What aspects of teaching should remain human? — from hechingerreport.org by Chris Berdik Even techno optimists hesitate to say teaching is best left to the bots, but there’s a debate about where to draw the line
ATLANTA — Science teacher Daniel Thompson circulated among his sixth graders at Ron Clark Academy on a recent spring morning, spot checking their work and leading them into discussions about the day’s lessons on weather and water. He had a helper: As Thompson paced around the class, peppering them with questions, he frequently turned to a voice-activated AI to summon apps and educational videos onto large-screen smartboards.
When a student asked, “Are there any animals that don’t need water?” Thompson put the question to the AI. Within seconds, an illustrated blurb about kangaroo rats appeared before the class.
Nitta said there’s something “deeply profound” about human communication that allows flesh-and-blood teachers to quickly spot and address things like confusion and flagging interest in real time.
While the traditional model of education is entrenched, emerging technologies like deep learning promise to shake its foundations and usher in an age of personalized, adaptive, and egalitarian education. It is expected to have a significant impact across higher education in several key ways.
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…deep learning introduces adaptivity into the learning process. Unlike a typical lecture, deep learning systems can observe student performance in real-time. Confusion over a concept triggers instant changes to instructional tactics. Misconceptions are identified early and remediated quickly. Students stay in their zone of proximal development, constantly challenged but never overwhelmed. This adaptivity prevents frustration and stagnation.
InstructureCon 24 Conference Notes — from onedtech.philhillaa.com by Glenda Morgan Another solid conference from the market leader, even with unclear roadmap
The new stuff: AI
Instructure rolled out multiple updates and improvements – more than last year. These included many AI-based or focused tools and services as well as some functional improvements. I’ll describe the AI features first.
Sal Khan was a surprise visitor to the keynote stage to announce the September availability of the full suite of AI-enabled Khanmigo Teacher Tools for Canvas users. The suite includes 20 tools, such as tools to generate lesson plans and quiz questions and write letters of recommendation. Next year, they plan to roll out tools for students themselves to use.
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Other AI-based features include.
Discussion tool summaries and AI-generated responses…
The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.
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Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.
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As we approach 2029, the line between physical and virtual learning environments will blur significantly.
Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations. … The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.
Meanwhile, a separate survey of faculty released Thursday by Ithaka S+R, a higher education consulting firm, showcased that faculty—while increasingly familiar with AI—often do not know how to use it in classrooms. Two out of five faculty members are familiar with AI, the Ithaka report found, but only 14 percent said they are confident in their ability to use AI in their teaching. Just slightly more (18 percent) said they understand the teaching implications of generative AI.
“Serious concerns about academic integrity, ethics, accessibility, and educational effectiveness are contributing to this uncertainty and hostility,” the Ithaka report said.
The diverging views about AI are causing friction. Nearly a third of students said they have been warned to not use generative AI by professors, and more than half (59 percent) are concerned they will be accused of cheating with generative AI, according to the Pearson report, which was conducted with Morning Consult and surveyed 800 students.
What teachers want from AI — from hechingerreport.org by Javeria Salman When teachers designed their own AI tools, they built math assistants, tools for improving student writing, and more
An AI chatbot that walks students through how to solve math problems. An AI instructional coach designed to help English teachers create lesson plans and project ideas. An AI tutor that helps middle and high schoolers become better writers.
These aren’t tools created by education technology companies. They were designed by teachers tasked with using AI to solve a problem their students were experiencing.
Over five weeks this spring, about 300 people – teachers, school and district leaders, higher ed faculty, education consultants and AI researchers – came together to learn how to use AI and develop their own basic AI tools and resources. The professional development opportunity was designed by technology nonprofit Playlab.ai and faculty at the Relay Graduate School of Education.
Next-Gen Classroom Observations, Powered by AI — from educationnext.org by Michael J. Petrilli The use of video recordings in classrooms to improve teacher performance is nothing new. But the advent of artificial intelligence could add a helpful evaluative tool for teachers, measuring instructional practice relative to common professional goals with chatbot feedback.
