From Dazzling Lights to Bursting Geysers, Jennifer Esseiva Captures Iceland’s Diverse Scenery — from thisiscolossal.com by Jennifer Esseiva and Jackie Andres
Uncanny Objects by Joyce Lin Blur Distinctions Between Reality and the Fantastical — from thisiscolossal.com by Kate Mothes and Joyce Lin
In London, an Enormous Exhibition of 500+ Works Roots Out the Creative Seeds of Flowers — from thisiscolossal.com by Grace Ebert and Co.
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.”
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Real-time Learning Enhancement
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:
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:
On a somewhat-related note, also see:
Four objectives to guide artificial intelligence’s impact on higher education — from timeshighereducation.com by Susan C. Aldridge
How can higher education leaders manage both the challenge and the opportunity artificial intelligence presents? Here are four objectives to guide the way
That’s why, today, the question I’m asking is: How best can we proactively guide AI’s use in higher education and shape its impact on our students, faculty and institution? The answer to that broad, strategic question lies in pursuing four objectives that, I believe, are relevant for many colleges and universities.
In This Week’s Gap Letter — by Ryan Craig
Learning to use business software is different from learning to think. But if the software is sufficiently complex, how different is it really? What if AI’s primary impact on education isn’t in the classroom, but rather shifting the locus of learning to outside the classroom?
Instead of sitting in a classroom listening to a teacher, high school and college students could be assigned real work and learn from that work. Students could be matched with employers or specific projects provided by or derived from employers, then do the work on the same software used in the enterprise. As AI-powered digital adoption platforms (DAPs) become increasingly powerful, they have the potential to transform real or simulated work into educational best practice for students only a few years away from seeking full-time employment.
If DAPs take us in this direction, four implications come to mind….
The Impact of Gen AI on Human Learning: a research summary — from drphilippahardman.substack.com by Dr. Philippa Hardman
A literature review of the most recent & important peer-reviewed studies
In this week’s blog post, I share a summary of five recent studies on the impact of Gen AI on learning to bring you right up to date.
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Implications for Educators and Developers
For Educators:
For Developers:
Assessing the GenAI process, not the output — from timeshighereducation.com by Paul McDermott, Leoni Palmer, and Rosemary Norton
A framework for building AI literacy in a literature-review-type assessment
In this resource, we outline our advice for implementing an approach that opens AI use up to our students through a strategy of assessing the process rather than outputs.
To start with, we recommend identifying learning outcomes for your students that can be achieved in collaboration with AI.
What’s New: The Updated Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell
A major expansion on our previously released market map, use case database, and AI tool company directory.
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Tutorial: 4 Ways to Use LearnLM as a Professor — from automatedteach.com by Graham Clay
Create better assessments, improve instructions and feedback, and tutor your students with this fine-tuned version of Gemini.
I cover how to use LearnLM
6% of Faculty Feel Supported on AI?! — from automatedteach.com by Graham Clay
Plus, a webinar on building AI tutors this Friday.
The Digital Education Council just released their Global AI Faculty Survey of 1,681 faculty members from 52 institutions across 28 countries, and the findings are eye-opening. (Click here if you missed their analogous survey of students.)
While 86% of faculty see themselves using AI in their future teaching [p. 21], only 6% strongly agree that their institutions have provided sufficient resources to develop their AI literacy [p. 35].
This is a concerning gap between the recognized power of AI and institutional support, and it’s a clear signal about where higher education needs to focus in 2025.
Speaking with faculty about AI around the world, I’ve seen this firsthand. But let’s dig into the survey’s findings.
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Why the gap? Well, one explanation is that faculty lack institutional support.
The survey reveals that…
From DSC:
I was in a teaching and learning group for 10+ years (and in several edtech-related positions before that). We had a senior staff established there but we were mainly called upon for edtech, instructional technology, learning spaces, or LMS types of tasks and questions. Though we could have brought a lot of value to the pedagogical table, the vast majority of the faculty wanted to talk to other faculty members. Our group’s hard-earned — and expensive — expertise didn’t count. We ourselves were teaching classes..but not enough to be on par with the faculty members (at least in their minds). They didn’t seek us out. Perhaps we should have gone door to door, but we didn’t have the resources to do that.
Book groups were effective when the T&L group met with faculty members to discuss things. The discussions were productive. And in those groups, we DID have a seat at the pedagogical table.
But I’m not going to jump on the “we don’t have enough support” bandwagon. Faculty members seek out other faculty members. In many cases, if you aren’t faculty, you don’t count.
So if I were still working and I was in a leadership position, I would sponsor some book study groups with faculty and personnel from teaching and learning centers. Topics for those books could be:
A Practical Framework for Microlearning Success: A Guide for Learning Leaders — from learningguild.com by Robyn A. Defelice
Gaining insight from the framework
Goals or Measurable Outcomes
Purpose
Potential
Evaluation
…and more
By focusing on short-term wins, auditing for gaps, and planning strategically, L&D leaders can create initiatives that deliver meaningful, sustained results.
A Community College’s Guide to Building Strong Partnerships — from eddesignlab.org
This November 2024 guidebook offers higher education practitioners actionable strategies for building and sustaining partnerships that both meet regional needs and support students, families, and communities. This work was based on the design and delivery of dual enrollment pathways as part of the Lab’s Designers in Residence 2.0: Accelerating Pathways project.
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The practices and case studies shared here are informed by higher education leaders across six community colleges as part of the Lab’s Designers in Residence program.
We have organized the guidebook based on core elements of a strong partnerships strategy, alongside how to establish a strong foundation and sustain and maintain the partnerships you’ve built. Through our research, we’ve identified four key elements of strong partnerships:
+ Communication and collaboration
+ Shared vision
+ Adaptive and responsive
+ Action-oriented
You will find guiding questions, tools, and case studies within each of the four elements.
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Also from The Education Design Lab:
