A few current categories of AI in Edtech particularly jump out:
Teacher Productivity and Joy: Tools to make educators’ lives easier (and more fun?) by removing some of the more rote tasks of teaching, like lesson planning (we counted at least 8 different tools for lesson planning), resource curation and data collection.
Personalization and Learning Delivery: Tools to tailor instruction to the particular interests, learning preferences and preferred media consumption of students. This includes tools that convert text to video, video to text, text to comic books, Youtube to notes, and many more.
Study and Course Creation Tools: Tools for learners to automatically make quizzes, flashcards, notes or summaries of material, or even to automatically create full courses from a search term.
AI Tutors, Chatbots and Teachers: There will be no shortage of conversational AI “copilots” (which may take many guises) to support students in almost any learning context. Many Edtech companies launched their own during the conference. Possible differentiators here could be personality, safety, privacy, access to a proprietary or specific data set, or bots built on proprietary LLMs.
Simplifying Complex Processes: One of the most inspiring conversations of the conference for me was with Tiffany Green, founder of Uprooted Academy, about how AI can and should be used to remove bureaucratic barriers to college for underrepresented students (for example, used to autofill FAFSA forms, College Applications, to search for schools and access materials, etc). This is not the only complex bureaucratic process in education.
Educational LLMs: The race is on to create usable large language models for education that are safe, private, appropriate and classroom-ready. Merlyn Mind is working on this, and companies that make LLMs are sprouting up in other sectors…
This week I spent a few days at the ASU/GSV conference and ran into 7,000 educators, entrepreneurs, and corporate training people who had gone CRAZY for AI.
No, I’m not kidding. This community, which makes up people like training managers, community college leaders, educators, and policymakers is absolutely freaked out about ChatGPT, Large Language Models, and all sorts of issues with AI. Now don’t get me wrong: I’m a huge fan of this. But the frenzy is unprecedented: this is bigger than the excitement at the launch of the i-Phone.
Second, the L&D market is about to get disrupted like never before. I had two interactive sessions with about 200 L&D leaders and I essentially heard the same thing over and over. What is going to happen to our jobs when these Generative AI tools start automatically building content, assessments, teaching guides, rubrics, videos, and simulations in seconds?
The answer is pretty clear: you’re going to get disrupted. I’m not saying that L&D teams need to worry about their careers, but it’s very clear to me they’re going to have to swim upstream in a big hurry. As with all new technologies, it’s time for learning leaders to get to know these tools, understand how they work, and start to experiment with them as fast as you can.
Speaking of the ASU+GSV Summit, see this posting from Michael Moe:
Last week, the 14th annual ASU+GSV Summit hosted over 7,000 leaders from 70+ companies well as over 900 of the world’s most innovative EdTech companies. Below are some of our favorite speeches from this year’s Summit…
High-quality tutoring is one of the most effective educational interventions we have – but we need both humans and technology for it to work. In a standing-room-only session, GSE Professor Susanna Loeb, a faculty lead at the Stanford Accelerator for Learning, spoke alongside school district superintendents on the value of high-impact tutoring. The most important factors in effective tutoring, she said, are (1) the tutor has data on specific areas where the student needs support, (2) the tutor has high-quality materials and training, and (3) there is a positive, trusting relationship between the tutor and student. New technologies, including AI, can make the first and second elements much easier – but they will never be able to replace human adults in the relational piece, which is crucial to student engagement and motivation.
ChatGPT, Bing Chat, Google’s Bard—AI is infiltrating the lives of billions.
The 1% who understand it will run the world.
Here’s a list of key terms to jumpstart your learning:
Being “good at prompting” is a temporary state of affairs.The current AI systems are already very good at figuring out your intent, and they are getting better. Prompting is not going to be that important for that much longer. In fact, it already isn’t in GPT-4 and Bing. If you want to do something with AI, just ask it to help you do the thing. “I want to write a novel, what do you need to know to help me?” will get you surprisingly far.
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The best way to use AI systems is not to craft the perfect prompt, but rather to use it interactively. Try asking for something. Then ask the AI to modify or adjust its output. Work with the AI, rather than trying to issue a single command that does everything you want. The more you experiment, the better off you are. Just use the AI a lot, and it will make a big difference – a lesson my class learned as they worked with the AI to create essays.
