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AI and Digital Education Innovations for Teacher Development
学分 3 时长 3.0 小时 浏览人数 44
  
 
课程简介 学习指南 学习活动 授课教师

The purpose of this advanced training course is about the mainstreaming of Artificial Intelligence (AI) and digital education innovations for teachers’ competency development. The course is designed to provide an overview of AI, introduce you to the components of AI and other digital education innovations, explore the ethical and moral uses of AI, and consider how AI may ultimately impact teachers and teacher development.

学习指南

You have the freedom to move through topics in any sequence, or you can choose to do only those modules or topics that are of most interest to you. However, the course is designed on the assumption that you will progress through each module sequentially, learning as you go from beginning to end.

Embedded in each module are:

  • Learning activities where we will ask you to consider the topic in your specific educational context.
  • Interactive activities where you will build an AI chatbot and play an interactive game.
  • Case studies of specific implementations across the education spectrum and the globe.
  • Spotlights on books, reports, videos, and other influential resources.
  • Knowledge checks that help you self-assess your learning
  • Optional quizzes that serve as a summative assessment and that allow you to earn credits and a certificate for successful completion.

考核办法

Credits will be obtained by completing the following tasks:

  • Engage in all learning resources from Module 1 to Module 5.
  • Complete all learning activities of each module and complete each of the practice quizzes.
  • Complete the final assessment of each module and achieve more than 70 points.
  • Once you complete each of activities above, an instructor will manually review your work and verify you have met the all of the required elements. Upon successful review, a electronic certificate will be issued.



Module 0: Course Overview and Introduction

Welcome to AI and Digital Education Innovations for Teacher Development Overview and Planning Document! We’re glad you’ve joined us to learn more about this exciting and important topic. 

预计学习时间 0 分钟
0.1 Course Overview and Introduction
0.1 Course Introduction
0.1.1 Course Overview
0.1.2 Course Structure
0.2 Participants
0.2 Participants
0.2.1 Expectations for Participants
0.3 Course Authorship Team
0.3 Course Authorship Team
0.3.1 Our Commitment to You
0.4 Course Organizers
0.4 Course Organizers
0.5 Earning Credits
0.5 Earning Credits
0.6 Creative Commons License
0.6 Creative Commons License
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Module 1 Introduction to AI and Digital Education Innovations for Teacher Development

This module provides a broad overview of how AI and other digital education innovations may help support students, teachers, and teacher development. We will examine the importance of AI in education from a global context and review major trends impacting education. You will gain better insight into current major digital education innovations and more specifically, what AI is, what it isn’t, and how AI and other digital innovations can benefit education. 

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1.0 Module Overview
Introduction Video for Module 1
1.0 Module Learning Objectives
1.1 Why AI and Digital Education Innovations for Teacher Development?
1.1 Why AI and Digital Education Innovations for Teacher Development?
1.1.1 Potential of AI and Other Digital Education Innovations
1.1.2 AI for Learners
Activity 1.1
1.1.3 AI for Teachers
Activity 1.2
1.1.4. AI for Teacher Development
Activity 1.3
1.1.5 AI for You
Activity 1.4
1.1.6 Global Importance of AI in Education
1.1.6 Global Importance of AI in Education (Cont.)
Activity 1.5
Dr. Ian Jukes discuss his predictions for education in 2038
Knowledge Check 1.1
1.2 Potential AI-Based Solutions for Education
1.2 Potential AI-Based Solutions for Education
1.2.1 Current Digital Education Innovations
1.2.1.1 Adaptive Learning
1.2.1.2 Open Educational Resources
1.2.1.3 Gamification, Game-Based Learning, and Serious Games
1.2.1.4 Online And Massive Open Online Courses
1.2.1.5 Mobility, Mobile Devices, and Mobile Learning.
1.2.1.6 Blended Learning/Hybrid Learning
1.2.1.7 Virtual Reality, Augmented Reality, Mixed Reality, and Extended Reality.
Knowledge Check 1.2
1.3 Artificial Intelligence
1.3 Artificial Intelligence
1.3.1 AI: What It Is
1.3.2 AI: What It Isn’t
1.3.3 Weak AI vs Strong AI
Knowledge Check 1.3
1.4 Module Summary
1.4 Module Summary
Dr. Nicky Mohan shares her vision of 10 likely uses of AI in education
Module 1 Final Assessment
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Module 2: Data Analytics, Learning Analytics, and Artificial Intelligence

This module provides an overview of Data Analytics for education, specifically Learning Analytics. While focusing on the key data produced by students and instructors in the process of teaching and learning with technology, we will review how Artificial Intelligence consumes the data to build new opportunities. We also examine how Data Analytics has the potential to introduce a data-informed decision-making process to stakeholders such as students, parents, instructors, academic administrators, and governmental authorities.       

