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“Student Guide to AI”; “AI Isn’t Just Changing How We Work — It’s Changing How We Learn”; + other items re: AI in our LE’s

On 05/12/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, change, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, expectations, experimentation, Facebook / Meta Platforms, faculty/staff, formal learning, future, future of higher education, game-changing environment, generational differences, global / globalization, Google, health, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, immersion, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, learning preferences, learning spaces, media/film, Microsoft, Mixed Reality (MR), multimedia, new media literacies, online media, online tutoring, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, skills, society, staying relevant, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), user interface design, vendors, vision/possibilities, voice recognition / voice enabled interfaces, wearables, workplace, XR - extended reality, youth, by Daniel Christian

.Get the 2025 Student Guide to Artificial Intelligence — from studentguidetoai.org
This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U).
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AI Isn’t Just Changing How We Work — It’s Changing How We Learn — from entrepreneur.com by Aytekin Tank; edited by Kara McIntyre
AI agents are opening doors to education that just a few years ago would have been unthinkable. Here’s how.

Agentic AI is taking these already huge strides even further. Rather than simply asking a question and receiving an answer, an AI agent can assess your current level of understanding and tailor a reply to help you learn. They can also help you come up with a timetable and personalized lesson plan to make you feel as though you have a one-on-one instructor walking you through the process. If your goal is to learn to speak a new language, for example, an agent might map out a plan starting with basic vocabulary and pronunciation exercises, then progress to simple conversations, grammar rules and finally, real-world listening and speaking practice.
…
For instance, if you’re an entrepreneur looking to sharpen your leadership skills, an AI agent might suggest a mix of foundational books, insightful TED Talks and case studies on high-performing executives. If you’re aiming to master data analysis, it might point you toward hands-on coding exercises, interactive tutorials and real-world datasets to practice with.

The beauty of AI-driven learning is that it’s adaptive. As you gain proficiency, your AI coach can shift its recommendations, challenge you with new concepts and even simulate real-world scenarios to deepen your understanding.

Ironically, the very technology feared by workers can also be leveraged to help them. Rather than requiring expensive external training programs or lengthy in-person workshops, AI agents can deliver personalized, on-demand learning paths tailored to each employee’s role, skill level, and career aspirations. Given that 68% of employees find today’s workplace training to be overly “one-size-fits-all,” an AI-driven approach will not only cut costs and save time but will be more effective.

What’s the Future for AI-Free Spaces? — from higherai.substack.com by Jason Gulya
Please let me dream…

This is one reason why I don’t see AI-embedded classrooms and AI-free classrooms as opposite poles. The bone of contention, here, is not whether we can cultivate AI-free moments in the classroom, but for how long those moments are actually sustainable.

Can we sustain those AI-free moments for an hour? A class session? Longer?
…
Here’s what I think will happen. As AI becomes embedded in society at large, the sustainability of imposed AI-free learning spaces will get tested. Hard. I think it’ll become more and more difficult (though maybe not impossible) to impose AI-free learning spaces on students.

However, consensual and hybrid AI-free learning spaces will continue to have a lot of value. I can imagine classes where students opt into an AI-free space. Or they’ll even create and maintain those spaces.

Duolingo’s AI Revolution — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 148 AI-Generated Courses Tell Us About the Future of Instructional Design & Human Learning

Last week, Duolingo announced an unprecedented expansion: 148 new language courses created using generative AI, effectively doubling their content library in just one year. This represents a seismic shift in how learning content is created — a process that previously took the company 12 years for their first 100 courses.

As CEO Luis von Ahn stated in the announcement, “This is a great example of how generative AI can directly benefit our learners… allowing us to scale at unprecedented speed and quality.”

In this week’s blog, I’ll dissect exactly how Duolingo has reimagined instructional design through AI, what this means for the learner experience, and most importantly, what it tells us about the future of our profession.

Are Mixed Reality AI Agents the Future of Medical Education? — from ehealth.eletsonline.com

Medical education is experiencing a quiet revolution—one that’s not taking place in lecture theatres or textbooks, but with headsets and holograms. At the heart of this revolution are Mixed Reality (MR) AI Agents, a new generation of devices that combine the immersive depth of mixed reality with the flexibility of artificial intelligence. These technologies are not mere flashy gadgets; they’re revolutionising the way medical students interact with complicated content, rehearse clinical skills, and prepare for real-world situations. By combining digital simulations with the physical world, MR AI Agents are redefining what it means to learn medicine in the 21st century.

4 Reasons To Use Claude AI to Teach — from techlearning.com by Erik Ofgang
Features that make Claude AI appealing to educators include a focus on privacy and conversational style.

After experimenting using Claude AI on various teaching exercises, from generating quizzes to tutoring and offering writing suggestions, I found that it’s not perfect, but I think it behaves favorably compared to other AI tools in general, with an easy-to-use interface and some unique features that make it particularly suited for use in education.

“AI agents arrive in US classrooms” [Rajkumar] + other items re: AI in our learning ecosystems

On 04/25/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, creativity, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, personalized/customized learning, podcasting, research, teachers, teaching & learning, trends, UK, United States, universities, vendors, by Daniel Christian

AI agents arrive in US classrooms — from zdnet.com by Radhika Rajkumar
Kira AI’s personalized learning platform is currently being implemented in Tennessee schools. How will it change education?

AI for education is a new but rapidly expanding field. Can it support student outcomes and help teachers avoid burnout?

