- AI Episode 1: Intro to Artificial Intelligence in Teaching
- AI Episode 2: What Does An AI Teaching Assistant Look Like?
- AI Episode 3: Implications for Thought Leaders and Policy Developers
- Introducing Simulations into Teacher Preparation Programs
- Assistive Technology to Support Writing￼
- Enhancing Instruction and Empowering Educators with AI Tools and Technology
- So, AI Ruined Your Term Paper Assignment?
- Step by Step Use of Chat GPT
- CIDDL ChatGPT: Summarizing Text
- CIDDL ChatGPT: Solving Multiple Choice Questions
- Equity, Diversity, and Access to Technology in the Age of Artificial Intelligence
- CIDDL ChatGPT: Writing Programs
- CIDDL ChatGPT: Solving Word Problems
- Artificial Intelligence: Positives and Negatives in the Mathematics Classroom
- AI to Support Literacy
- Using the AI Bill of Rights to Guide Education’s use of AI and the European Commission’s “Ethical Guidelines for Teaching and Learning” to Guide the Future of AI in Education Part 1 of 2
- Using the AI Bill of Rights to Guide Education’s use of AI and the European Commission’s “Ethical Guidelines for Teaching and Learning” to Guide the Future of AI in Education Part 2 of 2
- Three Free & Easy Tools to Support Tiered Reading in Your Classroom
- The Question of Equity in the Age of ChatGPT
- CIDDList: 5 AIs You Need to Check Out This Summer!
- Mixed Reality Simulations, Personalized Learning, AI, and the Future of Education with Dr. Chris Dede
- Foundations for AI and the Future of Teaching and Learning from the US Department of Educational Technology
- Apple Enters the AR/VR/MR/XR Scene
- ChatGPT, AIs, and the IEP?
- There’s An AI for That: A Site Dedicated to Curating AIs
- UDL, Design Learning, and Personalized Learning
- Embracing the Future: How Teachers Can Harness AI at the Beginning of the School Year
- Empowering Special Education Faculty: Navigating the AI Landscape in Higher Education for 2023-2024.
- CIDDList: Back-to-School Checklist for Technology in Teacher Preparation Courses
- Cracking the Code: Students with Disabilities in the Computer Sciences
- UNESCO Discusses Artificial Intelligence
- AI-integrated Apps for Those with Visual Impairments: Camera-Based Identifiers and Readers
- Publishers Respond to Generative AI
- K-12 Generative AI Readiness Checklist
- CIDDL Talks How AI Will Change Special Education at TED
- Re-designing and Aligning an Intro to Special Education Class to the UDL Framework through Technology Integration: Minimizing Threats and Distractions
AI Episode 1: Intro to Artificial Intelligence in Teaching
Author: Matthew Marino, Co-Principal Investigator of CIDDL
Artificial intelligence (AI) has changed how we interact with the world. AI gives us the ability to talk into our phones and turn on lights in any room of our house. It can predict what we are looking for during online searches and deliver customized items we might be interested in purchasing to our desktop. Roomba vacuums use AI to process data collected from sensors in the vacuum. They can measure a room, identify obstacles, and maximize efficiency during the cleaning process. Clearly, this technology is improving our lives. Can the same principles be applied to teaching and learning? What questions should we be asking? What concerns should we have about the unintended consequences of AI in education? This five-part series will guide you toward a more informed understanding of the potential benefits and challenges associated with AI in education.
A recent blog post in Scientific American by Dr. Chris Piech of Stanford stated,
Many look to AI-powered tools to address the need to scale high-quality education and with good reason. A surge in educational content from online courses expanded access to digital devices, and the contemporary renaissance in AI seems to provide the pieces necessary to deliver personalized learning at scale. However, technology has a poor track record for solving social issues without creating unintended harm.
Dr. Piech is a lead researcher at Stanford, investigating how autonomous AI agents can act as teaching assistants for students. AI teaching assistants have the potential to reduce educational inequality by providing students with virtual teachers 24/7/365. The challenge for software developers is to ensure the AI provides individualized feedback that motivates and engages students. The agents must understand student progress and then provide the optimal level of support, not too difficult, not too easy, also known as students’ zone of proximal development. This is not difficult for the AI when students are engaged in problems that are easy for the AI to interpret, meaning tasks are simple and linear. However, researchers at Stanford are working on a process to enable AI teaching assistants to provide meaningful feedback as students complete open-ended problems in STEM disciplines. This is challenging because open-ended problems often have complex, nonlinear solutions. You can learn more about the research by checking on this blog.
Take a deep dive. This is an in-depth topic with many potential benefits and challenges. Public Broadcasting System (PBS) FRONTLINE featured a special on AI in 2019. It is worth watching when you have an hour or two to commit.