Multiple companies are pairing AI with inexpensive, ubiquitous video technology to provide feedback to educators through asynchronous, offsite observation. It’s an appealing idea, especially given the promise and popularity of instructional coaching, as well as the challenge of scaling it effectively (see “Taking Teacher Coaching To Scale,” research, Fall 2018).
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Enter AI. Edthena is now offering an “AI Coach” chatbot that offers teachers specific prompts as they privately watch recordings of their lessons. The chatbot is designed to help teachers view their practice relative to common professional goals and to develop action plans to improve.
To be sure, an AI coach is no replacement for human coaching.
We need to shift our thinking about GenAI tutors serving only as personal learning tools. The above activities illustrate how these tools can be integrated into contemporary classroom instruction. The activities should not be seen as prescriptive but merely suggestive of how GenAI can be used to promote social learning. Although I specifically mention only one online activity (“Blended Learning”), all can be adapted to work well in online or blended classes to promote social interaction.
Stealth AI — from higherai.substack.com by Jason Gulya (a Professor of English at Berkeley College) talks to Zack Kinzler What happens when students use AI all the time, but aren’t allowed to talk about it?
In many ways, this comes back to one of my general rules: You cannot ban AI in the classroom. You can only issue a gag rule.
And if you do issue a gag rule, then it deprives students of the space they often need to make heads and tails of this technology.
We need to listen to actual students talking about actual uses, and reflecting on their actual feelings. No more abstraction.
In this conversation, Jason Gulya (a Professor of English at Berkeley College) talks to Zack Kinzler about what students are saying about Artificial Intelligence and education.
Welcome to our monthly update for Teams for Education and thank you so much for being part of our growing community! We’re thrilled to share over 20 updates and resources and show them in action next week at ISTELive 24 in Denver, Colorado, US.
… Copilot for Microsoft 365 – Educator features Guided Content Creation
Coming soon to Copilot for Microsoft 365 is a guided content generation experience to help educators get started with creating materials like assignments, lesson plans, lecture slides, and more. The content will be created based on the educator’s requirements with easy ways to customize the content to their exact needs. Standards alignment and creation Quiz generation through Copilot in Forms Suggested AI Feedback for Educators Teaching extension
To better support educators with their daily tasks, we’ll be launching a built-in Teaching extension to help guide them through relevant activities and provide contextual, educator-based support in Copilot. Education data integration
Copilot for Microsoft 365 – Student features Interactive practice experiences
Flashcards activity
Guided chat activity Learning extension in Copilot for Microsoft 365
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New AI tools for Google Workspace for Education — from blog.google by Akshay Kirtikar and Brian Hendricks We’re bringing Gemini to teen students using their school accounts to help them learn responsibly and confidently in an AI-first future, and empowering educators with new tools to help create great learning experiences.
We have to provide instructors the support they need to leverage educational technologies like generative AI effectively in the service of learning. Given the amount of benefit that could accrue to students if powerful tools like generative AI were used effectively by instructors, it seems unethical not to provide instructors with professional development that helps them better understand how learning occurs and what effective teaching looks like. Without more training and support for instructors, the amount of student learning higher education will collectively “leave on the table” will only increase as generative AI gets more and more capable. And that’s a problem.
From DSC: As is often the case, David put together a solid posting here. A few comments/reflections on it:
I agree that more training/professional development is needed, especially regarding generative AI. This would help achieve a far greater ROI and impact.
The pace of change makes it difficult to see where the sand is settling…and thus what to focus on
The Teaching & Learning Groups out there are also trying to learn and grow in their knowledge (so that they can train others)
The administrators out there are also trying to figure out what all of this generative AI stuff is all about; and so are the faculty members. It takes time for educational technologies’ impact to roll out and be integrated into how people teach.
As we’re talking about multiple disciplines here, I think we need more team-based content creation and delivery.
There needs to be more research on how best to use AI — again, it would be helpful if the sand settled a bit first, so as not to waste time and $$. But then that research needs to be piped into the classrooms far better. .
From DSC: Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.
LearnLM is our new family of models fine-tuned for learning, and grounded in educational research to make teaching and learning experiences more active, personal and engaging.