On Wednesday, AI education company Kira launched a “fully AI-native learning platform” for K-12 education, complete with agents to assist teachers with repetitive tasks. The platform hosts assignments, analyzes progress data, offers administrative assistance, helps build lesson plans and quizzes, and more.

“Unlike traditional tools that merely layer AI onto existing platforms, Kira integrates artificial intelligence directly into every educational workflow — from lesson planning and instruction to grading, intervention, and reporting,” the release explains. “This enables schools to improve student outcomes, streamline operations, and provide personalized support at scale.”

Also relevant/see:

Coursera Founder Andrew Ng’s New Venture Brings A.I. to K–12 Classrooms — from observer.com by Victor Dey
Andrew Ng’s Kira Learning uses A.I. agents to transform K–12 education with tools for teachers, students and administrators.

“Teachers today are overloaded with repetitive tasks. A.I. agents can change that, and free up their time to give more personalized help to students,” Ng said in a statement.

Kira was co-founded by Andrea Pasinetti and Jagriti Agrawal, both longtime collaborators of Ng. The platform embeds A.I. directly into lesson planning, instruction, grading and reporting. Teachers can instantly generate standards-aligned lesson plans, monitor student progress in real time and receive automated intervention strategies when a student falls behind.

Students, in turn, receive on-demand tutoring tailored to their learning styles. A.I. agents adapt to each student’s pace and mastery level, while grading is automated with instant feedback—giving educators time to focus on teaching.

‘Using GenAI is easier than asking my supervisor for support’ — from timeshighereducation.com
Doctoral researchers are turning to generative AI to assist in their research. How are they using it, and how can supervisors and candidates have frank discussions about using it responsibly?

Generative AI is increasingly the proverbial elephant in the supervisory room. As supervisors, you may be concerned about whether your doctoral researchers are using GenAI. It can be a tricky topic to broach, especially when you may not feel confident in understanding the technology yourself.

While the potential impact of GenAI use among undergraduate and postgraduate taught students, especially, is well discussed (and it is increasingly accepted that students and staff need to become “AI literate”), doctoral researchers often slip through the cracks in institutional guidance and policymaking.

AI as a Thought Partner in Higher Education — from er.educause.edu by Brian Basgen

When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.
…
The glaring contrast between the perceived ubiquity of GenAI and its actual use also reveals fundamental challenges associated with the practical application of these tools. This article explores two key questions about GenAI to address common misconceptions and encourage broader adoption and more effective use of these tools in higher education.

AI for Automation or Augmentation of L&D? — from drphilippahardman.substack.com by Dr. Philippa Hardman
An audio summary of my Learning Technologies talk

Like many of you, I spent the first part of this week at Learning Technologies in London, where I was lucky enough to present a session on the current state of AI and L&D.

In this week’s blog post, I summarise what I covered and share an audio summary of my paper for you to check out.

Bridging the AI Trust Gap — from chronicle.com by Ian Wilhelm, Derek Bruff, Gemma Garcia, and Lee Rainie

In a 2024 Chronicle survey, 86 percent of administrators agreed with the statement: “Generative artificial intelligence tools offer an opportunity for higher education to improve how it educates, operates, and conducts research.” In contrast, just 55 percent of faculty agreed, showing the stark divisions between faculty and administrative perspectives on adopting AI.

Among many faculty members, a prevalent distrust of AI persists — and for valid reasons. How will it impact in-class instruction? What does the popularity of generative AI tools portend for the development of critical thinking skills for Gen-Z students? How can institutions, at the administrative level, develop policies to safeguard against students using these technologies as tools for cheating?

Given this increasing ‘trust gap,’ how can faculty and administrators work together to preserve academic integrity as AI seeps into all areas of academia, from research to the classroom?

Join us for “Bridging the AI Trust Gap,” an extended, 75-minute Virtual Forum exploring the trust gap on campus about AI, the contours of the differences, and what should be done about it.

“Age appropriate” AI literacy, the future of AI in education + other items re: AI in our LE’s

On 04/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, cloud-based computing / apps / other cloud-related, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, design, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, learning theories, workplace, by Daniel Christian

What does ‘age appropriate’ AI literacy look like in higher education? — from timeshighereducation.com by Fun Siong Lim
As AI literacy becomes an essential work skill, universities need to move beyond developing these competencies at ‘primary school’ level in their students. Here, Fun Siong Lim reflects on frameworks to support higher-order AI literacies

Like platforms developed at other universities, Project NALA offers a front-end interface (known as the builder) for faculty to create their own learning assistant. An idea we have is to open the builder up to students to allow them to create their own GenAI assistant as part of our AI literacy curriculum. As they design, configure and test their own assistant, they will learn firsthand how generative AI works. They get to test performance-enhancement approaches beyond prompt engineering, such as grounding the learning assistant with curated materials (retrieval-augmented generation) and advanced ideas such as incorporating knowledge graphs.

They should have the opportunity to analyse, evaluate and create responsible AI solutions. Offering students the opportunity to build their own AI assistants could be a way forward to develop these much-needed skills.

How to Use ChatGPT 4o’s Update to Turn Key Insights Into Clear Infographics (Prompts Included) — from evakeiffenheim.substack.com by Eva Keiffenheim
This 3-step workflow helps you break down books, reports, or slide-decks into professional visuals that accelerate understanding.

This article shows you how to find core ideas, prompt GPT-4o3 for a design brief, and generate clean, professional images that stick. These aren’t vague “creative visuals”—they’re structured for learning, memory, and action.

If you’re a lifelong learner, educator, creator, or just someone who wants to work smarter, this process is for you.

You’ll spend less time re-reading and more time understanding. And maybe—just maybe—you’ll build ideas that not only click in your brain, but also stick in someone else’s.

SchoolAI Secures $25 Million to Help Teachers and Schools Reach Every Student — from globenewswire.com
The Classroom Experience platform gives every teacher and student their own AI tools for personalized learning

SchoolAI’s Classroom Experience platform combines AI assistants for teachers that help with classroom preparation and other administrative work, and Spaces–personalized AI tutors, games, and lessons that can adapt to each student’s unique learning style and interests. Together, these tools give teachers actionable insights into how students are doing, and how the teacher can deliver targeted support when it matters most.

“Teachers and schools are navigating hard challenges with shrinking budgets, teacher shortages, growing class sizes, and ongoing recovery from pandemic-related learning gaps,” said Caleb Hicks, founder and CEO of SchoolAI. “It’s harder than ever to understand how every student is really doing. Teachers deserve powerful tools to help extend their impact, not add to their workload. This funding helps us double down on connecting the dots for teachers and students, and later this year, bringing school administrators and parents at home onto the platform as well.”

AI in Education, Part 3: Looking Ahead – The Future of AI in Learning — from rdene915.com by Dr. Rachelle Dené Poth

In the first and second parts of my AI series, I focused on where we see AI in classrooms. Benefits range from personalized learning and accessibility tools to AI-driven grading and support of a teaching assistant. In Part 2, I chose to focus on some of the important considerations related to ethics that must be part of the conversation. Schools need to focus on data privacy, bias, overreliance, and the equity divide. I wanted to focus on the future for this last part in the current AI series. Where do we go from here?

Anthropic Education Report: How University Students Use Claude — from anthropic.com

The key findings from our Education Report are:

STEM students are early adopters of AI tools like Claude, with Computer Science students particularly overrepresented (accounting for 36.8% of students’ conversations while comprising only 5.4% of U.S. degrees). In contrast, Business, Health, and Humanities students show lower adoption rates relative to their enrollment numbers.
We identified four patterns by which students interact with AI, each of which were present in our data at approximately equal rates (each 23-29% of conversations): Direct Problem Solving, Direct Output Creation, Collaborative Problem Solving, and Collaborative Output Creation.
Students primarily use AI systems for creating (using information to learn something new) and analyzing (taking apart the known and identifying relationships), such as creating coding projects or analyzing law concepts. This aligns with higher-order cognitive functions on Bloom’s Taxonomy. This raises questions about ensuring students don’t offload critical cognitive tasks to AI systems.

From the Kuali Days 2025 Conference: A CEO’s View of Planning for AI — from campustechnology.com by Mary Grush
A Conversation with Joel Dehlin

How can a company serving higher education navigate the changes AI brings to the ed tech marketplace? What will customers expect in this dynamic? Here, CT talks with Kuali CEO Joel Dehlin, who shared his company’s AI strategies in a featured plenary session, “Sneak Peek of AI in Kuali Build,” at Kuali Days 2025 in Anaheim.

How students can use generative AI — from aliciabankhofer.substack.com by Alicia Bankhofer
Part 4 of 4 in my series on Teaching and Learning in the AI Age

This article is the culmination of a series exploring AI’s impact on education.

Part 1: What Educators Need outlined essential AI literacy skills for teachers, emphasizing the need to move beyond basic ChatGPT exploration to understand the full spectrum of AI tools available in education.

Part 2: What Students Need addressed how students require clear guidance to use AI safely, ethically, and responsibly, with emphasis on developing critical thinking skills alongside AI literacy.

Part 3: How Educators Can Use GenAI presented ten practical use cases for teachers, from creating differentiated resources to designing assessments, demonstrating how AI can reclaim 5-7 hours weekly for meaningful student interactions.

Part 4: How Students Can Use GenAI (this article) provides frameworks for guiding student AI use based on Joscha Falck’s dimensions: learning about, with, through, despite, and without AI.

Mapping a Multidimensional Framework for GenAI in Education — from er.educause.edu by Patricia Turner
Prompting careful dialogue through incisive questions can help chart a course through the ongoing storm of artificial intelligence.

The goal of this framework is to help faculty, educational developers, instructional designers, administrators, and others in higher education engage in productive discussions about the use of GenAI in teaching and learning. As others have noted, theoretical frameworks will need to be accompanied by research and teaching practice, each reinforcing and reshaping the others to create understandings that will inform the development of approaches to GenAI that are both ethical and maximally beneficial, while mitigating potential harms to those who engage with it.

Instructional Design Isn’t Dying — It’s Specialising — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how AI is impacting role & purpose of Instructional Design

Together, these developments have revealed something important: despite widespread anxiety, the instructional design role isn’t dying—it’s specialising.

What we’re witnessing isn’t the automation of instructional design and the death of the instructional designer, but rather the evolution of the ID role into multiple distinct professional pathways.

The generalist “full stack” instructional designer is slowly but decisively fracturing into specialised roles that reflect both the capabilities of generative AI and the strategic imperatives facing modern organisations.

In this week’s blog post, I’ll share what I’ve learned about how our field is transforming, and what it likely means for you and your career path.

Those instructional designers who cling to traditional generalist models risk being replaced, but those who embrace specialisation, data fluency, and AI collaboration will excel and lead the next evolution of the field. Similarly, those businesses that continue to view L&D as a cost centre and focus on automating content delivery will be outperformed, while those that invest in building agile, AI-enabled learning ecosystems will drive measurable performance gains and secure their competitive advantage.

