Micro-tutoring platform PhotoStudy has unveiled a new chatbot built on OpenAI’s ChatGPT APIs that can teach a complete elementary algebra textbook with “extremely high accuracy,” the company said.
“Textbook publishers and teachers can now transform their textbooks and teaching with a ChatGPT-like assistant that can teach all the material in a textbook, assess student progress, provide personalized help in weaker areas, generate quizzes with support for text, images, audio, and ultimately a student customized avatar for video interaction,” PhotoStudy said in its news release.
Some sample questions the MathGPT tool can answer:
“I don’t know how to solve a linear equation…”
“I have no idea what’s going on in class but we are doing Chapter 2. Can we start at the top?”
“Can you help me understand how to solve this mixture of coins problem?”
“I need to practice for my midterm tomorrow, through Chapter 6. Help.”
Streamlined and personalized teaching Some examples of how we’ve seen educators exploring how to teach and learn with tools like ChatGPT:
Drafting and brainstorming for lesson plans and other activities
Help with design of quiz questions or other exercises
Experimenting with custom tutoring tools
Customizing materials for different preferences (simplifying language, adjusting to different reading levels, creating tailored activities for different interests)
Providing grammatical or structural feedback on portions of writing
Use in upskilling activities in areas like writing and coding (debugging code, revising writing, asking for explanations)
Critique AI generated text
While several of the above draw on ChatGPT’s potential to be explored as a tool for personalization, there are risks associated with such personalization as well, including student privacy, biased treatment, and development of unhealthy habits. Before students use tools that offer these services without direct supervision, they and their educators should understand the limitations of the tools outlined below.
Also relevant/see:
Designing Assignments in the ChatGPT Era — from insidehighered.com by Susan D’Agostino Some instructors seek to craft assignments that guide students in surpassing what AI can do. Others see that as a fool’s errand—one that lends too much agency to the software.
Excerpt (emphasis DSC):
David Wiley wrote a thoughtful post on the ways in which AI and Large Language Models (LLMs) can “provide instructional designers with first drafts of some of the work they do.” He says “imagine you’re an instructional designer who’s been paired with a faculty member to create a course in microeconomics. These tools might help you quickly create first drafts of” learning outcomes, discussion prompts, rubrics, and formative assessment items. The point is that LLMs can quickly generate rough drafts that are mostly accurate drafts, that humans can then “review, augment, and polish,” potentially shifting the work of instructional designers from authors to editors. The post is well worth your time.
… The question that I’d like to spend some time thinking about is the following: What new knowledge, capacities, and skills do instructional designers need in their role as editors and users of LLMs?
This resonated with me. Instructional Designer positions are starting to require AI and ML chops. I’m introducing my grad students to AI and ChatGPT this semester. I have an assignment based on it.
A learning ecosystem is composed of people, tools, technologies, content, processes, culture, strategies, and any other resource that helps one learn. Learning ecosystems can be at an individual level as well as at an organizational level.
Some example components:
Subject Matter Experts (SMEs) such as faculty, staff, teachers, trainers, parents, coaches, directors, and others
Fellow employees
L&D/Training professionals
Managers
Instructional Designers
Librarians
Consultants
Types of learning
Active learning
Adult learning
PreK-12 education
Training/corporate learning
Vocational learning
Experiential learning
Competency-based learning
Self-directed learning (i.e., heutagogy)
Mobile learning
Online learning
Face-to-face-based learning
Hybrid/blended learning
Hyflex-based learning
Game-based learning
XR-based learning (AR, MR, and VR)
Informal learning
Formal learning
Lifelong learning
Microlearning
Personalized/customized learning
Play-based learning
Cloud-based learning apps
Coaching & mentoring
Peer feedback
Job aids/performance tools and other on-demand content
Websites
Conferences
Professional development
Professional organizations
Social networking
Social media – Twitter, LinkedIn, Facebook/Meta, other
Communities of practice
Artificial Intelligence (AI) — including ChatGPT, learning agents, learner profiles,
AI to help realize your dream career The Unschooler mentor helps you understand what you need to do to achieve your dream career. You can select one of six broad areas of expertise: science, people, tech, info, art, and business. The platform will then ask questions related to your future career.