We often talk about what Generative AI will do for coders, healthcare, science or even finance, but what about the benefits for the next generation? Permit me if you will, here I’m thinking about teachers and students.
It’s no secret that some of the most active users of ChatGPT in its heyday, were students. But how are other major tech firms thinking about this?
I actually think one of the best products with the highest ceiling from Google I/O 2024 is LearnLM. It has to be way more than a chatbot, it has to feel like a multimodal tutor. I can imagine frontier model agents (H) doing this fairly well.
What if everyone, everywhere could have their own personal AI tutor, on any topic?
ChatGPT4o Is the TikTok of AI Models — from nickpotkalitsky.substack.com by Nick Potkalitsky In Search of Better Tools for AI Access in K-12 Classrooms
Nick makes the case that we should pause on the use of OpenAI in the classrooms:
In light of these observations, it’s clear that we must pause and rethink the use of OpenAI products in our classrooms, except for rare cases where accessibility needs demand it. The rapid consumerization of AI, epitomized by GPT4o’s transformation into an AI salesperson, calls for caution.
[On 5/21/24] at Microsoft Build, Microsoft and Khan Academy announced a new partnership that aims to bring these time-saving and lesson-enhancing AI tools to millions of educators. By donating access to Azure AI-optimized infrastructure, Microsoft is enabling Khan Academy to offer all K-12 educators in the U.S. free access to the pilot of Khanmigo for Teachers, which will now be powered by Azure OpenAI Service.
The two companies will also collaborate to explore opportunities to improve AI tools for math tutoring in an affordable, scalable and adaptable way with a new version of Phi-3, a family of small language models (SLMs) developed by Microsoft.
Khan Academy’s AI assistant, Khanmigo, has earned praise for helping students to understand and practice everything from math to English, but it can also help teachers devise lesson plans, formulate questions about assigned readings, and even generate reading passages appropriate for students at different levels. More than just a chatbot, the software offers specific AI-powered tools for generating quizzes and assignment instructions, drafting lesson plans, and formulating letters of recommendation.
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Having a virtual teaching assistant is especially valuable in light of recent research from the RAND Corporation that found teachers work longer hours than most working adults, which includes administrative and prep work outside the classroom.
AI’s New Conversation Skills Eyed for Education — from insidehighered.com by Lauren Coffey The latest ChatGPT’s more human-like verbal communication has professors pondering personalized learning, on-demand tutoring and more classroom applications.
ChatGPT’s newest version, GPT-4o ( the “o” standing for “omni,” meaning “all”), has a more realistic voice and quicker verbal response time, both aiming to sound more human. The version, which should be available to free ChatGPT users in coming weeks—a change also hailed by educators—allows people to interrupt it while it speaks, simulates more emotions with its voice and translates languages in real time. It also can understand instructions in text and images and has improved video capabilities.
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Ajjan said she immediately thought the new vocal and video capabilities could allow GPT to serve as a personalized tutor. Personalized learning has been a focus for educators grappling with the looming enrollment cliff and for those pushing for student success.
There’s also the potential for role playing, according to Ajjan. She pointed to mock interviews students could do to prepare for job interviews, or, for example, using GPT to play the role of a buyer to help prepare students in an economics course.
Generative AI is fundamentally changing how we’re approaching learning and education, enabling powerful new ways to support educators and learners. It’s taking curiosity and understanding to the next level — and we’re just at the beginning of how it can help us reimagine learning.
Today we’re introducing LearnLM: our new family of models fine-tuned for learning, based on Gemini.
On YouTube, a conversational AI tool makes it possible to figuratively “raise your hand” while watching academic videos to ask clarifying questions, get helpful explanations or take a quiz on what you’ve been learning. This even works with longer educational videos like lectures or seminars thanks to the Gemini model’s long-context capabilities. These features are already rolling out to select Android users in the U.S.
… Learn About is a new Labs experience that explores how information can turn into understanding by bringing together high-quality content, learning science and chat experiences. Ask a question and it helps guide you through any topic at your own pace — through pictures, videos, webpages and activities — and you can upload files or notes and ask clarifying questions along the way.
