experimentation

How to do school with NotebookLM:

1. Record audio from class on your phone
2. Keep laptop closed. Just jot down short phrases to describe most important points
3. Upload audio and PDF scan of notes to NotebookLM
4. Ask Notebook to expand your notes with details from recording… pic.twitter.com/wfmCTJfRba

— Steven Johnson (@stevenbjohnson) September 26, 2024

Unlock deeper insights with NotebookLM: Now analyze YouTube videos & audio files alongside your docs. Plus, easily share your Audio Overview with a new sharing option!

Learn more: https://t.co/j1da9565aZ pic.twitter.com/9sULXX5Jud

— labs.google (@labsdotgoogle) September 26, 2024

According to Notebook LM on this Future U podcast — Searching for Fit: The Impacts of AI in Higher Ed — here are some excerpts from the generated table of contents:

Part 1: Setting the Stage

I. Introduction (0:00 – 6:16): …
II. Historical Contextualization (6:16 – 11:30): …
III. The Role of Product Fit in AI’s Impact (11:30 – 17:10): …
IV. AI and the Future of Knowledge Work (17:10 – 24:03): …
V. Teaching About AI in Higher Ed: A Measured Approach (24:03 – 34:20): …
VI. AI & the Evolving Skills Landscape (34:20 – 44:35): …
VII. Ethical & Pedagogical Considerations in an AI-Driven World (44:35 – 54:03):…
VIII. AI Beyond the Classroom: Administrative Applications & the Need for Intuition (54:03 – 1:04:30): …
IX. Reflections & Future Directions (1:04:30 – 1:11:15): ….

Part 2: Administrative Impacts & Looking Ahead

X. Bridging the Conversation: From Classroom to Administration (1:11:15 – 1:16:45): …
XI. The Administrative Potential of AI: A Looming Transformation (1:16:45 – 1:24:42): …
XII. The Need for Intuitiveness & the Importance of Real-World Applications (1:24:42 – 1:29:45): …
XIII. Looking Ahead: From Hype to Impactful Integration (1:29:45 – 1:34:25): …
XIV. Conclusion and Call to Action (1:34:25 – 1:36:03): …

The future of language learning — from medium.com by Sami Tatar

Most language learners do not have access to affordable 1:1 tutoring, which is also proven to be the most effective way to learn (short of moving to a specific country for complete immersion). Meanwhile, language learning is a huge market, and with an estimated 60% of this still dominated by “offline” solutions, meaning it is prime for disruption and never more so than with the opportunities unlocked through AI powered language learning. Therefore — we believe this presents huge opportunities for new startups creating AI native products to create the next language learning unicorns.

I never imagined I’d learn so much without paying for a course.

Here are 8 ChatGPT-4 prompts I wish I’d found sooner: pic.twitter.com/b9gqEGInSd

— Ryan Hart ? (@thisdudelikesAI) October 5, 2024

“The Broken Mirror: Rethinking Education, AI, and Equity in America’s Classrooms” — from nickpotkalitsky.substack.com by JC Price

It’s not that AI is inherently biased, but in its current state, it favors those who can afford it. The wealthy districts continue to pull ahead, leaving schools without resources further behind. Students in these underserved areas aren’t just being deprived of technology—they’re being deprived of the future.

But imagine a different world—one where AI doesn’t deepen the divide, but helps to bridge it. Technology doesn’t have to be the luxury of the wealthy. It can be a tool for every student, designed to meet them where they are. Adaptive AI systems, integrated into schools regardless of their budget, can provide personalized learning experiences that help students catch up and push forward, all while respecting the limits of their current infrastructure. This is where AI’s true potential lies—not in widening the gap, but in leveling the field.

But imagine if, instead of replacing teachers, AI helped to support them. Picture a world where teachers are freed from the administrative burdens that weigh them down. Where AI systems handle the logistics, so teachers can focus on what they do best—teaching, mentoring, and inspiring the next generation. Professional development could be personalized, helping teachers integrate AI into their classrooms in ways that enhance their teaching, without adding to their workload. This is the future we should be striving toward—one where technology serves to lift up educators, not push them out.