It also has some other useful features. Unschooler keeps track of your skills by adding them to a skill map that’s unique to you.You can also ask it to expand on the information it has already given you. This is done by selecting the text and clicking one of four buttons: more, example, how to, explain, and a question mark icon that defines the selected text. There’s also a mobile app that analyzes text from pictures and explains tasks or concepts.
From DSC: This integration of AI is part of the vision that I’ve been tracking at:
AI already does and will continue to impact education – along with every other sector.
Innovative education leaders have an opportunity to build the foundation for the most personalized learning system we have ever seen.
Action
Education leaders need to consider these possible futures now. There is no doubt that K-12 and higher ed learners will be using these tools immediately. It is not a question of preventing “AI plagiarism” (if such a thing could exist), but a question of how to modify teaching to take advantage of these new tools.
From DSC: They go on to list some solid ideas and experiments to try out — both for students and for teachers. Thanks Nate and Rachelle!
I really hate to be that guy, but AI is going to be transformative as a teacher. ?
I asked AI the following:
“Plan three lessons to explain how volcanoes are formed. Each lesson needs an introductory activity, information input, a student task and a plenary.”
I pasted the Volcano Lesson 1 content in, and it generated eight slides in under a minute. It's very basic, but for bare bones deckbuilding, it's got such potential. https://t.co/F9CEp9jd75 ? 2/3
In 2023, we are going to a huge increase in content creation generated by AI avatars. The use cases the infinite – from demos and tutorials to billboards and even ads.
? Here are 6 companies that are currently defining the future of content creation:
GPT Takes the Bar Exam — from papers.ssrn.com by Michael James Bommarito and Daniel Martin Katz; with thanks to Gabe Teninbaum for his tweet on this
Excerpt from the Abstract (emphasis DSC):
While our ability to interpret these results is limited by nascent scientific understanding of LLMs and the proprietary nature of GPT, we believe that these results strongly suggest that an LLM will pass the MBE component of the Bar Exam in the near future.
Real Ways Professionals Can Use ChatGPT to Improve Job Performance
Let’s dive into some real examples of how professionals across sales, marketing, product management, project management, recruiting, and teaching can take advantage of this new tool and leverage it for even more impact in their careers.
Teachers and ChatGPT
Help with grading and feedback on student work.
Example prompt: “Tell me every grammar rule that’s been violated in this student’s essay: [paste in essay]”
Create personalized learning materials.
Example prompt: “Help me explain photosynthesis to a 10th grade student in a way similar to sports.”
Generate lesson plans and activities.
Example prompt: “Create an activity for 50 students that revolves around how to learn the different colors of the rainbow.” or “Generate a lesson plan for a high school English class on the theme of identity and self-discovery, suitable for a 45-minute class period.”
Write fake essays several reading levels below your class, then print them out, and have your students review and edit the AI’s work to make it better.
Example prompt: “Generate a 5th grade level short essay about Maya Angelou and her work.”
Providing one-on-one support to students. Example prompt: “How can I best empower an introverted student in my classroom during reading time?”
From DSC: I haven’t tried these prompts. Rather I post this because I’m excited about the potential of Artificial Intelligence (AI) to help people teach and to help people to learn.
Seriously, #ChatGPT is going to change everything about how people gain access to legal information and guidance. Look at this. pic.twitter.com/BkxZlMxB9o
Out today! Catch the latest episode of Talk Justice for a look at creative ways to connect people with legal professionals and resources– by bus, kiosks and even a kayak! https://t.co/wApNohRJw3
OpenAI has built the best Minecraft-playing bot yet by making it watch 70,000 hours of video of people playing the popular computer game. It showcases a powerful new technique that could be used to train machines to carry out a wide range of tasks by binging on sites like YouTube, a vast and untapped source of training data.
The Minecraft AI learned to perform complicated sequences of keyboard and mouse clicks to complete tasks in the game, such as chopping down trees and crafting tools. It’s the first bot that can craft so-called diamond tools, a task that typically takes good human players 20 minutes of high-speed clicking—or around 24,000 actions.