Adding AI to Every Step in Your eLearning Design Workflow — from learningguild.com by George Hanshaw

We know that eLearning is a staple of training and development. The expectations of the learners are higher than ever: They expect a dynamic, interactive, and personalized learning experience. As instructional designers, we are tasked with meeting these expectations by creating engaging and effective learning solutions.

The integration of Artificial Intelligence (AI) into our eLearning design process is a game-changer that can significantly enhance the quality and efficiency of our work.

No matter if you use ADDIE or rapid prototyping, AI has a fit in every aspect of your workflow. By integrating AI, you can ensure a more efficient and effective design process that adapts to the unique needs of your learners. This not only saves time and resources but also significantly enhances the overall learning experience. We will explore the needs analysis and the general design process.

How might the memory of an AI — over time — impact personalized and lifelong learning? [Christian]

On 04/11/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate universities / corporate training, Daniel S. Christian, education, education reform, education technology, emerging technologies, experimentation, faculty/staff, formal learning, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, lifelong learning, online learning, online media, online tutoring, personalized/customized learning, platforms, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, trends, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

From DSC:
After seeing Sam’s posting below, I can’t help but wonder:

How might the memory of an AI over time impact the ability to offer much more personalized learning?
How will that kind of memory positively impact a person’s learning-related profile?
Which learning-related agents get called upon?
Which learning-related preferences does a person have while learning about something new?
Which methods have worked best in the past for that individual? Which methods didn’t work so well with him or her?

we have greatly improved memory in chatgpt–it can now reference all your past conversations!

this is a surprisingly great feature imo, and it points at something we are excited about: ai systems that get to know you over your life, and become extremely useful and personalized.

— Sam Altman (@sama) April 10, 2025

Starting today, memory in ChatGPT can now reference all of your past chats to provide more personalized responses, drawing on your preferences and interests to make it even more helpful for writing, getting advice, learning, and beyond. pic.twitter.com/s9BrWl94iY

— OpenAI (@OpenAI) April 10, 2025

Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

On 04/10/2025, in 21st century, 24x7x365 access, accreditation, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, Blockchain, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, credentialing, culture, curriculum, dangers of the status quo, Daniel S. Christian, data related items, Design Thinking, digital learning, disruption, education technology, emerging technologies, Emotion, engagement / engaging students, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, leadership, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, lifelong learning, MBA, Michigan, new business models, online learning, online media, online tutoring, organizational change, pace of change, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, technologies for your home, tools, trends, United States, universities, usability, user experience (UX), virtual tutoring, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

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Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
…
What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
…
Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
…
In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

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.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY
.

By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!

Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

The 2025 ABA Techshow Startup Alley Pitch Competition Ended In A Tie – Here Are The Winners — from lawnext.com by Bob Ambrogi

This year, two startups ended up with an equal number of votes for the top spot:

Case Crafter, a company from Norway that helps legal professionals build compelling visual timelines based on case files and evidence.
Querious, a product that provides attorneys with real-time insights during client conversations into legal issues, relevant content, and suggested questions and follow-ups.
.

DC: If https://t.co/c3Io6EqFds can do this with legal-related conversations, what about with lectures & learning-related applications of this?

Querious transforms client conversations with real-time legal insights while reducing non-billable administrative tasks.#legaltech #AI pic.twitter.com/s0r9o4N89q

— Daniel S. Christian (@dchristian5) April 9, 2025

AI academy gives law students a head start on legal tech, says OBA innovator — from canadianlawyermag.com by Branislav Urosevic

The Ontario Bar Association has recently launched a hands-on AI learning platform tailored for lawyers. Called the AI Academy, the initiative is designed to help legal professionals explore, experiment with, and adopt AI tools relevant to their practice.

Colin Lachance, OBA’s innovator-in-residence and the lead designer of the platform, says that although the AI Academy was built for practising lawyers, it is also well-suited for law students.

AI in Education Survey: What UK and US Educators Think in 2025 — from twinkl.com
As artificial intelligence (AI) continues to shape the world around us, Twinkl conducted a large-scale survey between January 15th and January 22nd to explore its impact on the education sector, as well as the work lives of teachers across the UK and the USA.

Teachers’ use of AI for work continues to rise
Twinkl’s survey asked teachers whether they were currently using AI for work purposes. Comparing these findings to similar surveys over recent years shows the use of AI tools by teachers has seen a significant increase across both the UK and USA.

According to two UK surveys by the National Literacy Trust – 30% of teachers used generative AI in 2023 and nearly half (47.7%) in 2024. Twinkl’s survey indicates that AI adoption continues to rise rapidly, with 60% of UK educators currently integrating it into their work lives in 2025.
Similarly, with 62% of US teachers currently using AI for work, uptake appears to have risen greatly in the past 12 months, with just 25% saying they were leveraging the new technology in the 2023-24 school year according to a RAND report.
Teachers are using AI more for work than in their personal lives: In the UK, personal usage drops to 43% (from 60% at school). In the US, 52% are using AI for non-work purposes (versus 62% in education settings).

60% of UK teachers and 62% of US teachers use AI in their work life in 2025.

Drive Continuous Learning: AI Integrates Work & Training — from learningguild.com by George Hanshaw

Imagine with me for a moment: Training is no longer confined to scheduled sessions in a classroom, an online module or even a microlearning you click to activate during your workflow. Imagine training being delivered because the system senses what you are doing and provides instructions and job aids without you having to take an action.