Duolingo Introduces AI-Powered Innovations at Duocon 2024 + an AI-based reading coach

On 10/05/2024, in 21st century, 24x7x365 access, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, engagement / engaging students, experimentation, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, languages and translation, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, lifelong learning, multimedia, Natural Language Processing (NLP), online learning, online media, online tutoring, personalized/customized learning, platforms, reading, skills, student-related, tools, United States, usability, user experience (UX), user interface design, vendors, videoconferencing, Virtual Reality (VR) / worlds / learning, virtual tutoring, vision/possibilities, voice recognition / voice enabled interfaces, writing, by Daniel Christian

Duolingo Introduces AI-Powered Innovations at Duocon 2024 — from investors.duolingo.com; via Claire Zau

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.

And here’s another AI-based learning item:

AI reading coach startup Ello now lets kids create their own stories — from techcrunch.com by Lauren Forristal; via Claire Zau

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.

Walt Disney’s Wisdom: Lessons for Learning & Development Leaders [Kelly]

On 10/05/2024, in adult learning, business, corporate / business world, corporate universities / corporate training, experimentation, innovation, learning ecosystem, lifelong learning, workplace, by Daniel Christian

Walt Disney’s Wisdom: Lessons for Learning & Development Leaders — from learningguild.com by David Kelly

Here are a few of my favorite [quotes], along with the valuable lessons they offer us in Learning and Development.

“Everyone has deadlines.”
“I believe in being an innovator.”
“Times and conditions change so rapidly that we must keep our aim constantly focused on the future.
“I can never stand still. I must explore and experiment.”
…and several other quotes.

Helping Neurodiverse Students Learn Through New Classroom Design — from insidehighered.com by Michael Tyre
Michael Tyre offers some insights into how architects and administrators can work together to create better learning environments for everyone.

We emerged with two guiding principles. First, we had learned that certain environments—in particular, those that cause sensory distraction—can more significantly impact neurodivergent users. Therefore, our design should diminish distractions by mitigating, when possible, noise, visual contrast, reflective surfaces and crowds. Second, we understood that we needed a design that gave neurodivergent users the agency of choice.

The importance of those two factors—a dearth of distraction and an abundance of choice—was bolstered in early workshops with the classroom committee and other stakeholders, which occurred at the same time we were conducting our research. Some things didn’t come up in our research but were made quite clear in our conversations with faculty members, students from the neurodivergent community and other stakeholders. That feedback greatly influenced the design of the Young Classroom.

We ended up blending the two concepts. The main academic space utilizes traditional tables and chairs, albeit in a variety of heights and sizes, while the peripheral classroom spaces use an array of less traditional seating and table configurations, similar to the radical approach.

On a somewhat related note, also see:

Unpacking Fingerprint Culture — from marymyatt.substack.com by Mary Myatt

This post summarises a fascinating webinar I had with Rachel Higginson discussing the elements of building belonging in our settings.

We know that belonging is important and one of the ways to make this explicit in our settings is to consider what it takes to cultivate an inclusive environment where each individual feels valued and understood.

Rachel has spent several years working with young people, particularly those on the periphery of education to help them back into mainstream education and participating in class, along with their peers.

Rachel’s work helping young people to integrate back into education resulted in schools requesting support and resources to embed inclusion within their settings. As a result, Finding My Voice has evolved into a broader curriculum development framework.

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.

3 UDL-Aligned EdTech Tools

Digital audiobook platforms.
Multimedia presentation tools.
Digital annotation tools.

Democrats and Republicans Agree Teacher Prep Needs to Change. But How? — from edweek.org by Libby Stanford
The programs have been designed “essentially to mass-produce identical educators,” a teachers college dean told lawmakers

The core problem, witnesses at the hearing said, is that teacher-preparation programs treat all teachers—and, by extension, students—the same, asking teachers to be “everything to everybody.”

“The current model of teaching where one teacher works individually with a group of learners in a classroom—or a small box inside of a larger box that we call school—promotes unrealistic expectations by assuming individual teachers working in isolation can meet the needs of all students,” said Greg Mendez, the principal of Skyline High School in Mesa, Ariz.

