1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:
2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?
Explain This Design…
Show Me Alternatives…
Challenge My Assumptions…
Learning Science Insights…
By reimagining the role of AI in this way, we would…
OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.
I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.
As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?
This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?
The Tutoring Revolution— from educationnext.org by Holly Korbey More families are seeking one-on-one help for their kids. What does that tell us about 21st-century education?
Recent research suggests that the number of students seeking help with academics is growing, and that over the last couple of decades, more families have been turning to tutoring for that help.
…
What the Future Holds Digital tech has made private tutoring more accessible, more efficient, and more affordable. Students whose families can’t afford to pay $75 an hour at an in-person center can now log on from home to access a variety of online tutors, including Outschool, Wyzant, and Anchorbridge, and often find someone who can cater to their specific skills and needs—someone who can offer help in French to a student with ADHD, for example. Online tutoring is less expensive than in-person programs. Khan Academy’s Khanmigo chatbot can be a student’s virtual AI tutor, no Zoom meeting required, for $4 a month, and nonprofits like Learn to Be work with homeless shelters and community centers to give virtual reading and math tutoring free to kids who can’t afford it and often might need it the most.
Employers Say Students Need AI Skills. What If Students Don’t Want Them? — from insidehighered.com by Ashley Mowreader Colleges and universities are considering new ways to incorporate generative AI into teaching and learning, but not every student is on board with the tech yet. Experts weigh in on the necessity of AI in career preparation and higher education’s role in preparing students for jobs of the future.
Among the 5,025-plus survey respondents, around 2 percent (n=93), provided free responses to the question on AI policy and use in the classroom. Over half (55) of those responses were flat-out refusal to engage with AI. A few said they don’t know how to use AI or are not familiar with the tool, which impacts their ability to apply appropriate use to coursework.
But as generative AI becomes more ingrained into the workplace and higher education, a growing number of professors and industry experts believe this will be something all students need, in their classes and in their lives beyond academia.
From DSC: I used to teach a Foundations of Information Technology class. Some of the students didn’t want to be there as they began the class, as it was a required class for non-CS majors. But after seeing what various applications and technologies could do for them, a good portion of those same folks changed their minds. But not all. Some students (2% sounds about right) asserted that they would never use technologies in their futures. Good luck with that I thought to myself. There’s hardly a job out there that doesn’t use some sort of technology.
And I still think that today — if not more so. If students want good jobs, they will need to learn how to use AI-based tools and technologies. I’m not sure there’s much of a choice. And I don’t think there’s much of a choice for the rest of us either — whether we’re still working or not.
So in looking at the title of the article — “Employers Say Students Need AI Skills. What If Students Don’t Want Them?” — those of us who have spent any time working within the world of business already know the answer.
#Reinvent #Skills #StayingRelevant #Surviving #Workplace + several other categories/tags apply.
For those folks who have tried AI:
Skills: However, genAI may also be helpful in building skills to retain a job or secure a new one. People who had used genAI tools were more than twice as likely to think that these tools could help them learn new skills that may be useful at work or in locating a new job. Specifically, among those who had not used genAI tools, 23 percent believed that these tools might help them learn new skills, whereas 50 percent of those who had used the tools thought they might be helpful in acquiring useful skills (a highly statistically significant difference, after controlling for demographic traits).
Duolingo’s new Video Call feature represents a leap forward in language practice for learners. This AI-powered tool allows Duolingo Max subscribers to engage in spontaneous, realistic conversations with Lily, one of Duolingo’s most popular characters. The technology behind Video Call is designed to simulate natural dialogue and provides a personalized, interactive practice environment. Even beginner learners can converse in a low-pressure environment because Video Call is designed to adapt to their skill level. By offering learners the opportunity to converse in real-time,Video Call builds the confidence needed to communicate effectively in real-world situations. Video Call is available for Duolingo Max subscribers learning English, Spanish, and French.
Ello, the AI reading companion that aims to support kids struggling to read, launched a new product on Monday that allows kids to participate in the story-creation process.
Called “Storytime,” the new AI-powered feature helps kids generate personalized stories by picking from a selection of settings, characters, and plots. For instance, a story about a hamster named Greg who performed in a talent show in outer space.
On Tuesday, Workera announced Sage, an AI agent you can talk with that’s designed to assess an employee’s skill level, goals, and needs. After taking some short tests, Workera claims Sage will accurately gauge how proficient someone is at a certain skill. Then, Sage can recommend the appropriate online courses through Coursera, Workday, or other learning platform partners.Through chatting with Sage, Workera is designed to meet employees where they are, testing their skills in writing, machine learning, or math, and giving them a path to improve.
Giving ELA Lessons a Little Edtech Boost — from edutopia.org by Julia Torres Common activities in English language arts classes such as annotation and note-taking can be improved through technology.
6 ELA Practices That Can Be Enhanced by EdTech
Book clubs.
Collective note-taking.
Comprehension checks.
Video lessons.
..and more
Using Edtech Tools to Differentiate Learning— from edutopia.org by Katie Novak and Mary E. Pettit Teachers can use tech tools to make it easier to give students choice about their learning, increasing engagement.
People started discussing what they could do with Notebook LM after Google launched the audio overview, where you can listen to 2 hosts talking in-depth about the documents you upload. Here are what it can do:
Summarization: Automatically generate summaries of uploaded documents, highlighting key topics and suggesting relevant questions.
Question Answering: Users can ask NotebookLM questions about their uploaded documents, and answers will be provided based on the information contained within them.
Idea Generation: NotebookLM can assist with brainstorming and developing new ideas.
Source Grounding: A big plus against AI chatbot hallucination, NotebookLM allows users to ground the responses in specific documents they choose.
…plus several other items
The posting also lists several ideas to try with NotebookLM such as:
Idea 2: Study Companion
Upload all your course materials and ask NotebookLM to turn them into Question-and-Answer format, a glossary, or a study guide.
Get a breakdown of the course materials to understand them better.
“Google’s AI note-taking app NotebookLM can now explain complex topics to you out loud”
With more immersive text-to-video and audio products soon available and the rise of apps like Suno AI, how we “experience” Generative AI is also changing from a chatbot of 2 years ago, to a more multi-modal educational journey. The AI tools on the research and curation side are also starting to reflect these advancements.
1. Upload a variety of sources for NotebookLM to use.
You can use …
websites
PDF files
links to websites
any text you’ve copied
Google Docs and Slides
even Markdown
You can’t link it to YouTube videos, but you can copy/paste the transcript (and maybe type a little context about the YouTube video before pasting the transcript).
2. Ask it to create resources. 3. Create an audio summary. 4. Chat with your sources.
5. Save (almost) everything.
I finally tried out Google’s newly-announced NotebookLM generative AI application. It provides a set of LLM-powered tools to summarize documents. I fed it my dissertation, and am surprised at how useful the output would be.
The most impressive tool creates a podcast episode, complete with dual hosts in conversation about the document. First – these are AI-generated hosts. Synthetic voices, speaking for synthetic hosts. And holy moly is it effective. Second – although I’d initially thought the conversational summary would be a dumb gimmick, it is surprisingly powerful.
4 Tips for Designing AI-Resistant Assessments — from techlearning.com by Steve Baule and Erin Carter As AI continues to evolve, instructors must modify their approach by designing meaningful, rigorous assessments.
As instructors work through revising assessments to be resistant to generation by AI tools with little student input, they should consider the following principles:
Incorporate personal experiences and local content into assignments
Ask students for multi-modal deliverables
Assess the developmental benchmarks for assignments and transition assignments further up Bloom’s Taxonomy
He added that he wants to avoid a global “AI divide” and that Google is creating a $120 million Global AI Opportunity Fund through which it will “make AI education and training available in communities around the world” in partnership with local nonprofits and NGOs.
Google on Thursday announced new updates to its AI note-taking and research assistant, NotebookLM, allowing users to get summaries of YouTube videos and audio files and even create sharable AI-generated audio discussions…
As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.
This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.
Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education
The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.
AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.
This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.
My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?
Here’s where we are in September, 2024:
…
Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby, Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)
As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.
AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.
From DSC: Anyone who is involved in putting on conferences should at least be aware that this kind of thing is now possible!!! Check out the following posting from Adobe (with help from Tata Consultancy Services (TCS).