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2.0 Module Overview
Introduction Video for Module 2
2.0.1 Module Introduction and Learning Objectives
2.1 Introduction to Data Analytics , Data Mining, Data Analysis, and Reporting
2.1 Introduction
2.1.1 Introduction to Data Analytics
2.1.2 Data Mining, Data Analysis, and Reporting
Knowledge Check 2.1
2.2 Introduction to Learning Analytics
2.2 Introduction to Learning Analytics
2.2.1 Metrics of Learning Analytics
2.2.2 Learning Analytics Examples
Learning Activity 2.1
Knowledge Check 2.2
2.3 Artificial Intelligence
2.3 Artificial Intelligence
2.3.1 Types of Artificial Intelligence
2.3.2 Machine Learning
2.3.3 AI in Education Examples
Learning Activity 2.2
2.3.4 Case Studies and Additional Activities Related to AI in Education
Knowledge Check 2.3
2.4 Module Summary
Module Summary
Module 2 Final Assessment
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Module 3: Simulation and Gamification

In this module, we explore how AI and other advanced technologies can bring the real world into the classroom and the classroom into the real world through the process of active learning. We examine simulation, gamification, and the psychological concepts of flow and intrinsic motivation. We review the role of copyright in education and how crowdsourcing, copyleft, the Creative Commons, and Open Educational Resources Open Solutions can provide for empowering learning experience in an AI-enabled world.

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3.0 Module Overview
Introduction Video for Module 3
3.0 Module Introduction and Learning Objectives
3.1 Simulation
3.1 Introduction
3.1.1 Simulation
Learning Activity 3.1
Knowledge Check 3.1
3.2 Gamification
3.2. Introduction
3.2.1 Gamification
3.2.2 Gamification Examples
Learning Activity 3.2
Knowledge Check 3.2
3.3 Copyright and Open Educational Resources
3.3 Copyright and Open Educational Resources
3.3.1 Crowdsourcing
3.3.2 Copyleft
3.3.3 Open Source
3.3.4 Creative Commons
3.3.5 Open Educational Resources
3.3.6 Open Solutions
Knowledge Check 3.3
3.4 Module Summary
3.4 Module Summary
3.4.1 Module 3 Final Assessment
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Module 4: Ethical Considerations for the Use of AI and Advanced Technology in Education

In this module, we explore the ethics of AI in education. We examine the inherent risk of AI in general, in education specifically, and how the world is organising around a set of guiding principles to encourage the ethical use of AI. We explore how bias in AI occurs by learning about the types of bias in AI and review several well-known case studies of bias in AI. We also review cases of AI bias in education. Finally, we explore guidelines that can ensure the trustworthy use of AI. 

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4.0 Module Overview
Introduction Video for Module 4
4.0.1 Module Introduction and Learning Objectives
4.1 Moral Questions About AI in Education
4.1 Moral Questions About AI in Education
Learning Activity 4.1
4.2 Inherent Risk of AI
4.2 Inherent Risk of AI
4.2.1 Inherent Risk of AI in Education
Knowledge Check 4.1
4.3 Bias in AI
4.3 Bias in AI
4.3.1 Types of Bias in AI (Part I)
Learning Activity 4.2
4.3.1 Types of Bias in AI (Part II)
Gender Shades
4.3.1 Types of Bias in AI (Part III)
4.3.2 Examples of Real World Bias in Educational AI
Knowledge Check 4.2
4.4 Guidelines for Trustworthy Artificial Intelligence
4.4 Guidelines for Trustworthy Artificial Intelligence
4.4.1 Transparency, Audibility, and Accountability
4.4.2 Example of Ethics Guidelines for Trustworthy Artificial Intelligence
4.4.3 Example of an Assessment List for Employing Trustworthy Artificial Intelligence
Knowledge Check 4.3
4.5 Conclusion
4.5 Conclusion
4.5.1 Module 4 Final Assessment
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Module 5: Strategies for Incorporating AI and Digital Education Innovations for Teacher Development

In this module, we will help you separate hype from reality. You will gain an understanding of the difficulties of innovating in existing educational systems. We’ll guide in using practical and theoretical frameworks for making decisions in the selection of potential AI applications. We’ll look at the subject areas where AI in education is booming and where it is straggling. Finally, we’ll offer guidance for ways you can begin to implement AI immediately at the institutional, student, and classroom levels for both you and the teachers you develop. 