The Gemini era
A year ago on the I/O stage we first shared our plans for Gemini: a frontier model built to be natively multimodal from the beginning, that could reason across text, images, video, code, and more. It marks a big step in turning any input into any output — an “I/O” for a new generation.
Google is integrating AI into all of its ecosystem: Search, Workspace, Android, etc. In true Google fashion, many features are “coming later this year”. If they ship and perform like the demos, Google will get a serious upper hand over OpenAI/Microsoft.
All of the AI features across Google products will be powered by Gemini 1.5 Pro. It’s Google’s best model and one of the top models. A new Gemini 1.5 Flash model is also launched, which is faster and much cheaper.
Google has ambitious projects in the pipeline. Those include a real-time voice assistant called Astra, a long-form video generator called Veo, plans for end-to-end agents, virtual AI teammates and more.
Google just casually announced Veo, a new rival to OpenAI’s Sora.
It can generate insanely good 1080p video up to 60 seconds.
Today at Google I/O we’re announcing new, powerful ways to get more done in your personal and professional life with Gemini for Google Workspace. Gemini in the side panel of your favorite Workspace apps is rolling out more broadly and will use the 1.5 Pro model for answering a wider array of questions and providing more insightful responses. We’re also bringing more Gemini capabilities to your Gmail app on mobile, helping you accomplish more on the go. Lastly, we’re showcasing how Gemini will become the connective tissue across multiple applications with AI-powered workflows. And all of this comes fresh on the heels of the innovations and enhancements we announced last month at Google Cloud Next.
Google is improving its AI-powered chatbot Gemini so that it can better understand the world around it — and the people conversing with it.
At the Google I/O 2024 developer conference on Tuesday, the company previewed a new experience in Gemini called Gemini Live, which lets users have “in-depth” voice chats with Gemini on their smartphones. Users can interrupt Gemini while the chatbot’s speaking to ask clarifying questions, and it’ll adapt to their speech patterns in real time. And Gemini can see and respond to users’ surroundings, either via photos or video captured by their smartphones’ cameras.
Generative AI in Search: Let Google do the searching for you — from blog.google With expanded AI Overviews, more planning and research capabilities, and AI-organized search results, our custom Gemini model can take the legwork out of searching.
Hello GPT-4o — from openai.com We’re announcing GPT-4o, our new flagship model that can reason across audio, vision, and text in real time.
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Providing inflection, emotions, and a human-like voice
Understanding what the camera is looking at and integrating it into the AI’s responses
Providing customer service
With GPT-4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT-4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.
This demo is insane.
A student shares their iPad screen with the new ChatGPT + GPT-4o, and the AI speaks with them and helps them learn in *realtime*.
Imagine giving this to every student in the world.
OpenAI rolls out Memory feature for ChatGPT
OpenAI has introduced a cool update for ChatGPT (rolling out to paid and free users – but not in the EU or Korea), enabling the AI to remember user-specific details across sessions. This memory feature enhances personalization and efficiency, making your interactions with ChatGPT more relevant and engaging.
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Key Features
Automatic Memory Tracking
ChatGPT now automatically records information from your interactions such as preferences, interests, and plans. This allows the AI to refine its responses over time, making each conversation increasingly tailored to you.
Enhanced Personalization
The more you interact with ChatGPT, the better it understands your needs and adapts its responses accordingly. This personalization improves the relevance and efficiency of your interactions, whether you’re asking for daily tasks or discussing complex topics.
Memory Management Options
You have full control over this feature. You can view what information is stored, toggle the memory on or off, and delete specific data or all memory entries, ensuring your privacy and preferences are respected.
Memory is now available to all ChatGPT Plus users. Using Memory is easy: just start a new chat and tell ChatGPT anything you’d like it to remember.
Memory can be turned on or off in settings and is not currently available in Europe or Korea. Team, Enterprise, and GPTs to come. pic.twitter.com/mlt9vyYeMK
From DSC: The ability of AI-based applications to remember things about us will have major and positive ramifications for us when we think about learning-related applications of AI.