This year, the organizers — innovative industry event company Beyond Ordinary Events — turned to Tata Consultancy Services (TCS) to make the impossible “possible.” Leveraging Adobe generative AI technology across products like Adobe Premiere Pro and Acrobat, they distilled hours of video content in minutes, delivering timely dispatches to thousands of attendees throughout the conference.
…
For POSSIBLE ’24, Muche had an idea for a daily dispatch summarizing each day’s sessions so attendees wouldn’t miss a single insight. But timing would be critical. The dispatch needed to reach attendees shortly after sessions ended to fuel discussions over dinner and carry the excitement over to the next day.
The workflow started in Adobe Premiere Pro, with the writer opening a recording of each session and using the Speech to Text feature to automatically generate a transcript. They saved the transcript as a PDF file and opened it in Adobe Acrobat Pro. Then, using Adobe Acrobat AI Assistant, the writer asked for a session summary.
It was that fast and easy. In less than four minutes, one person turned a 30-minute session into an accurate, useful summary ready for review and publication.
By taking advantage of templates, the designer then added each AI-enabled summary to the newsletter in minutes. With just two people and generative AI technology, TCS accomplished the impossible — for the first time delivering an informative, polished newsletter to all 3,500 conference attendees just hours after the last session of the day.
Right now, high schoolers and college students around the country are experimenting with free smartphone apps that help complete their math homework using generative AI. One of the most popular options on campus right now is the Gauth app, with millions of downloads. It’s owned by ByteDance, which is also TikTok’s parent company.
The Gauth app first launched in 2019 with a primary focus on mathematics, but soon expanded to other subjects as well, like chemistry and physics. It’s grown in relevance, and neared the top of smartphone download lists earlier this year for the education category. Students seem to love it. With hundreds of thousands of primarily positive reviews, Gauth has a favorable 4.8 star rating in the Apple App Store and Google Play Store.
All students have to do after downloading the app is point their smartphone at a homework problem, printed or handwritten, and then make sure any relevant information is inside of the image crop. Then Gauth’s AI model generates a step-by-step guide, often with the correct answer.
From DSC: I do hesitate to post this though, as I’ve seen numerous posting re: the dubious quality of AI as it relates to giving correct answers to math-related problems – or whether using AI-based tools help or hurt the learning process. The situation seems to be getting better, but as I understand it, we still have some progress to make in this area of mathematics.
Educational leaders must reconsider the definition of creativity, taking into account how generative AI tools can be used to produce novel and impactful creative work, similar to how film editors compile various elements into a cohesive, creative whole.
Generative AI democratizes innovation by allowing all students to become creators, expanding access to creative processes that were previously limited and fostering a broader inclusion of diverse talents and ideas in education.
AI-Powered Instructional Design at ASU — from drphilippahardman.substack.com by Dr. Philippa Hardman How ASU’s Collaboration with OpenAI is Reshaping the Role of Instructional Designers
The developments and experiments at ASU provide a fascinating window into two things:
How the world is reimagining learning in the age of AI;
How the role of the instructional designer is changing in the age of AI.
In this week’s blog post, I’ll provide a summary of how faculty, staff and students at ASU are starting to reimagine education in the age of AI, and explore what this means for the instructions designers who work there.
India’s ed-tech unicorn PhysicsWallah is using OpenAI’s GPT-4o to make education accessible to millions of students in India. Recently, the company launched a suite of AI products to ensure that students in Tier 2 & 3 cities can access high-quality education without depending solely on their enrolled institutions, as 85% of their enrollment comes from these areas.
Last year, AIM broke the news of PhysicsWallah introducing ‘Alakh AI’, its suite of generative AI tools, which was eventually launched at the end of December 2023. It quickly gained traction, amassing over 1.5 million users within two months of its release.
What An Agent Is
Agents are computer programs that can autonomously perform tasks, make decisions and interact with humans or other computers. There are many different types of agents, and they are designed to achieve specific goals spanning our lives and nearly every industry, making them an integral and unstoppable part of our future.