From DSC: Agreed –> “Being “good at prompting” is a temporary state of affairs.” The User Interfaces that are/will be appearing will help greatly in this regard.
From DSC: Bizarre…at least for me in late April of 2023:
FaceTiming live with AI… This app came across the @ElunaAI Discord and I was very impressed with its responsiveness, natural expression and language, etc…
Feels like the beginning of another massive wave in consumer AI products.
The rise of AI-generated music has ignited legal and ethical debates, with record labels invoking copyright law to remove AI-generated songs from platforms like YouTube.
Tech companies like Google face a conundrum: should they take down AI-generated content, and if so, on what grounds?
Some artists, like Grimes, are embracing the change, proposing new revenue-sharing models and utilizing blockchain-based smart contracts for royalties.
The future of AI-generated music presents both challenges and opportunities, with the potential to create new platforms and genres, democratize the industry, and redefine artist compensation.
The Need for AI PD — from techlearning.com by Erik Ofgang Educators need training on how to effectively incorporate artificial intelligence into their teaching practice, says Lance Key, an award-winning educator.
“School never was fun for me,” he says, hoping that as an educator he could change that with his students. “I wanted to make learning fun.” This ‘learning should be fun’ philosophy is at the heart of the approach he advises educators take when it comes to AI.
At its 11th annual conference in 2023, educational company Coursera announced it is adding ChatGPT-powered interactive ed tech tools to its learning platform, including a generative AI coach for students and an AI course-building tool for teachers. It will also add machine learning-powered translation, expanded VR immersive learning experiences, and more.
Coursera Coach will give learners a ChatGPT virtual coach to answer questions, give feedback, summarize video lectures and other materials, give career advice, and prepare them for job interviews. This feature will be available in the coming months.
From DSC: Yes…it will be very interesting to see how tools and platforms interact from this time forth. The term “integration” will take a massive step forward, at least in my mind.
A New Era for Education — from linkedin.com by Amit Sevak, CEO of ETS and Timothy Knowles, President of the Carnegie Foundation for the Advancement of Teaching
Excerpt (emphasis DSC):
It’s not every day you get to announce a revolution in your sector. But today, we’re doing exactly that. Together, we are setting out to overturn 117 years of educational tradition. … The fundamental assumption [of the Carnegie Unit] is that time spent in a classroom equals learning. This formula has the virtue of simplicity. Unfortunately, a century of research tells us that it’s woefully inadequate.
From DSC: It’s more than interesting to think that the Carnegie Unit has outlived its usefulness and is breaking apart. In fact, the thought is very profound.
If that turns out to be the case, the ramifications will be enormous and we will have the opportunity to radically reinvent/rethink/redesign what our lifelong learning ecosystems will look like and provide.
So I appreciate what Amit and Timothy are saying here and I appreciate their relaying what the new paradigm might look like. It goes with the idea of using design thinking to rethink how we build/reinvent our learning ecosystems. They assert:
It’s time to change the paradigm. That’s why ETS and the Carnegie Foundation have come together to design a new future of assessment.
Whereas the Carnegie Unit measures seat time, the new paradigm willmeasureskills—with a focus on the ones we know are most important for success in career and in life.
Whereas the Carnegie Unit never leaves the classroom, the new paradigm willcapture learning wherever it takes place—whether that is in after-school activities, during a work-experience placement, in an internship, on an apprenticeship, and so on.
Whereas the Carnegie Unit offers only one data point—pass or fail—the new paradigm willgenerate insights throughout the learning process, the better to guide students, families, educators, and policymakers.
I could see this type of information being funneled into peoples’ cloud-based learner profiles — which we as individuals will own and determine who else can access them. I diagrammed this back in January of 2017 using blockchain as the underlying technology. That may or may not turn out to be the case. But the concept will still hold I think — regardless of the underlying technology(ies).
For example, we are seeing a lot more articles regarding things like Comprehensive Learner Records (CLR) or Learning and Employment Records (LER; examplehere), and similar items.
Speaking of reinventing our learning ecosystems, also see:
Learning happens throughout life and is not isolated to the K-12 or higher education sectors. Yet, often, validations of learning only happen in these specific areas. The system of evaluation based on courses, grades, and credit serves as a poor proxy for communicating skills given the variation in course content, grade inflation, and inclusion of participation and extra credit within course grades.
