Higher education has a trust problem. In the past ten years, the share of Americans who are confident in higher education has dropped from 57 percent to 36 percent.
Colleges and universities need to show that they understand and care about students, faculty, staff, and community members, AND they need to work efficiently and effectively.
Technology leaders can help. The 2025 EDUCAUSE Top 10 describes how higher education technology and data leaders and professionals can help to restore trust in the sector by building competent and caring institutions and, through radical collaboration, leverage the fulcrum of leadership to maintain balance between the two.
The Uberfication of Higher Ed — from evolllution.com by Robert Ubell | Vice Dean Emeritus of Online Learning in the School of Engineering, New York University As the world of work increasingly relies on the gig economy, higher ed is no different. Many institutions seek to drive down labor costs by hiring contingent works, thereby leaving many faculty in a precarious position and driving down the quality of education.
While some of us are aware that higher ed has been steadily moving away from employing mostly full-time, tenured and tenure-track faculty, replacing them with a part-time, contingent academic workforce, the latest AAUP report issued this summer shows the trend is accelerating. Precarious college teachers have increased by nearly 300,000 over the last decade, as conventional faculty employment stays pretty much flat. It’s part of a national trend in the wider economy that replaces permanent workers with lower paid, contingent staff—members of what we now call the gig economy.
The wide disparity is among the most glaring dysfunctions—along with vast student debt, falling enrollment, rising tuition and other dangers afflicting higher education—but it’s the least acknowledged. Rarely, if ever, does it take its place among the most troubling ails of academic life. It’s a silent disease, its symptoms largely ignored for over half a century.
Do families who send their kids to college, paying increasingly stiff tuition, realize that most of the faculty at our universities are as precarious as Uber drivers?
… Everyone at the table was taken aback, totally surprised, a sign—even if anecdotal—that this dirty secret is pretty safe. Mass participation of contingent faculty at our universities remains largely obscure, wrapped in a climate of silence, with adjunct faculty perpetuating the quiet by leaving their students mostly uninformed about their working conditions.
The TLDR here is that, as useful as popular AI tools are for learners, as things stand they only enable us to take the very first steps on what is a long and complex journey of learning.
AI tools like ChatGPT 4o, Claude 3.5 & NotebookLM can help to give us access to information but (for now at least) the real work of learning remains in our – the humans’ – hands.
To which Anna Mills had a solid comment:
It might make a lot of sense to regulate generated audio to require some kind of watermark and/or metadata. Instructors who teach online and assign voice recordings, we need to recognize that these are now very easy and free to auto-generate. In some cases we are assigning this to discourage students from using AI to just autogenerate text responses, but audio is not immune.
1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:
2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?
Explain This Design…
Show Me Alternatives…
Challenge My Assumptions…
Learning Science Insights…
By reimagining the role of AI in this way, we would…
OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.
I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.
As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?
This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?
With enrollment trends improving and state appropriations increasing, the community college sector has reason for “optimism,” according to a recent report from S&P Global Ratings.
For 2023, median full-time equivalent enrollment, at 5,439 students, was down just 0.3% from 2021 and up nearly 8.1% from the previous year, S&P found among the roughly 200 community colleges it rates. That comes after enrollment in the sector fell 7.7% year over year in 2022,.
Meanwhile, median state appropriations per FTE student for the sector increased 19.1% to $4,930 between 2021 and 2023, analysts found.
U.S. colleges face a “new normal” and accelerated existing challenges in the wake of the COVID-19 pandemic, including constrained operations and heavy competition, a recent report from S&P Global Ratings found.
Between 2018 and 2023, operating margin rates fell from 0.8% to -0.1% amid rising costs to colleges, according to S&P. Meanwhile, median tuition discount rates at private colleges rose by more than 5 percentage points, to 44.4%, in that period, putting pressure on college revenues.
From 2019 through the second quarter of 2024, the ratings agency issued 126 credit downgrades for the higher ed sector, compared to 62 upgrades, per the report.
5 ways colleges can improve outreach to rural students — from highereddive.com by Laura Spitalniak Students from small towns help strengthen campus communities, said panelists at the National Association for College Admission Counseling’s conference.
We cannot just swoop in and take the best and brightest and just say, ‘Oh, good job us.’ We want this to be a two-way highway, not a one-way brain drain.
Marjorie Betley Deputy director of admissions at the University of Chicago
A Trauma-Informed Teaching Framework for Stewards— from scholarlyteacher.com by Jeannette Baca, New Mexico Highlands University; Debbie Gonzalez, California State Polytechnic University, Humboldt; Jamie Langlois, Grand Valley State University; and Mary Kirk, Winona State University
Using the Trauma-Informed Community of Inquiry (T-I CoI) framework as a pedagogical design helped us address students’ emotional stress and facilitated cognitive growth and connection to the learning process. It also provided an opportunity to create a sense of community within an online learning environment. When we returned to in-person instruction, the model continued to be beneficial.