The rapid evolution of artificial intelligence (AI) and wearable technology has made it easier than ever to seamlessly integrate learning directly into the workflow. Smart glasses, earpieces, and other advanced devices are redefining how employees gain knowledge and skills by delivering microlearning moments precisely when and where they are needed.

AI plays a crucial role in this transformation by sensing the optimal moment to deliver the training through augmented reality (AR).

These Schools Are Banding Together to Make Better Use of AI in Education — from edsurge.com by Emily Tate Sullivan

Kennelly and Geraffo are part of a small team at their school in Denver, DSST: College View High School, that is participating in the School Teams AI Collaborative, a year-long pilot initiative in which more than 80 educators from 19 traditional public and charter schools across the country are experimenting with and evaluating AI-enabled instruction to improve teaching and learning.

The goal is for some of AI’s earliest adopters in education to band together, share ideas and eventually help lead the way on what they and their colleagues around the U.S. could do with the emerging technology.

“Pretty early on we thought it was going to be a massive failure,” says Kennelly of last semester’s project. “But it became a huge hit. Students loved it. They were like, ‘I ran to second period to build this thing.’”

Transactional vs. Conversational Visions of Generative AI in Teaching — from elmartinsen.substack.com by Eric Lars Martinsen
AI as a Printer, or AI as a Thought Partner

As writing instructors, we have a choice in how we frame AI for our students. I invite you to:

Experiment with AI as a conversation partner yourself before introducing it to students
Design assignments that leverage AI’s strengths as a thought partner rather than trying to “AI-proof” your existing assignments
Explicitly teach students how to engage in productive dialogue with AI—how to ask good questions, challenge AI’s assumptions, and use it to refine rather than replace their thinking
Share your experiences, both positive and negative, with colleagues to build our collective understanding of effective AI integration

.
Building an AI-Ready Workforce: A look at College Student ChatGPT Adoption in the US — from cdn.openai.com

One finding from our student survey that stood out to us: Many college and university students are teaching themselves and their friends about AI without waiting for their institutions to provide formal AI education or clear policies about the technology’s use. The education ecosystem is in an important moment of exploration and learning, but the rapid adoption by students across the country who haven’t received formalized instruction in how and when to use the technology creates disparities in AI access and knowledge.

The enclosed snapshot of how young people are using ChatGPT provides insight into the state of AI use among America’s college-aged students. We also include actionable proposals to help address adoption gaps. We hope these insights and proposals can inform research and policy conversation across the nation’s education ecosystem about how to achieve outcomes that support our students, our workforce, and the economy. By improving literacy, expanding access, and implementing clear policies, policymakers and educators can better integrate AI into our educational infrastructure and ensure that our workforce is ready to both sustain and benefit from our future with AI.

Leah Belsky | Vice President, Education | OpenAI

“AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities” + other items re: AI in our learning ecosystems

On 02/20/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, colleges, communications, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital audio, e-readers, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, legislatures / government / legal, liberal arts, mathematics, multimedia, pedagogy, personalized/customized learning, platforms, research, STEAM-related, student-related, teachers, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, by Daniel Christian

AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities (webinar)
How AI is Transforming Classrooms Today and What’s Next

Audio-Based Learning 4.0 — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new & powerful way to leverage AI for learning?

At the end of all of this my reflection is that the research paints a pretty exciting picture – audio-based learning isn’t just effective, it’s got some unique superpowers when it comes to boosting comprehension, ramping up engagement, and delivering feedback that really connects with learners.

While audio has been massively under-used as a mode of learning, especially compared to video and text, we’re at an interesting turning point where AI tools are making it easier than ever to tap into audio’s potential as a pedagogical tool.

What’s super interesting is how the solid research backing audio’s effectiveness is and how well this is converging with these new AI capabilities.

From DSC:
I’ve noticed that I don’t learn as well via audio-only based events. It can help if visuals are also provided, but I have to watch the cognitive loads. My processing can start to get overloaded — to the point that I have to close my eyes and just listen sometimes. But there are people I know who love to listen to audiobooks and prefer to learn that way. They can devour content and process/remember it all. Audio is a nice change of pace at times, but I prefer visuals and reading often times. It needs to be absolutely quiet if I’m tackling some new information/learning.

In Conversation With… Ashton Cousineau — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new video series exploring how L&D professionals are working with AI on the ground

In Conversation With… Ashton Cousineau by Dr Philippa Hardman

A new video series exploring how L&D professionals are working with AI on the ground

Read on Substack

The Learning Research Digest vol. 28 — from learningsciencedigest.substack.com by Dr. Philippa Hardman

Hot Off the Research Press This Month:

AI-Infused Learning Design – A structured approach to AI-enhanced assignments using a three-step model for AI integration.
Mathematical Dance and Creativity in STEAM – Using AI-powered motion capture to translate dance movements into mathematical models.
AI-Generated Instructional Videos – How adaptive AI-powered video learning enhances problem-solving and knowledge retention.
Immersive Language Learning with XR & AI – A new framework for integrating AI-driven conversational agents with Extended Reality (XR) for task-based language learning.
Decision-Making in Learning Design – A scoping review on how instructional designers navigate complex instructional choices and make data-driven decisions.
Interactive E-Books and Engagement – Examining the impact of interactive digital books on student motivation, comprehension, and cognitive engagement.
Elevating Practitioner Voices in Instructional Design – A new initiative to amplify instructional designers’ contributions to research and innovation.