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5.0 Module Overview
Introduction Video for Module 5
5.0 Module Overview and Learning Objectives
5.1 Module Introduction
5.1 Module Introduction
5.2 Hype and Reality
5.2 Hype and Reality
5.2.1 Understanding the Hype Cycle
Learning Activity 5.1
5.3 Failure to Disrupt
5.3 Failure to Disrupt
5.3.1 Four Dilemmas
Learning Activity 5.2
5.4 The Learning Theory Perspective
5.4 The Learning Theory Perspective
Learning Activity 5.3
Knowledge Check 5.1
5.5 Areas of Greatest Focus for AI in Education
5.5 Areas of Greatest Focus for AI in Education
5.5.1 Prevalence of AI by Subject Area
Learning Activity 5.4
5.6 Putting AI to Work for You… Today
5.6 Putting AI to Work for You… Today
5.6.1 Schools & Institutions
5.6.2 Students
How we made David Beckham speak 9 languages
5.6.3 Teachers
Activity 5.5
5.7 Preparing Teachers for Future AI Adoption
5.7 Preparing Teachers for Future AI Adoption
Learning Activity 5.6
Knowledge Check 5.2
5.8 Bringing It All Together
5.8 Bringing It All Together
Final Learning Activity
5.9 Module Summary
5.9 Module Summary
5.9.1 Module 5 Final Assessment
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Course Conclusion
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Course Conclusion
Wrap Up
Next Steps
Credit Options
Thank You
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Your course authorship team consists of: 

Szymon Machajewski, Ph.D

Image of Szymon MachajewskiDr. Szymon Machajewski is a codewright and a gamification sherpa focused on student engagement through learning analytics. Authoring of open source projects such as BbStats and LoginAs was recognized in 2011 with an award in Innovative Code Development and a U.S. patent in e-learning. While teaching Computer Science since 2003, he is certified in Mental Health First Aid and most recently recognized with a national award for Optimising Student Experience and an award for Leading Change in 2021. For his work at the University of Illinois at Chicago, he was invited to the Blackboard Community Leadership Circle, a governance board appointed to lead and influence initiatives for the global education community. He also serves on the EDUCAUSE Student Success Analytics CG Steering Committee and UIC Electronic Information Technology (EIT) Accessibility Policy Committee.

Nicky Mohan, Ed.D

Image of Nicky MohanDr. Nicky Mohan is a global citizen. Born and raised in South Africa, she now shares her time between New Zealand and Canada. Nicky has been a classroom teacher, a school administrator, a university leader, a business sector manager, a corporate trainer, an international speaker, and a global consultant. She worked as the Director of Curriculum for the 21st Century Fluency Group (Canada). She is currently the Managing Partner of the InfoSavvy Group (Canada), and Director and co-founder of SpringBoard21 (USA). Nicky has co-written five books including the award-winning Reinventing Learning for the Always-on Generation, and the bestseller LeaderShift2020: Renewing Our Schools For Modern Times. She served as a member of the Teacher Task Force - UNESCO core working group on ‘The Role of AI in Education’. 

George Saltsman, Ed.D

Image of George SaltsmanDr. George Saltsman is an Associate Research Professor in the Center for Doctoral Studies in Educational Leadership and Director of the Center for Educational Innovation and Digital Learning at Lamar University where he works to advance the effectiveness of technology in education. In that pursuit, Dr. Saltsman has delivered over 250 presentations on technology integration and served as an educational consultant to Apple, Google, AT&T, Alcatel-Lucent, Pearson, and numerous ministries of education, NGOs, and corporations during his academic career. As a researcher, Dr. Saltsman has overseen 42 empirical investigations into digital learning working and is co-author of An Administrators Guide to Online Education and multiple other works focused on the integration of technology in education. For his dedication to advancing education he has been appointed as an Apple Distinguished Educator, mobile learning policy advisor to UNESCO, and winner of multiple awards, including Campus Technology Innovator of the Year, Blackboard Catalyst Award, and The New Media Consortium’s Center of Excellence Award.

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学分  3
时长  3.0 小时
学习活动数  140
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