The average student borrows over $30,000 to pursue a bachelor’s degree.
A total of 42.8 million borrowers have federal student loan debt.
It may take borrowers close to 20 years to pay off their student loans.
From DSC: In other words, we are approaching the end of the line in terms of following the status quo within higher education. Institutions of traditional higher education can no longer increase their cost of tuition by significantly more than the rate of inflation. Increasingly, K-12 students (and families) are looking for other pathways and alternatives. Higher ed better stop trying to change around the edges…they need new, more cost-effective business models as well as being able to be much more responsive in terms of their curricula.
We emerged with two guiding principles. First, we had learned that certain environments—in particular, those that cause sensory distraction—can more significantly impact neurodivergent users. Therefore, our design should diminish distractions by mitigating, when possible, noise, visual contrast, reflective surfaces and crowds. Second, we understood that we needed a design that gave neurodivergent users the agency of choice.
The importance of those two factors—a dearth of distraction and an abundance of choice—was bolstered in early workshops with the classroom committee and other stakeholders, which occurred at the same time we were conducting our research. Some things didn’t come up in our research but were made quite clear in our conversations with faculty members, students from the neurodivergent community and other stakeholders. That feedback greatly influenced the design of the Young Classroom.
We ended up blending the two concepts. The main academic space utilizes traditional tables and chairs, albeit in a variety of heights and sizes, while the peripheral classroom spaces use an array of less traditional seating and table configurations, similar to the radical approach.
This post summarises a fascinating webinar I had with Rachel Higginson discussing the elements of building belonging in our settings.
We know that belonging is important and one of the ways to make this explicit in our settings is to consider what it takes to cultivate an inclusive environment where each individual feels valued and understood.
Rachel has spent several years working with young people, particularly those on the periphery of education to help them back into mainstream education and participating in class, along with their peers.
Rachel’s work helping young people to integrate back into education resulted in schools requesting support and resources to embed inclusion within their settings. As a result, Finding My Voice has evolved into a broader curriculum development framework.
People started discussing what they could do with Notebook LM after Google launched the audio overview, where you can listen to 2 hosts talking in-depth about the documents you upload. Here are what it can do:
Summarization: Automatically generate summaries of uploaded documents, highlighting key topics and suggesting relevant questions.
Question Answering: Users can ask NotebookLM questions about their uploaded documents, and answers will be provided based on the information contained within them.
Idea Generation: NotebookLM can assist with brainstorming and developing new ideas.
Source Grounding: A big plus against AI chatbot hallucination, NotebookLM allows users to ground the responses in specific documents they choose.
…plus several other items
The posting also lists several ideas to try with NotebookLM such as:
Idea 2: Study Companion
Upload all your course materials and ask NotebookLM to turn them into Question-and-Answer format, a glossary, or a study guide.
Get a breakdown of the course materials to understand them better.
“Google’s AI note-taking app NotebookLM can now explain complex topics to you out loud”
With more immersive text-to-video and audio products soon available and the rise of apps like Suno AI, how we “experience” Generative AI is also changing from a chatbot of 2 years ago, to a more multi-modal educational journey. The AI tools on the research and curation side are also starting to reflect these advancements.
1. Upload a variety of sources for NotebookLM to use.
You can use …
websites
PDF files
links to websites
any text you’ve copied
Google Docs and Slides
even Markdown
You can’t link it to YouTube videos, but you can copy/paste the transcript (and maybe type a little context about the YouTube video before pasting the transcript).
2. Ask it to create resources. 3. Create an audio summary. 4. Chat with your sources.
5. Save (almost) everything.
I finally tried out Google’s newly-announced NotebookLM generative AI application. It provides a set of LLM-powered tools to summarize documents. I fed it my dissertation, and am surprised at how useful the output would be.
The most impressive tool creates a podcast episode, complete with dual hosts in conversation about the document. First – these are AI-generated hosts. Synthetic voices, speaking for synthetic hosts. And holy moly is it effective. Second – although I’d initially thought the conversational summary would be a dumb gimmick, it is surprisingly powerful.
4 Tips for Designing AI-Resistant Assessments — from techlearning.com by Steve Baule and Erin Carter As AI continues to evolve, instructors must modify their approach by designing meaningful, rigorous assessments.
As instructors work through revising assessments to be resistant to generation by AI tools with little student input, they should consider the following principles:
Incorporate personal experiences and local content into assignments
Ask students for multi-modal deliverables
Assess the developmental benchmarks for assignments and transition assignments further up Bloom’s Taxonomy
He added that he wants to avoid a global “AI divide” and that Google is creating a $120 million Global AI Opportunity Fund through which it will “make AI education and training available in communities around the world” in partnership with local nonprofits and NGOs.