Deep Reasoning, Agentic AI & the Continued Rise of Specialised AI Research & Tools for Education — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s a quick teaser of key developments in the world of AI & learning this month:

DeepSeek R-1, OpenAI’s Deep Seek & Perplexity’s ‘Deep Research’ are the latest additions to a growing number of “reasoning models” with interesting implications for evidence-based learning design & development.
The U.S. Education Dept release an AI Toolkit and a fresh policy roadmap enabling the adoption of AI use in schools.
Anthropic Release “Agentic Claude”, another AI agent that clicks, scrolls, and can even successfully complete e-learning courses…
Oxford University Announce the AIEOU Hub, a research-backed research lab to support research and implementation on AI in education.
“AI Agents Everywhere”: A Forbes peek at how agentic AI will handle the “boring bits” of classroom life.
[Bias klaxon!] Epiphany AI: My own research leads to the creation of a specialised, “pedagogy first” AI co-pilot for instructional design marking the continued growth of specialised AI tools designed for specific industries and workflows.

AI is the Perfect Teaching Assistant for Any Educator — from unite.ai by Navi Azaria, CPO at Kaltura

Through my work with leading educational institutions at Kaltura, I’ve seen firsthand how AI agents are rapidly becoming indispensable. These agents alleviate the mounting burdens on educators and provide new generations of tech-savvy students with accessible, personalized learning, giving teachers the support they need to give their students the personalized attention and engagement they deserve.

Learning HQ — from ai-disruptor-hq.notion.site

This HQ includes all of my AI guides, organized by tool/platform. This list is updated each time a new one is released, and outdated guides are removed/replaced over time.

How AI Is Reshaping Teachers’ Jobs — from edweek.org

Artificial intelligence is poised to fundamentally change the job of teaching. AI-powered tools can shave hours off the amount of time teachers spend grading, lesson-planning, and creating materials. AI can also enrich the lessons they deliver in the classroom and help them meet the varied needs of all students. And it can even help bolster teachers’ own professional growth and development.

Despite all the promise of AI, though, experts still urge caution as the technology continues to evolve. Ethical questions and practical concerns are bubbling to the surface, and not all teachers feel prepared to effectively and safely use AI.

In this special report, see how early-adopter teachers are using AI tools to transform their daily work, tackle some of the roadblocks to expanded use of the technology, and understand what’s on the horizon for the teaching profession in the age of artificial intelligence.

2025 EDUCAUSE AI Landscape Study: Into the Digital AI Divide — from library.educause.edu

The higher education community continues to grapple with questions related to using artificial intelligence (AI) in learning and work. In support of these efforts, we present the 2025 EDUCAUSE AI Landscape Study, summarizing our community’s sentiments and experiences related to strategy and leadership, policies and guidelines, use cases, the higher education workforce, and the institutional digital divide.

“Half A Million Students Given ChatGPT As CSU System Makes AI History” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 02/07/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, change, colleges, community colleges, content development, aggregation, repositories, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, graphics, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, research, student-related, teachers, teaching & learning, tools, trends, United States, universities, vendors, by Daniel Christian

Half A Million Students Given ChatGPT As CSU System Makes AI History — from forbes.com by Dan Fitzpatrick

The California State University system has partnered with OpenAI to launch the largest deployment of AI in higher education to date.

The CSU system, which serves nearly 500,000 students across 23 campuses, has announced plans to integrate ChatGPT Edu, an education-focused version of OpenAI’s chatbot, into its curriculum and operations. The rollout, which includes tens of thousands of faculty and staff, represents the most significant AI deployment within a single educational institution globally.

We’re still in the early stages of AI adoption in education, and it is critical that the entire ecosystem—education systems, technologists, educators, and governments—work together to ensure that all students globally have access to AI and develop the skills to use it responsibly

Leah Belsky, VP and general manager of education at OpenAI.

HOW educators can use GenAI – where to start and how to progress — from aliciabankhofer.substack.com by Alicia Bankhofer
Part of 3 of my series: Teaching and Learning in the AI Age

As you read through these use cases, you’ll notice that each one addresses multiple tasks from our list above.

1. Researching a topic for a lesson
2. Creating Tasks For Practice
3. Creating Sample Answers
4. Generating Ideas
5. Designing Lesson Plans
6. Creating Tests
7. Using AI in Virtual Classrooms
8. Creating Images
9. Creating worksheets
10. Correcting and Feedback

“Over 100 AI Tools for Teachers” [Kharbach] + other items re: AI in our learning ecosystems

On 02/01/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, teaching online, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

DeepSeek: How China’s AI Breakthrough Could Revolutionize Educational Technology — from nickpotkalitsky.substack.com by Nick Potkalitsky
Can DeepSeek’s 90% efficiency boost make AI accessible to every school?

The most revolutionary aspect of DeepSeek for education isn’t just its cost—it’s the combination of open-source accessibility and local deployment capabilities. As Azeem Azhar notes, “R-1 is open-source. Anyone can download and run it on their own hardware. I have R1-8b (the second smallest model) running on my Mac Mini at home.”
…

Real-time Learning Enhancement

AI tutoring networks that collaborate to optimize individual learning paths
Immediate, multi-perspective feedback on student work
Continuous assessment and curriculum adaptation

The question isn’t whether this technology will transform education—it’s how quickly institutions can adapt to a world where advanced AI capabilities are finally within reach of every classroom.

Over 100 AI Tools for Teachers — from educatorstechnology.com by Med Kharbach, PhD

I know through your feedback on my social media and blog posts that several of you have legitimate concerns about the impact of AI in education, especially those related to data privacy, academic dishonesty, AI dependence, loss of creativity and critical thinking, plagiarism, to mention a few. While these concerns are valid and deserve careful consideration, it’s also important to explore the potential benefits AI can bring when used thoughtfully.