Learning: AI agents will transform education by providing personalized learning experiences such as one-to-one tutoring. ChatGPT and other large language models (LLMs) are providing access to all digital knowledge now. An “agent” would act as a more personalized version of an LLM.
The hacking and control of an AI agent could lead to disastrous consequences, affecting privacy, security, the economy and societal stability. Proactive and comprehensive security strategies are essential to mitigate these risks in the future.
86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.
The Post-AI Instructional Designer— from drphilippahardman.substack.com by Dr. Philippa Hardman How the ID role is changing, and what this means for your key skills, roles & responsibilities
Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.
Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.
Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.
The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.
An example way to leverage AI:
How to Leverage AI for Identity Inclusion Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.
Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.
Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.
To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.
Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development.Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.
Change blindness — from oneusefulthing.org by Ethan Mollick 21 months later
I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.
Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:
What are you doing?
Why are you doing it that way?
How could you change that workflow with AI?
Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”
So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.
But as generative AI tools like ChatGPT sweep into mainstream business tools, promising to draft properly-formatted text from simple prompts and the click of a button, new questions are rising about what role writing centers should play — or whether they will be needed in the future.
…
Writing centers need to find a balance between introducing AI into the writing process and keeping the human support that every writer needs, argues Anna Mills, an English instructor at the College of Marin.
AI can serve as a supplement to a human tutor, Mills says. She encourages her students to use MyEssayFeedback, an AI tool that critiques the organization of an essay, the quality of evidence a student has included to support their thesis or the tone of the writing. Such tools can also evaluate research questions or review a student’s writing based on the rubric for the assignment, she says.
From DSC: The above item is simply excellent!!! I love it!
We’re going to see a lot more of the Square, Stripe, Shopify-type startups pop up for agentic AI.
This one is like an AI-human broker.
1) Prompt an AI with a need
2) Give the AI a budget (real money)
3) AI turns need into plan with tasks
4) AI finds humans to complete the… https://t.co/UXf1bNZ4AK
3 new Chrome AI features for even more helpful browsing — from blog.google from Parisa Tabriz See how Chrome’s new AI features, including Google Lens for desktop and Tab compare, can help you get things done more easily on the web.
On speaking to AI — from oneusefulthing.org by Ethan Mollick Voice changes a lot of things
So, let’s talk about ChatGPT’s new Advanced Voice mode and the new AI-powered Siri. They are not just different approaches to talking to AI. In many ways, they represent the divide between two philosophies of AI – Copilots versus Agents, small models versus large ones, specialists versus generalists.
1. Flux, an open-source text-to-image creator that is comparable to industry leaders like Midjourney, was released by Black Forest Labs (the “original team” behind Stable Diffusion). It is capable of generating high quality text in images (there are tons of educational use cases). You can play with it on their demo page, on Poe, or by running it on your own computer (tutorial here).
Other items re: Flux:
How to FLUX — from heatherbcooper.substack.com by Heather Cooper Where to use FLUX online & full tutorial to create a sleek ad in minutes
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Also from Heather Cooper:
Introducing FLUX: Open-Source text to image model
FLUX… has been EVERYWHERE this week, as I’m sure you have seen. Developed by Black Forest Labs, is an open-source image generation model that’s gaining attention for its ability to rival leading models like Midjourney, DALL·E 3, and SDXL.
What sets FLUX apart is its blend of creative freedom, precision, and accessibility—it’s available across multiple platforms and can be run locally.
Why FLUX Matters
FLUX’s open-source nature makes it accessible to a broad audience, from hobbyists to professionals.
It offers advanced multimodal and parallel diffusion transformer technology, delivering high visual quality, strong prompt adherence, and diverse outputs.
It’s available in 3 models:
FLUX.1 [pro]: A high-performance, commercial image synthesis model.
FLUX.1 [dev]: An open-weight, non-commercial variant of FLUX.1 [pro]
FLUX.1 [schnell]: A faster, distilled version of FLUX.1, operating up to 10x quicker.
During the weekend, image models made a comeback. Recently released Flux models can create realistic images with near-perfect text—straight from the model, without much patchwork. To get the party going, people are putting these images into video generation models to create pretty–trippy–videos. I can’t identify half of them as AI, and they’ll only get better. See this tutorial on how to create a video ad for your product..
