ELI Webinar | How AI and Machine Learning Shape the Future of Teaching

https://events.educause.edu/eli/webinars/2019/how-ai-and-machine-learning-shape-the-future-of-teaching

Outcomes

• Explore what is meant by AI and how it relates to machine learning and data science
• Identify relevant uses of AI and machine learning to advance education
• Explore opportunities for using AI and machine learning to transform teaching
• Understand how technology can shape open educational materials

Kyle Bowen, Director, Teaching and Learning with Technology https://members.educause.edu/kyle-bowen

Jennifer Sparrow, Senior Director of Teaching and Learning With Tech, https://members.educause.edu/jennifer-sparrow

Malcolm Brown, Director, Educause, Learning Initiative

more in this IMB blog on Jennifer Sparrow and digital fluency: https://blog.stcloudstate.edu/ims/2018/11/01/preparing-learners-for-21st-century-digital-citizenship/

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Feb 5, 2018 webinar notes

creating a jazz band of one: ThoughSourus

Eureka: machine learning tool, brainstorming engine. give it an initial idea and it returns similar ideas. Like Google: refine the idea, so the machine can understand it better. create a collection of ideas to translate into course design or others.

Netlix:

influencers and microinfluencers, pre- and doing the execution

place to start explore and generate content.

https://answerthepublic.com/

a machine can construct a book with the help of a person. bionic book. machine and person working hand in hand. provide keywords and phrases from lecture notes, presentation materials. from there recommendations and suggestions based on own experience; then identify included and excluded content. then instructor can construct.

Design may be the least interesting part of the book for the faculty.

multiple choice quiz may be the least interesting part, and faculty might want to do much deeper assessment.

use these machine learning techniques to build assessment. how to more effectively. inquizitive is the machine learning

students engagements and similar prompts

presence in the classroom: pre-service teachers class. how to immerse them and practice classroom management skills

https://books.wwnorton.com/books/inquizitive/overview/

First class: marriage btw VR and use of AI – an environment headset: an algorithm reacts how teachers are interacting with the virtual kids. series of variables, oppty to interact with present behavior. classroom management skills. simulations and environments otherwise impossible to create. apps for these type of interactions

facilitation, reflection and research

AI for more human experience, allow more time for the faculty to be more human, more free time to contemplate.

Jason: Won’t the use of AI still reduce the amount of faculty needed?

Christina Dumeng: @Jason–I think it will most likely increase the amount of students per instructor.

Andrew Cole (UW-Whitewater): I wonder if instead of reducing faculty, these types of platforms (e.g., analytic capabilities) might require instructors to also become experts in the various technology platforms.

Dirk Morrison: Also wonder what the implications of AI for informal, self-directed learning?

Kate Borowske: The context that you’re presenting this in, as “your own jazz band,” is brilliant. These tools presented as a “partner” in the “band” seems as though it might be less threatening to faculty. Sort of gamifies parts of course design…?

Dirk Morrison: Move from teacher-centric to student-centric? Recommender systems, AI-based tutoring?

Andrew Cole (UW-Whitewater): The course with the bot TA must have been 100-level right? It would be interesting to see if those results replicate in 300, 400 level courses

Recording available here

https://events.educause.edu/eli/webinars/2019/how-ai-and-machine-learning-shape-the-future-of-teaching