Credentialed learning provides a way to accurately document human capability for all learners throughout their life. A lifetime credentialed learning ecosystem provides better granularity around learning, better documentation of the learning, and more relevance for both the credential recipient and reviewer. This improves the match between higher education and/or employment with the individual, while also providing a more clear and accurate lifetime learning pathway.
With a fully-credentialed system, individuals can own well-documented evidence of a lifetime of learning and choose what and when to share this data. This technology enables every learner to have more opportunities for finding the best career match without today’s existing barriers around cost, access, and proxies.
Addendum on 4/28/23 — speaking of credentials:
First Rung — from the-job.beehiiv.com by Paul Fain New research shows stacking credentials pays off for low-income learners.
Stacking credentials pays off for many low-income students, new research finds, but only if learners move up the education ladder. Also, Kansas is hoping a new grant program will attract more companies to participate in microinternships.
GPT-4 passes basically every exam. And doesn’t just pass…
The Bar Exam: 90%
LSAT: 88%
GRE Quantitative: 80%, Verbal: 99%
Every AP, the SAT… pic.twitter.com/zQW3k6uM6Z
Sal Khan walks through Khan Academy’s GPT-4 integration (not generally available yet). Folks can join the waitlist at Khanacademy.org. To learn more about Khanmigo, visit: khanacademy.org/khan-labs
We believe that AI has the potential to transform learning in a positive way, but we are also keenly aware of the risks. To test the possibilities, we’re inviting our district partners to opt in to Khan Labs, a new space for testing learning technology. We want to ensure that our work always puts the needs of students and teachers first, and we are focused on ensuring that the benefits of AI are shared equally across society. In addition to teachers and students, we’re inviting the general public to join a waitlist to test Khanmigo. Teachers, students and donors will be our partners on this learning journey, helping us test AI to see if we can harness it as a learning tool for all.
GPT-4 has arrived. It will blow ChatGPT out of the water.— from washingtonpost.com by Drew Harwell and Nitasha Tiku The long-awaited tool, which can describe images in words, marks a huge leap forward for AI power — and another major shift for ethical norms
For example, [GPT-4] passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%.
ChatGPT as a teaching tool, not a cheating tool — from timeshighereducation.com by Jennifer Rose How to use ChatGPT as a tool to spur students’ inner feedback and thus aid their learning and skills development
Excerpt:
Use ChatGPT to spur student’s inner feedback
One way that ChatGPT answers can be used in class is by asking students to compare what they have written with a ChatGPT answer. This draws on David Nicol’s work on making inner feedback explicit and using comparative judgement. His work demonstrates that in writing down answers to comparative questions students can produce high-quality feedback for themselves which is instant and actionable. Applying this to a ChatGPT answer, the following questions could be used:
Which is better, the ChatGPT response or yours? Why?
What two points can you learn from the ChatGPT response that will help you improve your work?
What can you add from your answer to improve the ChatGPT answer?
How could the assignment question set be improved to allow the student to demonstrate higher-order skills such as critical thinking?
How can you use what you have learned to stay ahead of AI and produce higher-quality work than ChatGPT?
Artificial Intelligence is now taking the world of learning by storm. Here are 5 ways you can successfully incorporate AI in online learning.
Let’s say you’re training sales reps on handling different customer personalities. You can use this technology to diversify your branching scenarios so that trainees can also speak and not only type. This way, not only will the training become more realistic, but you’ll also be able to assess and work on additional elements, such as tone of voice, volume, speech tempo, etc.
Modeled on research demonstrating that the most effective form of learning is one-on-one tutoring1, Q-Chat offers students the experience of interacting with a personal AI tutor in an effective and conversational way. Whether they’re learning French vocabulary or Roman History, Q-Chat engages students with adaptive questions based on relevant study materials delivered through a fun chat experience. Pulling from Quizlet’s massive educational content library and using the question-based Socratic method to promote active learning, Q-Chat has the ability to test a student’s knowledge of educational content, ask in-depth questions to get at underlying concepts, test reading comprehension, help students learn a language and encourage students on healthy learning habits.