The result is a breakthrough for a technique known as imitation learning, in which neural networks are trained to perform tasks by watching humans do them.
…
The team’s approach, called Video Pre-Training (VPT), gets around the bottleneck in imitation learning by training another neural network to label videos automatically.
“Most language learning software can help with the beginning part of learning basic vocabulary and grammar, but gaining any degree of fluency requires speaking out loud in an interactive environment,” Zwick told TechCrunch in an email interview. “To date, the only way people can get that sort of practice is through human tutors, which can also be expensive, difficult and intimidating.”
Speak’s solution is a collection of interactive speaking experiences that allow learners to practice conversing in English. Through the platform, users can hold open-ended conversations with an “AI tutor” on a range of topics while receiving feedback on their pronunciation, grammar and vocabulary.
It’s one of the top education apps in Korea on the iOS App Store, with over 15 million lessons started annually, 100,000 active subscribers and “double-digit million” annual recurring revenue.
If you last checked in on AI image makers a month ago & thought “that is a fun toy, but is far from useful…” Well, in just the last week or so two of the major AI systems updated.
You can now generate a solid image in one try. For example, “otter on a plane using wifi” 1st try: pic.twitter.com/DhiYeVMEEV
So, is this a cool development that will become a fun tool for many of us to play around with in the future? Sure. Will people use this in their work? Possibly. Will it disrupt artists across the board? Unlikely. There might be a few places where really generic artwork is the norm and the people that were paid very little to crank them out will be paid very little to input prompts. Look, PhotoShop and asset libraries made creating company logos very, very easy a long time ago. But people still don’t want to take the 30 minutes it takes to put one together, because thinking through all the options is not their thing. You still have to think through those options to enter an AI prompt. And people just want to leave that part to the artists. The same thing was true about the printing press. Hundreds of years of innovation has taught us that the hard part of the creation of art is the human coming up with the ideas, not the tools that create the art.
A quick comment from DSC: Possibly, at least in some cases. But I’ve seen enough home-grown, poorly-designed graphics and logos to make me wonder if that will be the case.
How to Teach With Deep Fake Technology — from techlearning.com by Erik Ofgang Despite the scary headlines, deep fake technology can be a powerful teaching tool
Excerpt:
The very concept of teaching with deep fake technology may be unsettling to some. After all, deep fake technology, which utilizes AI and machine learning and can alter videos and animate photographs in a manner that appears realistic, has frequently been covered in a negative light. The technology can be used to violate privacy and create fake videos of real people.
However, while these potential abuses of the technology are real and concerning that doesn’t mean we should turn a blind eye to the technology’s potential when using it responsibly, says Jaime Donally, a well-known immersive learning expert.
From DSC: I’m still not sure about this one…but I’ll try to be open to the possibilities here.
Recently, we spoke with three more participants of the AI Explorations program to learn about its ongoing impact in K-12 classrooms. Here, they share how the program is helping their districts implement AI curriculum with an eye toward equity in the classroom.
A hitherto stealth legal AI startup emerged from the shadows today with news via TechCrunch that it has raised $5 million in funding led by the startup fund of OpenAI, the company that developed advanced neural network AI systems such as GPT-3 and DALL-E 2.
The startup, called Harvey, will build on the GPT-3 technology to enable lawyers to create legal documents or perform legal research by providing simple instructions using natural language.
The company was founded by Winston Weinberg, formerly an associate at law firm O’Melveny & Myers, and Gabriel Pereyra, formerly a research scientist at DeepMind and most recently a machine learning engineer at Meta AI.
You’ve likely been reading for the last few minutes my arguments for why AI is going to change education. You may agree with some points, disagree with others…
Only, those were not my words.
An AI has written every single word in this essay up until here.
The only thing I wrote myself was the first sentence: Artificial Intelligence is going to revolutionize education. The images too, everything was generated by AI.
Using Virtual Reality for Career Training — from techlearning.com by Erik Ofgang The Boys & Girls Clubs of Indiana have had success using virtual reality simulations to teach students about career opportunities.