From DSC:
I’ve long thought teacher education programs could and should evolve (that’s why I have a “student teacher/teacher education” category on this blog). For example, they should inform their future teachers about the science of learning and how to leverage edtech/emerging technologies into their teaching methods.

But regardless of what happens in our teacher prep programs, the issues about the current PreK-12 learning ecosystem remain — and THOSE things are what we need to address. Or we will continue to see teachers leave the profession.

Are we straight-jacketing our teachers and administrators by having them give so many standardized tests and then having to teach to those tests? (We should require our legislators to teach in a classroom before they can draft any kind of legislation.)
Do teachers have the joy they used to have? The flexibility they used to have? Do students?
Do students have choice and voice?
etc.

Also, I highlighted the above excerpt because we can’t expect a teacher to do it all. They can’t be everything to everybody. It’s a recipe for burnout and depression. There are too many agendas coming at them.

We need to empower our current teachers and listen very carefully to the changes that they recommend. We should also listen very carefully to what our STUDENTS are recommending as well!

This article….

Artificial Intelligence and Schools: When Tech Makers and Educators Collaborate, AI Doesn’t Have to be Scary — from the74million.org by Edward Montalvo
AI is already showing us how to make education more individualized and equitable.

The XQ Institute shares this mindset as part of our mission to reimagine the high school learning experience so it’s more relevant and engaging for today’s learners, while better preparing them for the future. We see AI as a tool with transformative potential for educators and makers to leverage — but only if it’s developed and implemented with ethics, transparency and equity at the forefront. That’s why we’re building partnerships between educators and AI developers to ensure that products are shaped by the real needs and challenges of students, teachers and schools. Here’s how we believe all stakeholders can embrace the Department’s recommendations through ongoing collaborations with tech leaders, educators and students alike.

…lead me to the XQ Institute, and I very much like what I’m initially seeing! Here are some excerpts from their website:

Transforming high school isn’t easy, but it is possible. ? Educator @nwallacecxh from XQ’s @CrosstownHigh shares real-world strategies to make learning relevant and meaningful. Ready to see how it’s done? ? https://t.co/xD8hkP33TH

— XQ (@XQAmerica) September 26, 2024

“AI, Humans and Work: 10 Thoughts.” [Tobaccowala] + other items re: AI in general

On 09/23/2024, in Artificial Intelligence/Agents/LLMs/and Related, change, creativity, emerging technologies, engineering, experimentation, future, game-changing environment, generational differences, media/film, Open AI, platforms, robotics, society, tools, United States, vendors, workplace, by Daniel Christian

AI researcher Jim Fan has had a charmed career. He was OpenAI’s first intern before he did his PhD at Stanford with “godmother of AI,” Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI “GEAR” group. The lab’s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a “foundation agent” that can generalize across skills, embodiments and realities—both physical and virtual. He also supports Jensen Huang’s idea that “Everything that moves will eventually be autonomous.”

Runway Partners with Lionsgate — from runwayml.com via The Rundown AI
Runway and Lionsgate are partnering to explore the use of AI in film production.

Lionsgate and Runway have entered into a first-of-its-kind partnership centered around the creation and training of a new AI model, customized on Lionsgate’s proprietary catalog. Fundamentally designed to help Lionsgate Studios, its filmmakers, directors and other creative talent augment their work, the model generates cinematic video that can be further iterated using Runway’s suite of controllable tools.

Per The Rundown: Lionsgate, the film company behind The Hunger Games, John Wick, and Saw, teamed up with AI video generation company Runway to create a custom AI model trained on Lionsgate’s film catalogue.

The details:

The partnership will develop an AI model specifically trained on Lionsgate’s proprietary content library, designed to generate cinematic video that filmmakers can further manipulate using Runway’s tools.
Lionsgate sees AI as a tool to augment and enhance its current operations, streamlining both pre-production and post-production processes.
Runway is considering ways to offer similar custom-trained models as templates for individual creators, expanding access to AI-powered filmmaking tools beyond major studios.