To explore this question, I collaborated with my new friend Chat GPT to create a concept of what a day in the life of a 2040 student might look like. The results were fascinating, providing a glimpse into the possible future of education.
In response to our collaborative moment, I would like to pose three guiding questions to the audience:
How might we re-imagine education to create a more holistic and meaningful learning experience for our students as we move forward towards 2040?
How might we cultivate a sense of curiosity, wonder, and creativity in our students, and how might this foster a deeper engagement with learning?
How might we expand the definition of “education” beyond the confines of the classroom and foster lifelong learning and growth in our students?
From DSC: I appreciated this interesting thought experiment re: the future of learning in the year 2040. I appreciate Russell’s statement where he says:
To conduct a thorough and accurate foresight project, it is crucial to explore multiple potential futures. While the scenario presented here is intended to be playful and imaginative, it represents only one possible outcome among many. I encourage readers to share their scenarios and perspectives in the comments, as this will help to create a more robust and diverse exploration of the future.
Fascinating chat with three people heading up L&D in a major international company. AI has led them to completely re-evaluate their strategy. Key concepts were performance, process and data. What I liked was their focus on that oft-quoted issue of aligning L&D with the business goals – unlike most, they really meant it.
The technology that puts that in the hands of learners has arrived. Performance support will be a teacher or trainer at your fingertips.
We also talked about prompting, the need to see it as ‘CHAT’gpt, an iterative process, where you need to understand how to speak to the tech. It’s a bit like speaking to an alien from space, as it has no comprehension or consciousness but it is still competent and smart. We have put together 100 prompt tips for learning professionals and taking it out on the road soon. All good in the hood.
Introducing: ChatGPT Edu-Mega-Prompts— from drphilippahardman.substack.com by Dr. Philippa Hardman; with thanks to Ray Schroeder out on LinkedIn for this resource How to combine the power of AI + learning science to improve your efficiency & effectiveness as an educator
From DSC:
Before relaying some excerpts, I want to say that I get the gist of what Dr. Hardman is saying re: quizzes. But I’m surprised to hear she had so many pedagogical concerns with quizzes. I, too, would like to see quizzes used as an instrument of learning and to practice recall — and not just for assessment. But I would give quizzes a higher thumbs up than what she did. I think she was also trying to say that quizzes don’t always identify misconceptions or inaccurate foundational information.
Excerpts:
The Bad News: Most AI technologies that have been built specifically for educators in the last few years and months imitate and threaten to spread the use of broken instructional practices (i.e. content + quiz).
The Good News: Armed with prompts which are carefully crafted to ask the right thing in the right way, educators can use AI like GPT3 to improve the effectiveness of their instructional practices.
As is always the case, ChatGPT is your assistant. If you’re not happy with the result, you can edit and refine it using your expertise, either alone or through further conversation with ChatGPT.
For example, once the first response is generated, you can ask ChatGPT to make the activity more or less complex, to change the scenario and/or suggest more or different resources – the options are endless.
Philippa recommended checking out Rob Lennon’s streams of content. Here’s an example from his Twitter account:
Everyone’s using ChatGPT.
But almost everyone’s STUCK in beginner mode.
10 techniques to get massively ahead with AI:
(cut-and-paste these prompts?)
— Rob Lennon ? | Audience Growth (@thatroblennon) January 3, 2023
AI-assisted design and development work
This is the trend most likely to have a dramatic evolution this year.
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Solutions like large language models, speech generators, content generators, image generators, translation tools, transcription tools, and video generators, among many others, will transform the way IDs create the learning experiences our organizations use. Two examples are:
1. IDs will be doing more curation and less creation:
Many IDs will start pulling raw material from content generators (built using natural language processing platforms like Open AI’s GPT-3, Microsoft’s LUIS, IBM’s Watson, Google’s BERT, etc.) to obtain ideas and drafts that they can then clean up and add to the assets they are assembling. As technology advances, the output from these platforms will be more suitable to become final drafts, and the curation and clean-up tasks will be faster and easier.
Then, the designer can leverage a solution like DALL-E 2 (or a product developed based on it) to obtain visuals that can (or not) be modified with programs like Illustrator or Photoshop (see image below for Dall-E’s “Cubist interpretation of AI and brain science.”
