Do I Need a Degree in Instructional Design? It Depends. — from teamedforlearning.com

It’s a common question for those considering a career in instructional design: Do I need a degree to land a job? The answer? It depends.

Hiring managers aren’t just looking for a degree—they want proof that you have the knowledge, skills, and abilities to succeed. In fact, most employers focus on 3 key factors when assessing candidates. You typically need at least 2 of these to be considered:

  1. A Credential – A degree or certification in instructional design, learning experience design, or a related field.
  2. Relevant Work Experience – Hands-on experience designing and developing learning solutions.
  3. Proof of Abilities – A strong portfolio showcasing eLearning modules, course designs, or learning strategies.

The good news? You don’t have to spend years earning a degree to break into the field. If you’re resourceful, you can fast-track your way in through volunteer projects, contract work, and portfolio building.

Whether you’re a recent graduate, a career changer, or a working professional looking for your next opportunity, focusing on these key factors can help you stand out and get hired.

 

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

.
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.

 




Students and folks looking for work may want to check out:

Also relevant/see:


 

8 Weeks Left to Prepare Students for the AI-Enhanced Workplace — from insidehighered.com by Ray Schroeder
We are down to the final weeks left to fully prepare students for entry into the AI-enhanced workplace. Are your students ready?

The urgent task facing those of us who teach and advise students, whether they be degree program or certificate seeking, is to ensure that they are prepared to enter (or re-enter) the workplace with skills and knowledge that are relevant to 2025 and beyond. One of the first skills to cultivate is an understanding of what kinds of services this emerging technology can provide to enhance the worker’s productivity and value to the institution or corporation.

Given that short period of time, coupled with the need to cover the scheduled information in the syllabus, I recommend that we consider merging AI use into authentic assignments and assessments, supplementary modules, and other resources to prepare for AI.


Learning Design in the Era of Agentic AI — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to design online async learning experiences that learners can’t afford to delegate to AI agents

The point I put forward was that the problem is not AI’s ability to complete online async courses, but that online async courses courses deliver so little value to our learners that they delegate their completion to AI.

The harsh reality is that this is not an AI problem — it is a learning design problem.

However, this realisation presents us with an opportunity which we overall seem keen to embrace. Rather than seeking out ways to block AI agents, we seem largely to agree that we should use this as a moment to reimagine online async learning itself.



8 Schools Innovating With Google AI — Here’s What They’re Doing — from forbes.com by Dan Fitzpatrick

While fears of AI replacing educators swirl in the public consciousness, a cohort of pioneering institutions is demonstrating a far more nuanced reality. These eight universities and schools aren’t just experimenting with AI, they’re fundamentally reshaping their educational ecosystems. From personalized learning in K-12 to advanced research in higher education, these institutions are leveraging Google’s AI to empower students, enhance teaching, and streamline operations.


Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

  • Research and analysis
  • Communication efficiency
  • Multimedia creation

AI tactics that work surprisingly well 

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.

 
 

Who does need college anymore? About that book title … — from Education Design Lab

As you may know, Lab founder Kathleen deLaski just published a book with a provocative title: Who Needs College Anymore? Imagining a Future Where Degrees Won’t Matter.

Kathleen is asked about the title in every media interview, before and since the Feb. 25 book release. “It has generated a lot of questions,” she said in our recent book chat. “I tell people to focus on the word, ‘who.’ Who needs college anymore? That’s in keeping with the design thinking frame, where you look at the needs of individuals and what needs are not being met.”

In the same conversation, Kathleen reminded us that only 38% of American adults have a four-year degree. “We never talk about the path to the American dream for the rest of folks,” she said. “We currently are not supporting the other really interesting pathways to financial sustainability — apprenticeships, short-term credentials. And that’s really why I wrote the book, to push the conversation around the 62% of who we call New Majority Learners at the Lab, the people for whom college was not designed.” Watch the full clip

She distills the point into one sentence in this SmartBrief essay:  “The new paradigm is a ‘yes and’ paradigm that embraces college and/or other pathways instead of college or bust.”

