8 AI Chatbots for Teachers: A Simple Guide and Quick Tips – Class Tech Tips
— from classtechtips.com by Dr. Monica Burns
On 07/01/2025,
in accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, communications, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, pedagogy, personalized/customized learning, platforms, strategy, teachers, tools, vendors,
by Daniel Christian
Transform Public Speaking with Yoodli: Your AI Coach — from rdene915.com by Paula Johnson
Yoodli is an AI tool designed to help users improve their public speaking skills. It analyzes your speech in real-time or after a recording and gives you feedback on things like:
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- Filler words (“um,” “like,” “you know”)
- Pacing (Are you sprinting or sedating your audience?)
- Word choice and sentence complexity
- Eye contact and body language (with video)
- And yes, even your “uhhh” to actual word ratio
Yoodli gives you a transcript and a confidence score, plus suggestions that range from helpful to brutally honest. It’s basically Simon Cowell with AI ethics and a smiley face interface.
[What’s] going on with AI and education? — from theneuron.ai by Grant Harvey
With students and teachers alike using AI, schools are facing an “assessment crisis” where the line between tool and cheating has blurred, forcing a shift away from a broken knowledge economy toward a new focus on building human judgment through strategic struggle.
What to do about it: The future belongs to the “judgment economy,” where knowledge is commoditized but taste, agency, and learning velocity become the new human moats. Use the “Struggle-First” principle: wrestle with problems for 20-30 minutes before turning to AI, then use AI as a sparring partner (not a ghostwriter) to deepen understanding. The goal isn’t to avoid AI, but to strategically choose when to embrace “desirable difficulties” that build genuine expertise versus when to leverage AI for efficiency.
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The Alpha-School Program in brief:
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- Students complete core academics in just 2 hours using AI tutors, freeing up 4+ hours for life skills, passion projects, and real-world experiences.
- The school claims students learn at least 2x faster than their peers in traditional school.
- The top 20% of students show 6.5x growth. Classes score in the top 1-2% nationally across the board.
- Claims are based on NWEA’s Measures of Academic Progress (MAP) assessments… with data only available to the school. Hmm…
Austen Allred shared a story about the school, which put it on our radar.
Featured Report: Teaching for Tomorrow: Unlocking Six Weeks a Year With AI — from gallup.com
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In the latest installment of Gallup and the Walton Family Foundation’s research on education, K-12 teachers reveal how AI tools are transforming their workloads, instructional quality and classroom optimism. The report finds that 60% of teachers used an AI tool during the 2024–25 school year. Weekly AI users report reclaiming nearly six hours per week — equivalent to six weeks per year — which they reinvest in more personalized instruction, deeper student feedback and better parent communication.
Despite this emerging “AI dividend,” adoption is uneven: 40% of teachers aren’t using AI at all, and only 19% report their school has a formal AI policy. Teachers with access to policies and support save significantly more time.
Educators also say AI improves their work. Most report higher-quality lesson plans, assessments and student feedback. And teachers who regularly use AI are more optimistic about its benefits for student engagement and accessibility — mirroring themes from the Voices of Gen Z: How American Youth View and Use Artificial Intelligence report, which found students hesitant but curious about AI’s classroom role. As AI tools grow more embedded in education, both teachers and students will need the training and support to use them effectively.
Also see:
- 2-Hour Learning
- What if children could crush academics in 2 hours, 2x faster?
- What if children could get back their most valuable resource, which is time?
- What if children could pursue the things they want during their afternoons and develop life skills?
Amira Learning: Teaching With The AI-Powered Reading Tool — from techlearning.com by Erik Ofgang
Amira Learning is a research-backed AI reading tutor that incorporates the science of reading into its features.
What Is Amira Learning?
Amira Learning’s system is built upon research led by Jack Mostow, a professor at Carnegie Mellon who helped pioneer AI literacy education. Amira uses Claude AI to power its AI features, but these features are different than many other AI tools on the market. Instead of focusing on chat and generative response, Amira’s key feature is its advanced speech recognition and natural language processing capabilities, which allow the app to “hear” when a student is struggling and tailor suggestions to that student’s particular mistakes.
Though it’s not meant to replace a teacher, Amira provides real-time feedback and also helps teachers pinpoint where a student is struggling. For these reasons, Amira Learning is a favorite of education scientists and advocates for science of reading-based literacy instruction. The tool currently is used by more than 4 million students worldwide and across the U.S.
On 06/23/2025,
in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, 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 agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing,
by Daniel Christian
Thoughts on thinking — from dcurt.is by Dustin Curtis
Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.
The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.
Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them
Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.
First, the easy stuff.
Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.
Also see:
Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others
This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.
One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.
It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
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The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:
What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.
The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures
On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.
Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.
Of course, that would be a mistake.
We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.
Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng
By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.
This AI Model Never Stops Learning — from link.wired.com by Will Knight
Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.
The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.
The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.
Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing
Highlights:
- Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
- Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
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.
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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?
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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.
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.
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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.
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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.
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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.
On 04/09/2025,
in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, Canada, career development, change, changing business models, cloud-based computing / apps / other cloud-related, education technology, emerging technologies, entrepreneurship, Europe, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, law schools, Legal operations, legal technologies, legislatures / government / legal, tools, United States, vendors,
by Daniel Christian
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.
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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.
On 03/07/2025,
in Artificial Intelligence/Agents/LLMs/and Related, business, collaboration, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, human-computer interaction (HCI), ideas, instructional design, intelligent systems, intelligent tutoring, K-12 related, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, United States, universities, vendors, wearables, writing,
by Daniel Christian
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
On 02/25/2025,
in Artificial Intelligence/Agents/LLMs/and Related, career development, colleges, community colleges, digital learning, education technology, emerging technologies, experimentation, faculty/staff, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning ecosystem, Learning from the Living [Class] Room, Open AI, productivity / tips and tricks, programming, skills, staying relevant, student-related, teachers, teaching & learning, teaching online, United States, universities, vendors, workplace, writing,
by Daniel Christian
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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
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
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.