Why it matters: As many writers, actors, and filmmakers strike against ChatGPT, Lionsgate is diving head-first into the world of generative AI through its partnership with Runway. This is one of the first major collabs between an AI startup and a major Hollywood company — and its success or failure could set precedent for years to come.

A bottle of water per email: the hidden environmental costs of using AI chatbots — from washingtonpost.com by Pranshu Verma and Shelly Tan (behind paywall)
AI bots generate a lot of heat, and keeping their computer servers running exacts a toll.

Each prompt on ChatGPT flows through a server that runs thousands of calculations to determine the best words to use in a response.

In completing those calculations, these servers, typically housed in data centers, generate heat. Often, water systems are used to cool the equipment and keep it functioning. Water transports the heat generated in the data centers into cooling towers to help it escape the building, similar to how the human body uses sweat to keep cool, according to Shaolei Ren, an associate professor at UC Riverside.

Where electricity is cheaper, or water comparatively scarce, electricity is often used to cool these warehouses with large units resembling air-conditioners, he said. That means the amount of water and electricity an individual query requires can depend on a data center’s location and vary widely.

AI, Humans and Work: 10 Thoughts. — from rishad.substack.com by Rishad Tobaccowala
The Future Does Not Fit in the Containers of the Past. Edition 215.

10 thoughts about AI, Humans and Work in 10 minutes:

AI is still Under-hyped.
AI itself will be like electricity and is unlikely to be a differentiator for most firms.
AI is not alive but can be thought of as a new species.
Knowledge will be free and every knowledge workers job will change in 2025.
The key about AI is not to ask what AI will do to us but what AI can do for us.
Plus 5 other thoughts

“10 Ways I Use LLMs like ChatGPT as a Professor” [Clay] + other items re: AI in our learning ecosystems

On 09/23/2024, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, career development, change, colleges, community colleges, content development, aggregation, repositories, culture, dangers of the status quo, education technology, emerging technologies, experimentation, faculty/staff, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, learning ecosystem, Learning Experience Design, pace of change, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, tools, United States, universities, vendors, workplace, by Daniel Christian

10 Ways I Use LLMs like ChatGPT as a Professor — from automatedteach.com by Graham Clay
ChatGPT-4o, Gemini 1.5 Pro, Claude 3.5 Sonnet, custom GPTs – you name it, I use it. Here’s how…

Excerpt:

To plan lessons (especially activities)
To create course content (especially quizzes)
To tutor my students
To grade faster and give better feedback
To draft grant applications
Plus 5 other items

From Caution to Calcification to Creativity: Reanimating Education with AI’s Frankenstein Potential — from nickpotkalitsky.substack.com by Nick Potkalitsky
A Critical Analysis of AI-Assisted Lesson Planning: Evaluating Efficacy and Pedagogical Implications

Excerpt (emphasis DSC):

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

NotebookLM and Google’s Multimodal Vision for AI-Powered Learning Tools — from marcwatkins.substack.com by Marc Watkins

A Variety of Use Cases

Create an Interactive Syllabus
Presentation Deep Dive: Upload Your Slides
Note Taking: Turn Your Chalkboard into a Digital Canvas
Explore a Reading or Series of Readings
Help Navigating Feedback
Portfolio Building Blocks

Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform — from er.educause.edu by Fawzi BenMessaoud
The transformative impact of artificial intelligence on educational systems calls for a comprehensive reform to prepare future generations for an AI-integrated world.

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.

How might we build the nation’s new learning ecosystem together? [Getting Smart]

On 09/17/2024, in change, education, education reform, experimentation, future, ideas, innovation, K-12 related, leadership, learning, learning ecosystem, Learning Experience Design, strategy, student-related, teachers, United States, vision/possibilities, youth, by Daniel Christian

Horizon Three Learning — from gettingsmart.com
How might we build the nation’s new learning ecosystem together?

America’s education system was a groundbreaking effort to help a growing nation thrive in the 19th century. Now, 200 years later, the world has changed; the horizon looks drastically different. Collectively, we need to redesign our education system to enable all of our children — and, by extension, our nation — to thrive today and tomorrow.

“Horizon Three” or “H3” names the future-ready system we need, one that is grounded in equity serving learners’ individual strengths and needs as well as the common good. This series provides a glimpse of where H3 is already being designed and built. It also includes provocations about how we might fundamentally reimagine learning for the future ahead.

Today, I’m excited to share with you all the fruit of our effort at @OpenAI to create AI models capable of truly general reasoning: OpenAI’s new o1 model series! (aka ?) Let me explain ? 1/ pic.twitter.com/aVGAkb9kxV

— Noam Brown (@polynoamial) September 12, 2024

Introducing OpenAI o1 – from openai.com

We’ve developed a new series of AI models designed to spend more time thinking before they respond. Here is the latest news on o1 research, product and other updates.

The wait is over. OpenAI has just released GPT-5, now called OpenAI o1.

It brings advanced reasoning capabilities and can generate entire video games from a single prompt.

Think of it as ChatGPT evolving from fast, intuitive thinking (System-1) to deeper, more deliberate… pic.twitter.com/uAMihaUjol

— Lior? (@AlphaSignalAI) September 12, 2024

OpenAI Strawberry (o1) is out! We are finally seeing the paradigm of inference-time scaling popularized and deployed in production. As Sutton said in the Bitter Lesson, there’re only 2 techniques that scale indefinitely with compute: learning & search. It’s time to shift focus to… pic.twitter.com/jTViQucwxr

— Jim Fan (@DrJimFan) September 12, 2024

Something New: On OpenAI’s “Strawberry” and Reasoning — from oneusefulthing.org by Ethan Mollick
Solving hard problems in new ways

The new AI model, called o1-preview (why are the AI companies so bad at names?), lets the AI “think through” a problem before solving it. This lets it address very hard problems that require planning and iteration, like novel math or science questions. In fact, it can now beat human PhD experts in solving extremely hard physics problems.

To be clear, o1-preview doesn’t do everything better. It is not a better writer than GPT-4o, for example. But for tasks that require planning, the changes are quite large.

What is the point of Super Realistic AI? — from Heather Cooper who runs Visually AI on Substack

The arrival of super realistic AI image generation, powered by models like Midjourney, FLUX.1, and Ideogram, is transforming the way we create and use visual content.

Recently, many creators (myself included) have been exploring super realistic AI more and more.

But where can this actually be used?

Super realistic AI image generation will have far-reaching implications across various industries and creative fields. Its importance stems from its ability to bridge the gap between imagination and visual representation, offering multiple opportunities for innovation and efficiency.

Heather goes on to mention applications in:

Creative Industries
Entertainment and Media
Education and Training

NotebookLM now lets you listen to a conversation about your sources — from blog.google by Biao Wang
Our new Audio Overview feature can turn documents, slides, charts and more into engaging discussions with one click.

Today, we’re introducing Audio Overview, a new way to turn your documents into engaging audio discussions. With one click, two AI hosts start up a lively “deep dive” discussion based on your sources. They summarize your material, make connections between topics, and banter back and forth. You can even download the conversation and take it on the go.

Bringing generative AI to video with Adobe Firefly Video Model — from blog.adobe.com by Ashley Still

Over the past several months, we’ve worked closely with the video editing community to advance the Firefly Video Model. Guided by their feedback and built with creators’ rights in mind, we’re developing new workflows leveraging the model to help editors ideate and explore their creative vision, fill gaps in their timeline and add new elements to existing footage.

Just like our other Firefly generative AI models, editors can create with confidence knowing the Adobe Firefly Video Model is designed to be commercially safe and is only trained on content we have permission to use — never on Adobe users’ content.

We’re excited to share some of the incredible progress with you today — all of which is designed to be commercially safe and available in beta later this year. To be the first to hear the latest updates and get access, sign up for the waitlist here.

“Which AI tools do Instructional Designers use the most?” [Hardman] + other items re: AI in our learning ecosystems

On 09/12/2024, in 21st century, accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, biology, colleges, community colleges, corporate universities / corporate training, creativity, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, face-to-face, faculty/staff, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, learning, learning ecosystem, Learning Experience Design, media/film, multimedia, Natural Language Processing (NLP), neurodivergent/special needs, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, voice recognition / voice enabled interfaces, writing, by Daniel Christian

The Most Popular AI Tools for Instructional Design (September, 2024) — from drphilippahardman.substack.com by Dr. Philippa Hardman
The tools we use most, and how we use them

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.

The Impact of AI in Advancing Accessibility for Learners with Disabilities — from er.educause.edu by Rob Gibson

AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.

The Six AI Use Case Families of Instructional Design — from drphilippahardman.substack.com by Dr. Phillipa Harman
Pushing AI beyond content creation

So what are the six families? Here’s the TLDR:

Creative Ideation, aka using AI to spark novel ideas and innovative design concepts.
Research & Analysis, aka using AI to rapidly gather and synthesise information from vast sources.
Data-Driven Insights, aka using AI to extract meaningful patterns and predictions from complex datasets.
…and more

Town Hall: Back to School with AI — from gettingsmart.com

Key Points

AI can help educators focus more on human interaction and critical thinking by automating tasks that consume time but don’t require human empathy or creativity.
Encouraging students to use AI as a tool for learning and creativity can significantly boost their engagement and self-confidence, as seen in examples from student experiences shared in the discussion.

The speakers discuss various aspects of AI, including its potential to augment human intelligence and the need to focus on uniquely human competencies in the face of technological advancements. They also emphasize the significance of student agency, with examples of student-led initiatives and feedback sessions that reveal how young learners are already engaging with AI in innovative ways. The episode underscores the necessity for educators and administrators to stay informed and actively participate in the ongoing dialogue about AI to ensure its effective and equitable implementation in schools.

The video below is from The Artifice of Twinning by Marc Watkins

How AI Knocks Down Classroom Barriers — from gettingsmart.com by Alyssa Faubion

Key Points

AI can be a powerful tool to break down language, interest, and accessibility barriers in the classroom, making learning more inclusive and engaging.
Incorporating AI tools in educational settings can help build essential skills that AI can’t replace, such as creativity and problem-solving, preparing students for future job markets.

Join our linked in group, AI in the Classroom https://t.co/rmfw0SvcW1 #edtech #GenAI @isteofficial @cosn @ascd @neatoday @aftunion @oecd_edu @ccsso @fetc @tcea @cueinc pic.twitter.com/Cxl80WuDuS

— David Ross (@DavidPBLRoss) August 20, 2024

This AI App Can Solve Your Math Homework, Steps Included — from link.wired.com by Will Knight

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.

Redefining Creativity in the Age of AI — from gettingsmart.com by David Ross

Key Points

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:

1. How the world is reimagining learning in the age of AI;
2. 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.

PhysicsWallah’s ‘Alakh AI’ is Making Education Accessible to Millions in India — from analyticsindiamag.com by Siddharth Jindal

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.

7+ items regarding AI in our learning ecosystems

On 08/26/2024, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), business, career development, change, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital audio, digital storytelling, digital video, education technology, emerging technologies, experimentation, faculty/staff, graphics, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, law schools, learning ecosystem, Learning Experience Design, multimedia, music, neurodivergent/special needs, pace of change, productivity / tips and tricks, skills, student-related, teaching & learning, training / L&D, United States, universities, workplace, by Daniel Christian

What Students Want: Key Results from DEC Global AI Student Survey 2024 — from digitaleducationcouncil.com by Digital Education Council

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.

Chatting with WEF about ChatGPT in the classroom — from futureofbeinghuman.com by Andrew Maynard
A short video on generative AI in education from the World Economic Forum

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.

7 Ways to Use AI Music in Your Classroom — from classtechtips.com by Monica Burns

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.

My AI Breakthrough — from mgblog.org by Miguel Guhlin

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.

Learning Ecosystems

Walt Disney’s Wisdom: Lessons for Learning & Development Leaders [Kelly]

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