What can colleges do moving forward?
In this excellent Q&A with Inside Higher Ed, Kathleen shares her No. 1 suggestion: “College needs to be designed as a stepladder approach, where people can come in and out of it as they need, and at the very least, they can build earnings power along the way to help afford a degree program.”

In her Hechinger Report essay, Kathleen lists four more steps colleges can take to meet the demand for more choices, including “affordability must rule.”

From white-collar apprenticeships and micro-credential programs at local community colleges to online bootcamps, self-instruction using YouTube, and more—students are forging alternative paths to GREAT high-paying jobs. (source)

 

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.

 

Law Prawfs Statement Regarding an Urgent Constitutional Crisis — from thefacultylounge.org
Over 400 law professors have signed the Call to Urgency below. The authors invite others to join in here.

A CALL TO URGENCY

The opening weeks of the second Trump administration convince us, as law professors who have spent years studying the American legal system, that we are beginning to see unfold the gravest threat to the rule of law and its constituent principles – the separation of governmental powers, the independence of prosecutorial authority, the inviolability of human rights, the transparency of government action, and the sanctity of constitutional accountability itself – ever presented in our lifetimes. The president’s and his associates’ actions, and threats of action, profoundly undermine the bedrock principle of our federal government system – that the Chief Executive and his agents are constrained by the United States Constitution. The fundamental guardrails of our constitutional democracy itself are threatened and notably battered. They are, as we write, at risk of complete collapse.

 
 

How to Make Learning as Addictive as Social Media | Duolingo’s Luis Von Ahn | TED — from youtube.com; via Kamil Banc at AI Adopter

When technologist Luis von Ahn was building the popular language-learning platform Duolingo, he faced a big problem: Could an app designed to teach you something ever compete with addictive platforms like Instagram and TikTok? He explains how Duolingo harnesses the psychological techniques of social media and mobile games to get you excited to learn — all while spreading access to education across the world.
.

 

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:

 


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:


 

Five things to know before you launch a research podcast — from timeshighereducation.com by David Allan  and Andrew Murray
Starting a podcast can open up your research to a new audience. David Allan and Andrew Murray show how

Launching a podcast isn’t necessarily difficult. Sustaining it, on the other hand, is difficult. You’re entering a crowded market – it’s estimated that there are more than 4 million of them – and audience share is far from equal. An alarmingly high number fail to make it past their third episode before being scrapped, and the vast majority put out fewer than 20 episodes.

Despite these challenges, podcasts can be an astonishingly effective tool to promote research or academic knowledge. If you avoid the many pitfalls, you have a communication tool with full control of the message; a tool that exists in perpetuity, drawing attention to the work that you do.

Here, a highly experienced podcast producer and associate lecturer at the University of the West of Scotland and an award-winning former broadcast journalist draw on their experiences to share advice on how to successfully launch a research podcast.


Also from timeshighereducation.com:

An introvert’s guide to networking — from by Yalinu Poya
For academics, networking can greatly enhance your career. But if the very idea fills you with dread, Yalinu Poya offers her advice for putting yourself out there

In academia, meeting the right person can lead to a research collaboration, or it could lead to your work being shared with someone who can use it to make a difference. It could lead to public speaking opportunities or even mentorship. It all goes towards your long-term success.

For some of us, the idea of putting yourself out there in that way – of making an active effort to meet new people – is terrifying.

 

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.
.

Why the gap? Well, one explanation is that faculty lack institutional support.

The survey reveals that…

  • 80% of faculty don’t find their institutional AI guidelines comprehensive [p. 32]
  • 80% say their institutions haven’t made clear how AI can be used in teaching [p. 33]
  • The top barrier to AI adoption, at 40%? “I don’t have time or resources to explore AI” [p. 9]
  • The second-highest barrier, at 38%? “I am not sure how to use AI in my teaching” [p. 9]

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:

  • What AI is
  • What those techs can offer
  • What the LMS vendors are doing in this regard
  • and ideas on how to use AI in one’s teaching 
 

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:

  1. Break your own AI policies before you implement them.
  2. Fund your failures.
  3. Resist the pilot program. …
  4. Host Anti-Tech Tech Talks
  5. …+ 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.

 
© 2025 | Daniel Christian