Tools such as ChatGPT and Claude are like smart research assistants that are available 24/7 to support you with all kinds of tasks from drafting detailed lesson plans, creating differentiated materials, generating classroom activities, to summarizing and simplifying complex topics. Likewise, students can use them to enhance their learning by, for instance, brainstorming ideas for research projects, generating constructive feedback on assignments, practicing problem-solving in a guided way, and much more.

The point here is that AI is here to stay and expand, and we better learn how to use it thoughtfully and responsibly rather than avoid it out of fear or skepticism.

Beth’s posting links to:

Digital Education Council Global AI Faculty Survey 2025 — from digitaleducationcouncil.com

Derek’s posting on LinkedIn

From Theory to Practice: How Generative AI is Redefining Instructional Materials — from edtechinsiders.substack.com by Alex Sarlin
Top trends and insights from The Edtech Insiders Generative AI Map research process about how Generative AI is transforming Instructional Materials

As part of our updates to the Edtech Insiders Generative AI Map, we’re excited to release a new mini market map and article deep dive on Generative AI tools that are specifically designed for Instructional Materials use cases.

In our database, the Instructional Materials use case category encompasses tools that:

Assist educators by streamlining lesson planning, curriculum development, and content customization
Enable educators or students to transform materials into alternative formats, such as videos, podcasts, or other interactive media, in addition to leveraging gaming principles or immersive VR to enhance engagement
Empower educators or students to transform text, video, slides or other source material into study aids like study guides, flashcards, practice tests, or graphic organizers
Engage students through interactive lessons featuring historical figures, authors, or fictional characters
Customize curriculum to individual needs or pedagogical approaches
Empower educators or students to quickly create online learning assets and courses

On a somewhat-related note, also see:

Tech & Learning Announces Winners of Best of 2024 — from techlearning.com by TL Editors
This annual award celebrates recognizing the best in EdTech from 2024

“Leadership & Generative AI: Hard-Earned Lessons That Matter” [Klitgaard Stricker] + other items re: AI in our learning ecosystems

On 01/22/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, library / librarians, lifelong learning, Michigan, microlearning, multimedia, Natural Language Processing (NLP), personalized/customized learning, platforms, productivity / tips and tricks, reading, research, strategy, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, writing, by Daniel Christian

Your AI Writing Partner: The 30-Day Book Framework — from aidisruptor.ai by Alex McFarland and Kamil Banc
How to Turn Your “Someday” Manuscript into a “Shipped” Project Using AI-Powered Prompts

With that out of the way, I prefer Claude.ai for writing. For larger projects like a book, create a Claude Project to keep all context in one place.

Copy [the following] prompts into a document
Use them in sequence as you write
Adjust the word counts and specifics as needed
Keep your responses for reference
Use the same prompt template for similar sections to maintain consistency

Each prompt builds on the previous one, creating a systematic approach to helping you write your book.

Using NotebookLM to Boost College Reading Comprehension — from michellekassorla.substack.com by Michelle Kassorla and Eugenia Novokshanova
This semester, we are using NotebookLM to help our students comprehend and engage with scholarly texts

We were looking hard for a new tool when Google released NotebookLM. Not only does Google allow unfettered use of this amazing tool, it is also a much better tool for the work we require in our courses. So, this semester, we have scrapped our “old” tools and added NotebookLM as the primary tool for our English Composition II courses (and we hope, fervently, that Google won’t decide to severely limit its free tier before this semester ends!)

If you know next-to-nothing about NotebookLM, that’s OK. What follows is the specific lesson we present to our students. We hope this will help you understand all you need to know about NotebookLM, and how to successfully integrate the tool into your own teaching this semester.

Leadership & Generative AI: Hard-Earned Lessons That Matter — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable Advice for Higher Education Leaders in 2025

AFTER two years of working closely with leadership in multiple institutions, and delivering countless workshops, I’ve seen one thing repeatedly: the biggest challenge isn’t the technology itself, but how we lead through it. Here is some of my best advice to help you navigate generative AI with clarity and confidence:

Break your own AI policies before you implement them. …
Fund your failures. …
Resist the pilot program. …
Host Anti-Tech Tech Talks …
…+ several more tips

While generative AI in higher education obviously involves new technology, it’s much more about adopting a curious and human-centric approach in your institution and communities. It’s about empowering learners in new, human-oriented and innovative ways. It is, in a nutshell, about people adapting to new ways of doing things.

Maria Anderson responded to Clay’s posting with this idea:

Here’s an idea: […] the teacher can use the [most advanced] AI tool to generate a complete solution to “the problem” — whatever that is — and demonstrate how to do that in class. Give all the students access to the document with the results.

And then grade the students on a comprehensive followup activity / presentation of executing that solution (no notes, no more than 10 words on a slide). So the students all have access to the same deep AI result, but have to show they comprehend and can iterate on that result.

Grammarly just made it easier to prove the sources of your text in Google Docs — from zdnet.com by Jack Wallen
If you want to be diligent about proving your sources within Google Documents, Grammarly has a new feature you’ll want to use.

In this age of distrust, misinformation, and skepticism, you may wonder how to demonstrate your sources within a Google Document. Did you type it yourself, copy and paste it from a browser-based source, copy and paste it from an unknown source, or did it come from generative AI?

