AI Literacy for Educators

Professional Development

AI Literacy for Educators: A Curriculum for 21st Century Teaching

January 6 - 17, 2025
AI Literacy for Educators: A Curriculum for 21st Century Teaching

Program Description:

AI Literacy for Educators aims to equip participants with essential knowledge and skills in the field of Artificial Intelligence (AI). The course includes five modules, each introducing one of the five big AI ideas. This course provides educators with a fundamental knowledge of AI, as well as the practical proficiency, ethical awareness, and a collaborative mindset essential for navigating the evolving landscape of Artificial Intelligence. The course's holistic approach ensures that students emerge with a well-rounded understanding of AI, ready to contribute meaningfully to their professional fields. The course will also include discussions and examples of how to integrate AI literacy across the curriculum.

  • Modules 1 and 2 will focus on the foundations of AI and will introduce such concepts as datasets, algorithms, autonomy, perception, and predictions. Students will use ethical metrics to unpack implications of AI technology and develop social awareness in AI across industries, including robotics, entertainment, social media, and chatbots.
  • Modules 3 and 4 will provide an overview of the AI decision-making process and will introduce such concepts as object perception, representation, decision trees and classification, search, and graphs. The course will encourage students to explore different types of computer perception that can extract meaning from sensory signals. Students will categorize real world problems in order to determine types of representation used in daily lives.
  • Module 5 will introduce machine perception and supervised machine learning. Students will explore reasoning algorithms and neural networks and utilize Teachable Machines to create a machine learning model. Students will also discuss the implications of algorithmic bias and what can be done to mitigate the bias.

Dates: January 6 - 17, 2025

Times: Live Zoom sessions that will meet each day from 7:00 - 9:30pm ET (Monday - Friday)

Format:  Online Modules with Live Zoom Sessions (See dates and times above)

Price: $590

For more information, questions or to register:  Email tcacademy@tc.columbia.edu

Please Note: This course is offered on a non-credit basis or for 0-3 credits. Registration for this course through TC Academy is for the non-credit offering and Academic Credits will not be awarded. For instructions on how to register for the credit offering see below.

This course can be taken for credit in accordance with TC's enrollment policies.  If you are not a current student and would like to take this course for credit, please review the Non-Degree Application Instructions page on our website and proceed accordingly.  Also, please note that if you plan to take this on a for-credit basis, college tuition and fees will apply.  If you are a continuing student in a degree program and have approval from your advisor, you can register for this course beginning on December 4th.  Winter session courses will follow spring registration and payment deadlines. 

 

Instructor(s)

Irina Lyublinskaya

Dr. Irina Lyublinskaya is a Professor of Mathematics and Education at Teachers College, Columbia University, New York.  She holds Ph.D. in Theoretical and Mathematical Physics from the Leningrad State University, Russia. She taught high school and university level mathematics and science for over 30 years. Her research interests are in the areas of STEM education, teacher education, curriculum development, and international comparative education. She is a recipient of multiple awards for teaching excellence. She has published substantially in these fields, including 16 books, 15 book chapters, and a substantial number of articles and conference proceedings.

 

Xiaoxue Du

Dr. Xiaoxue Du is a Postdoctoral Associate in the Personal Robots Group (PRG) at the MIT Media Lab. She received Ed.D in Instructional Technology and Media from Teachers College, Columbia University, following years of experience as a researcher and practitioner in the field of special education, teacher education, inclusive education, assessment and evaluation, and assistive technology. Her current research at MIT PRG focuses on K-12 Artificial Intelligence literacy in inclusive classrooms.

Learning Objectives

Participants will:

  • Develop an understanding of the foundations of AI, including such concepts as datasets, algorithms, autonomy, perception and predictions
  • Increase awareness of AI use across industries, including robotics, entertainment, social media, and chatbots
  • Learn to use ethical metrics to unpack the implications of AI technology
  • Engage with the building blocks of web-based applications that integrate machine learning models
  • Develop an understanding of the AI decision-making process
  • Categorize real world problems to explore the power of computer perception
  • Train machine models to recognize image and voice sets
  • Discuss the implications of algorithmic bias and strategies to mitigate such bias

Who Should Attend

Educators interested in AI, as well as degree and non-degree students enrolled in Teachers College or Columbia University. 

Upon Completion

Participants who successfully complete this course will receive a Certificate of Participation.

Licensed educators in NY state are also eligible for a Continuing Teacher Leader Education (CTLE) certificate for a total of 30 CTLE hours.

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