2. IDs will spend less, and in some cases no time at all, creating learning pathways
AI engines contained in LXPs and other platforms will select the right courses for employees and guide these learners from their current level of knowledge and skill to their goal state with substantially less human intervention.
Somehow, Mira Murati can forthrightly discuss the dangers of AI while making you feel like it’s all going to be OK.
… A growing number of leaders in the field are warning of the dangers of AI. Do you have any misgivings about the technology?
This is a unique moment in time where we do have agency in how it shapes society. And it goes both ways: the technology shapes us and we shape it. There are a lot of hard problems to figure out. How do you get the model to do the thing that you want it to do, and how you make sure it’s aligned with human intention and ultimately in service of humanity? There are also a ton of questions around societal impact, and there are a lot of ethical and philosophical questions that we need to consider. And it’s important that we bring in different voices, like philosophers, social scientists, artists, and people from the humanities.
Gerganov adapted it from a program called Whisper, released in September by OpenAI, the same organization behind ChatGPTand dall-e. Whisper transcribes speech in more than ninety languages. In some of them, the software is capable of superhuman performance—that is, it can actually parse what somebody’s saying better than a human can.
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Until recently, world-beating A.I.s like Whisper were the exclusive province of the big tech firms that developed them.
Ever since I’ve had tape to type up—lectures to transcribe, interviews to write down—I’ve dreamed of a program that would do it for me. The transcription process took so long, requiring so many small rewindings, that my hands and back would cramp. As a journalist, knowing what awaited me probably warped my reporting: instead of meeting someone in person with a tape recorder, it often seemed easier just to talk on the phone, typing up the good parts in the moment.
From DSC: Journalism majors — and even seasoned journalists — should keep an eye on this type of application, as it will save them a significant amount of time and/or money.
Built on the familiar, all-in-one collaborative experience of Microsoft Teams, Teams Premium brings the latest technologies, including Large Language Models powered by OpenAI’s GPT-3.5, to make meetings more intelligent, personalized, and protected—whether it’s one-on-one, large meetings, virtual appointments, or webinars.
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.”
In this publication, we articulate the critical steps needed to unbundle the learning ecosystem, build core competencies, design learning experiences, curate new opportunities, and rebundle these experiences into coherent pathways. .
Vision
Every learner deserves an unlimited number of unbundled opportunities to explore, engage, and define experiences that advance their progress along a co-designed educational pathway. Each pathway provides equitable and personalized access to stacked learning experiences leading to post-secondary credentials and secure family-sustaining employment. Throughout the journey, supportive coaches focus on helping learners build skills to navigate with agency. In parallel, learners develop foundational skills (literacy, math), technical skills, and durable skills and connect these to challenging co-designed experiences. The breadth and depth of experiences increase over time, and, in partnership, learners and coaches map progress towards reaching community-defined goals. This vision is only enabled by an unbundled learning ecosystem.
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Recommendations
Solutions already exist in the ecosystem and need to be combined and scaled. Funding models (like My Tech High), badging/credentialing at the competency level (like VLACS), coaching models (like Big Thought), and open ecosystems (like NH Learn Everywhere) provide an excellent foundation. Thus, building unbundled systems has already begun but needs systemic changes to become widely available and accepted.
Build a robust competency-based system.
Create a two-way marketplace for unbundled learning.
Implement policy to support credit for out-of-system experiences.
Invest in technology infrastructure for Learning and Employment Records.
Design interoperable badging systems that connect to credentials.
Now is the ideal time for a flexible and competent market leader to emerge and seize this opportunity, delivering personalized and lifelong educational solutions and experiences that meet the needs of a learning-hungry populace.
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Edtech businesses can address this widening skills gap and need for frequent job-switching through those same data-driven ecosystems, which can support the user through their career and leisure activities. For example, a user could sync their profile with their work’s employee portal to receive further professional development. Simultaneously, the technology would support the user during their spare time as they take courses or watch video content ranging from Adobe InDesign to gardening, further refining their skills. And, when it comes time to retire, the user’s trusted ecosystem has a backlog of data to recommend applicable hobbies and community events.
For example, a user could sync their profile with their work’s employee portal to receive further professional development.
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,