Last week a behemoth of a paper was released by AI researchers in academia and industry on the ethics of advanced AI assistants.
It’s one of the most comprehensive and thoughtful papers on developing transformative AI capabilities in socially responsible ways that I’ve read in a while. And it’s essential reading for anyone developing and deploying AI-based systems that act as assistants or agents — including many of the AI apps and platforms that are currently being explored in business, government, and education.
The paper — The Ethics of Advanced AI Assistants— is written by 57 co-authors representing researchers at Google Deep Mind, Google Research, Jigsaw, and a number of prominent universities that include Edinburgh University, the University of Oxford, and Delft University of Technology. Coming in at 274 pages this is a massive piece of work. And as the authors persuasively argue, it’s a critically important one at this point in AI development.
Key questions for the ethical and societal analysis of advanced AI assistants include:
What is an advanced AI assistant? How does an AI assistant differ from other kinds of AI technology?
What capabilities would an advanced AI assistant have? How capable could these assistants be?
What is a good AI assistant? Are there certain values that we want advanced AI assistants to evidence across all contexts?
Are there limits on what AI assistants should be allowed to do? If so, how are these limits determined?
What should an AI assistant be aligned with? With user instructions, preferences, interests, values, well-being or something else?
What issues need to be addressed for AI assistants to be safe? What does safety mean for this class of technologies?
What new forms of persuasion might advanced AI assistants be capable of? How can we ensure that users remain appropriately in control of the technology?
How can people – especially vulnerable users – be protected from AI manipulation and unwanted disclosure of personal information?
Is anthropomorphism for AI assistants morally problematic? If so, might it still be permissible under certain conditions?
AI Resources and Teaching | Kent State University offers valuable resources for educators interested in incorporating artificial intelligence (AI) into their teaching practices. The university recognizes that the rapid emergence of AI tools presents both challenges and opportunities in higher education.
The AI Resources and Teaching page provides educators with information and guidance on various AI tools and their responsible use within and beyond the classroom. The page covers different areas of AI application, including language generation, visuals, videos, music, information extraction, quantitative analysis, and AI syllabus language examples.
For all its jaw-dropping power, Watson the computer overlord was a weak teacher. It couldn’t engage or motivate kids, inspire them to reach new heights or even keep them focused on the material — all qualities of the best mentors.
It’s a finding with some resonance to our current moment of AI-inspired doomscrolling about the future of humanity in a world of ascendant machines. “There are some things AI is actually very good for,” Nitta said, “but it’s not great as a replacement for humans.”
His five-year journey to essentially a dead-end could also prove instructive as ChatGPT and other programs like it fuel a renewed, multimillion-dollar experiment to, in essence, prove him wrong.
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To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”
Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”
From DSC: This is why the vision that I’ve been tracking and working on has always said that HUMAN BEINGS will be necessary — they are key to realizing this vision. Along these lines, here’s a relevant quote:
Another crucial component of a new learning theory for the age of AI would be the cultivation of “blended intelligence.” This concept recognizes that the future of learning and work will involve the seamless integration of human and machine capabilities, and that learners must develop the skills and strategies needed to effectively collaborate with AI systems. Rather than viewing AI as a threat to human intelligence, a blended intelligence approach seeks to harness the complementary strengths of humans and machines, creating a symbiotic relationship that enhances the potential of both.
Per Alexander “Sasha” Sidorkin, Head of the National Institute on AI in Society at California State University Sacramento.
I’ve spent months talking with founders, investors, and scientists, trying to understand what this technology is and who the players are. Today, I’m going to share my findings. I’ll cover:
What an AI agent is
The major players
The technical bets
The future
Agentic workflows are loops—they can run many times in a row without needing a human involved for each step in the task. A language model will make a plan based on your prompt, utilize tools like a web browser to execute on that plan, ask itself if that answer is right, and close the loop by getting back to you with that answer.
But agentic workflows are an architecture, not a product. It gets even more complicated when you incorporate agents into products that customers will buy.
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Early reports of GPT-5 are that it is “materially better” and is being explicitly prepared for the use case of AI agents.
