What to Expect From Artificial Intelligence in K-12

Location: Room 217D

Listen and learn

[Listen and learn : Lecture]

Monday, June 26, 4:30–5:30 pm
Location: Room 217D

Dr. Scott Garrigan  
Forget fictional artificial intelligence (AI), it’s here today in K-12 schools. AI powers PARCC adaptive testing to Khan Academy mastery learning. AI understands language, does medical diagnosis, recommends books and drives cars. Amazon Inspire will recommend lessons. Explore ways AI will impact teaching and learning in your classroomor school.

Skill level: Beginner
Attendee devices: Devices useful
Attendee device specification: Laptop: PC, Chromebook, Mac
Tablet: Android, iOS, Windows
Focus: Digital age teaching & learning
Topic: Personalized learning
Grade level: PK-12
Subject area: STEM/STEAM
ISTE Standards: Administrators : Systemic improvement
Teachers : Design and develop digital age learning experiences and assessments
Students : Empowered learner
Additional detail: Session recorded for video-on-demand, Session will be simulcast live

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Proposal summary

Purpose & objective

Proposal Summary:
It took 20 years for technology to make an impact in business, 15 years in manufacturing, 10 years in health care, and our schools are next. But today’s technology increasingly comes with Artificial Intelligence (AI). And that will make a big difference to all of us.
The ISTE audience is interesting in emerging technologies in education, and AI is the first technology that can make complex judgments to help the teaching and learning process. The major educational significance is that AI can now do “white collar” and “professional” work like making medical diagnoses that used to take a trained physician. Rather than having only one intelligence (the teacher) to direct learning in a classroom, AI promises an array of intelligent support for student learning.
The introduction of AI systems that learn about students (through machine learning) will bring unexpected disruption as second-order effects. Replication will occur naturally as Khan Academy and PARCC adaptive testing have been unquestioningly adopted nationwide. ISTE participants need to be aware of this emerging disruption, its potential for improved learning as well as its potential threats.
The presenter has a doctorate in education with a minor in computer science. He’s studied artificial intelligence since 1984, made his first AI conference presentation in 1985, and created his first district-adopted AI-enabled software in 1990. He has closely followed the entry of AI into one field after another. As a frequent ISTE presenter, he is able to deliver complex ideas to a diverse audience through carefully-chosen examples and case studies. Many of the topics in this presentation were developed in his Lehigh University graduate course, “Trends and Innovations in Instructional Technology.”

Purpose & Objectives
The primary purpose of this session is to raise the awareness of educators and technologists to the current and anticipated application of Artificial Intelligence systems in K-12 education. These will shortly have some “white collar” and “professional” capabilities. Participants will be able to:
1. identify current examples of AI used in many schools,
2. recognize where AI is now used in professional applications that are comparable to education (like medical diagnosis and book recommendation).
3. state likely areas where powerful AI will partner with classroom teachers for diagnostic assessment, level placement, leveling up, and assessment.
4. state potential game changers like Amazon Insight recommending next learning activities based on student performance and interests.
5. recognize the huge successes AI has made in knowledge-intensive applications in Amazon, Google, IBM, Microsoft, Apple, and next, Pearson.


The one-hour session will alternate short presentation with discussion about each topic as follows:

10 min – introduction of speaker and topic (longer intro than usual)
10 min – case studies and examples of current “professional” AI applications outside education
5 min – discussion of AI outside of education
10 min – case studies & examples of current AI applications in education
5 min – discussion of education AI
10 min – projection of emergent “professional” AI apps in education
5 min – discussion of projected “professional” education AI
5 min – Q&A and summary

Supporting research

This is gigantic and active field. Below are just a few appropriate references I will share with the session participants:

Diamandis, Peter. “Abundance”
Kurzweil, Ray. “The Singularity is Near”



Dr. Scott Garrigan, Lehigh University

learning starts here

San Antonio

June 25-28, 2017

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