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Learning Trends 2022: An Interview with Peter Arashiro - Learning Well Ep. 4

Thursday Jan 06, 2022

Learning Trends 2022: An Interview with Peter Arashiro - Learning Well Ep. 4
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Join us as we talk with Peter Arashiro, from the Center for Academic Innovation at the University of Michigan. Peter is a long-time friend and we’ve worked on a variety of projects together over the years. We’re excited to explore 2 important Learning Trends we should be focusing on in 2022.

 

Segment Topics:

Designing with DEIJ lenses

  • Persona development
    • Chelsea Chandler - Associate Director of the Center for Faculty Excellence - Bowling Green State University
      • Diversity, Equity, and Inclusion in MOOCs: Mapping Goals from Proposal to Design - lead author
        • Rebecca Quintana
        • Yuanru Tan
        • Nicole Yang
      • DEIJ Lenses
    • Alternative text
      • Cynthia Bennett - post-doctoral researcher at Carnegie Mellon University’s Human-Computer Interaction Institute
        • The Radical AI Podcast Interview
        • “It’s Complicated”: Negotiating Accessibility and (Mis)Representation in Image Description in Image Descriptions of Race, Gender, and Disability - lead author
          • Identity

 

AI/ML/NLP for designing learning experiences

  • Data and algorithms
    • Learning analytics
    • NLP and Content
  • Content knowledge acquisition at scale; becoming more efficient at producing prototypes and content
    • Brute force “learning”; or
    • Use NLP techniques to assist designers with
      • Summarizing large sets of text (think transcripts)
      • Identifying key concepts in text
      • Generating MCQ or other forms of assessment
    • Content generation and AI/ML in ID/LXD
      • Donald Clark - EdTech Entrepreneur, researcher, professor
        • Artificial intelligence for Learning: How to use AI to support employee development
        • CEO of WildFire Learning
      • Learning about NLP to gain insights about your learning experience/ID practice –
        • Position paper - Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data - lead author with Alexander Koller
        • TWIML (formerly this week in machine learning) podcast interview

 

 

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