You may not think this is an important clarification, but if writing is a critical part of your livelihood or life, you will definitely want to demonstrate your sources.

That’s where the new Grammarly feature comes in.

The new feature is called Authorship, and according to Grammarly, “Grammarly Authorship is a set of features that helps users demonstrate their sources of text in a Google doc. When you activate Authorship within Google Docs, it proactively tracks the writing process as you write.”

AI Agents Are Coming to Higher Education — from govtech.com
AI agents are customizable tools with more decision-making power than chatbots. They have the potential to automate more tasks, and some schools have implemented them for administrative and educational purposes.

Custom GPTs are on the rise in education. Google’s version, Gemini Gems, includes a premade version called Learning Coach, and Microsoft announced last week a new agent addition to Copilot featuring use cases at educational institutions.

Generative Artificial Intelligence and Education: A Brief Ethical Reflection on Autonomy — from er.educause.edu by Vicki Strunk and James Willis
Given the widespread impacts of generative AI, looking at this technology through the lens of autonomy can help equip students for the workplaces of the present and of the future, while ensuring academic integrity for both students and instructors.

The principle of autonomy stresses that we should be free agents who can govern ourselves and who are able to make our own choices. This principle applies to AI in higher education because it raises serious questions about how, when, and whether AI should be used in varying contexts. Although we have only begun asking questions related to autonomy and many more remain to be asked, we hope that this serves as a starting place to consider the uses of AI in higher education.

“AI tutoring shows stunning results” [World Bank] + “AI Is Unavoidable, Not Inevitable.” [Watkins]

On 01/17/2025, in 21st century, adjunct faculty, adult learning, Africa, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future, game-changing environment, higher education, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, K-12 related, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, teachers, teaching & learning, United States, universities, by Daniel Christian

AI Is Unavoidable, Not Inevitable — from marcwatkins.substack.com by Marc Watkins

I had the privilege of moderating a discussion between Josh Eyler and Robert Cummings about the future of AI in education at the University of Mississippi’s recent AI Winter Institute for Teachers. I work alongside both in faculty development here at the University of Mississippi. Josh’s position on AI sparked a great deal of debate on social media:
…
To make my position clear about the current AI in education discourse I want to highlight several things under an umbrella of “it’s very complicated.”

Most importantly, we all deserve some grace here. Dealing with generative AI in education isn’t something any of us asked for. It isn’t normal. It isn’t fixable by purchasing a tool or telling faculty to simply ‘prefer not to’ use AI. It is and will remain unavoidable for virtually every discipline taught at our institutions.

If one good thing happens because of generative AI let it be that it helps us clearly see how truly complicated our existing relationships with machines are now. As painful as this moment is, it might be what we need to help prepare us for a future where machines that mimic reasoning and human emotion refuse to be ignored.

“AI tutoring shows stunning results.”
See below article.

From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time — from blogs.worldbank.org by Martín E. De Simone, Federico Tiberti, Wuraola Mosuro, Federico Manolio, Maria Barron, and Eliot Dikoru

Learning gains were striking
The learning improvements were striking—about 0.3 standard deviations. To put this into perspective, this is equivalent to nearly two years of typical learning in just six weeks. When we compared these results to a database of education interventions studied through randomized controlled trials in the developing world, our program outperformed 80% of them, including some of the most cost-effective strategies like structured pedagogy and teaching at the right level. This achievement is particularly remarkable given the short duration of the program and the likelihood that our evaluation design underestimated the true impact.
…
Our evaluation demonstrates the transformative potential of generative AI in classrooms, especially in developing contexts. To our knowledge, this is the first study to assess the impact of generative AI as a virtual tutor in such settings, building on promising evidence from other contexts and formats; for example, on AI in coding classes, AI and learning in one school in Turkey, teaching math with AI (an example through WhatsApp in Ghana), and AI as a homework tutor.

Comments on this article from The Rundown AI:

Why it matters: This represents one of the first rigorous studies showing major real-world impacts in a developing nation. The key appears to be using AI as a complement to teachers rather than a replacement — and results suggest that AI tutoring could help address the global learning crisis, particularly in regions with teacher shortages.

Other items re: AI in our learning ecosystems:

Will AI revolutionise marking? — from timeshighereducation.com by Rohim Mohammed
Artificial intelligence has the potential to improve speed, consistency and detail in feedback for educators grading students’ assignments, writes Rohim Mohammed. Here he lists the pros and cons based on his experience
Marty the Robot: Your Classroom’s AI Companion — from rdene915.com by Dr. Rachelle Dené Poth
Generative Artificial Intelligence: Cautiously Recognizing Educational Opportunities — from scholarlyteacher.com by Todd Zakrajsek, University of North Carolina at Chapel Hill
Personal AI — from michelleweise.substack.com by Dr. Michelle Weise
“Personalized” Doesn’t Have To Be a Buzzword
Today, however, is a different kind of moment. GenAI is now rapidly evolving to the point where we may be able to imagine a new way forward. We can begin to imagine solutions truly tailored for each of us as individuals, our own personal AI (pAI). pAI could unify various silos of information to construct far richer and more holistic and dynamic views of ourselves as long-life learners. A pAI could become our own personal career navigator, skills coach, and storytelling agent. Three particular areas emerge when we think about tapping into the richness of our own data:
- Personalized Learning Pathways & Dynamic Skill Assessment: …
- Storytelling for Employers:…
- Ongoing Mentorship and Feedback: …
Speak — a language learning app — via The Neuron

Voc.Adapt — via The Neuron

Learning Ecosystems

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