did you start the day yesterday? Front of room Discuss in pairs or trios: Eastern Pacific What brings you to the workshop? Other Central Mountain

  3. In your opinion, what is the minimum size large data needs In your opinion, what is the minimum size large data needs to be for students to learn data management skills? to be for students to learn data management skills? Front of room Discuss in pairs or trios: largest smallest How do data skills help students succeed? (in college, careers, etc)

  4. In your perspective, what is the most important reason to In your perspective, what is the most important reason to incorporate large data into teaching? incorporate large data into teaching? Front of room Discuss in pairs or trios: Relevance (societal topics, future careers, etc) Specific skills (graphing, calculations, etc) What about the EDDIE approach is exciting/ engaging for students? Other Self-efficacy/ confidence (e.g. conquering math phobia) Small group learning (collaboration/pedagogy)

  5. What do you consider the biggest barrier to incorporating What do you consider the biggest barrier to incorporating large data into teaching? large data into teaching? Front of room Discuss in pairs or trios: Technical constraints (software, data access, etc.) Lack instructor experience (pedagogy, data skills, etc) What solutions to this barrier would you suggest to a colleague? Other Data wrangling ( messy data) Large class size

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