Excerpts:
Virtual reality can help boost CTE programs and teach students about potential careers in fields they may know nothing about, says Lana Taylor from the Indiana Alliance of Boys & Girls Clubs of America.
…
One of those other resources has been a partnership with Transfer VR to provide students access to headsets to participate in career simulations that can give them a tactile sense of what working in certain careers might be like.
“Not all kids are meant to go to college, not all kids want to do it,” Taylor says. “So it’s important to give them some exposure to different careers and workforce paths that maybe they hadn’t thought of before.”
Get Ready to Relearn How to Use the Internet — from bloomberg.com by Tyle Cowen; with thanks to Sam DeBrule for this resource Everyone knows that an AI revolution is coming, but no one seems to realize how profoundly it will change their day-to-day life.
Excerpts:
This year has brought a lot of innovation in artificial intelligence, which I have tried to keep up with, but too many people still do not appreciate the import of what is to come. I commonly hear comments such as, “Those are cool images, graphic designers will work with that,” or, “GPT-3 is cool, it will be easier to cheat on term papers.” And then they end by saying: “But it won’t change my life.”
This view is likely to be proven wrong — and soon, as AI is about to revolutionize our entire information architecture. You will have to learn how to use the internet all over again.
…
Change is coming. Consider Twitter, which I use each morning to gather information about the world. Less than two years from now, maybe I will speak into my computer, outline my topics of interest, and somebody’s version of AI will spit back to me a kind of Twitter remix, in a readable format and tailored to my needs.
The AI also will be not only responsive but active. Maybe it will tell me, “Today you really do need to read about Russia and changes in the UK government.” Or I might say, “More serendipity today, please,” and that wish would be granted.
Of course all this is just one man’s opinion. If you disagree, in a few years you will be able to ask the new AI engines what they think.
In this blog, we introduce an important natural language understanding (NLU) capability called Natural Language Assessment (NLA), and discuss how it can be helpful in the context of education. While typical NLU tasks focus on the user’s intent, NLA allows for the assessment of an answer from multiple perspectives. In situations where a user wants to know how good their answer is, NLA can offer an analysis of how close the answer is to what is expected. In situations where there may not be a “correct” answer, NLA can offer subtle insights that include topicality, relevance, verbosity, and beyond. We formulate the scope of NLA, present a practical model for carrying out topicality NLA, and showcase how NLA has been used to help job seekers practice answering interview questions with Google’s new interview prep tool, Interview Warmup.
A startup that provides AI-powered translation is working with the National Weather Service to improve language translations of extreme weather alerts across the U.S.
When I’ve been doing this with GPT-3, a 175 billion parameter language model, it has been uncanny how much it reminds me of blogging. When I’m writing this, from March through August 2022, large language models are not yet as good at responding to my prompts as the readers of my blog. But their capacity is improving fast and the prices are dropping.
Soon everyone can have an alien intelligence in their inbox.
The search for TV’s next killer app
TV makers have some reason to celebrate these days: Streaming has officially surpassed cable and broadcast as the most popular form of TV consumption; smart TVs are increasingly replacing external streaming devices; and the makers of these TVs have largely figured out how to turn those one-time purchases into recurring revenue streams, thanks to ad-supported services.
… What TV makers need is a new killer app. Consumer electronics companies have for some time toyed with the idea of using TV for all kinds of additional purposes, including gaming, smart home functionality and fitness. Ad-supported video took priority over those use cases over the past few years, but now, TV brands need new ways to differentiate their devices.
Turning the TV into the most useful screen in the house holds a lot of promise for the industry. To truly embrace this trend, TV makers might have to take some bold bets and be willing to push the envelope on what’s possible in the living room.
From DSC: What if smart TVs’ new killer app was a next-generation learning-related platform? Could smart TVs deliver more blended/hybrid learning? Hyflex-based learning? .
.
Or what if smart TVs had to do with delivering telehealth-based apps? Or telelegal/virtual courts-based apps?
![The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV](http://danielschristian.com/learning-ecosystems/wp-content/uploads/2012/07/The-Living-Class-Room-Daniel-S-Christian-July-2012.jpg)