Google on Thursday announced new updates to its AI note-taking and research assistant, NotebookLM, allowing users to get summaries of YouTube videos and audio files and even create sharable AI-generated audio discussions…
As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.
This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.
Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education
The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.
AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.
This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.
My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?
Here’s where we are in September, 2024:
…
Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby, Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)
As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.
AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.
86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.
The Post-AI Instructional Designer— from drphilippahardman.substack.com by Dr. Philippa Hardman How the ID role is changing, and what this means for your key skills, roles & responsibilities
Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.
Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.
Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.
The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.
An example way to leverage AI:
How to Leverage AI for Identity Inclusion Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.
Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.
Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.
To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.
Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development.Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.
Change blindness — from oneusefulthing.org by Ethan Mollick 21 months later
I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.
Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:
What are you doing?
Why are you doing it that way?
How could you change that workflow with AI?
Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”
So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.
Over 500 private, nonprofit four-year institutions have closed in the last 10 years, according to the State Higher Education Executive Officers Association. That is three times what it was in the decade prior. Rachel Burns, a senior policy analyst at SHEEO, estimates at least 1.25 million students were affected by these closures. (Many more for-profit institutions have closed in this period as well.)
Around two-thirds of incoming college seniors said college has significantly contributed to their ability to land a well–paying job, according to a new survey from job platform Handshake.
A slightly higher share, 72%, said higher education has appreciably improved their ability to secure a meaningful job. And 85% of surveyed seniors said college significantly helped them understand their own career goals.
College seniors also indicated that higher education has helped them beyond their career development. According to the survey, 88% said college significantly contributed to their personal growth.
We are excited to announce the publication of the 2024 US Instructor Survey. This survey, adapted from our longstanding US Faculty Survey, provides a detailed snapshot of over 5,200 faculty members from different disciplines, institution types, ages, and titles across the US at four-year institutions. This new report offers a comprehensive overview of how college instructors across the country are navigating and shaping the current educational landscape.
Overall, we heard that instructors are increasingly adopting innovative, technology-driven teaching methods, while recognizing the critical role libraries play in supporting student success. The growing use of open educational resources (OERs) reflects a commitment to affordable education, though fewer instructors create their own. Additionally, strong institutional support remains essential for effective teaching, particularly IT and with pedagogical practices. Below we share several key findings:
But starting with the 2013-14 academic year, a whopping 726 degree-granting institutions closed through the 2022-23 school year, according to the National Center for Education Statistics. That means in just nine years, 15 percent of the-then 4,724 degree-granting colleges or universities closed. … Ultimately, after all, the prediction is a result of business model failure, in which rising expenses outpace revenue, as the students cease to enroll or have the capacity to pay enough.
But non-profit institutions are in their own world of hurt as well. According to Higher Ed Dive, 18 have announced their closure this year so far. But 141 closed between 2013-14 and 2022-23—or roughly 8.4 percent.
Survey: Over Half of Rising Seniors Feel Pessimistic About Starting Their Careers — from insidehighered.com by Ahsley Mowreader New data from Handshake finds 57 percent of the Class of 2025 have low expectations for their future after graduation, largely tied to a competitive job market, student loan debt and current political climate.
Entering senior year can be a stressful time for college students as they prepare for their next step after graduation. Inside Higher Ed’s 2024 Student Voice survey found 68 percent of fourth-year students (n=703) are at least somewhat stressed when they think about their life postgraduation, with 25 percent feeling “extremely stressed.”
This year’s graduating class is feeling less hopeful than their peers before them, with almost three in five students sharing that they feel pessimistic about their immediate future, according to new data from Handshake.
The results highlight a challenging job market for new graduates, the role of affordability in higher education and how institutions are supporting students as they launch into careers.
AI is welcomed by those with dyslexia, and other learning issues, helping to mitigate some of the challenges associated with reading, writing, and processing information. Those who want to ban AI want to destroy the very thing that has helped most on accessibility. Here are 10 ways dyslexics, and others with issues around text-based learning, can use AI to support their daily activities and learning.
Are U.S. public schools lagging behind other countries like Singapore and South Korea in preparing teachers and students for the boom of generative artificial intelligence? Or are our educators bumbling into AI half-blind, putting students’ learning at risk?
Or is it, perhaps, both?
Two new reports, coincidentally released on the same day last week, offer markedly different visions of the emerging field: One argues that schools need forward-thinking policies for equitable distribution of AI across urban, suburban and rural communities. The other suggests they need something more basic: a bracing primer on what AI is and isn’t, what it’s good for and how it can all go horribly wrong.
Bite-Size AI Content for Faculty and Staff— from aiedusimplified.substack.com by Lance Eaton Another two 5-tips videos for faculty and my latest use case: creating FAQs!
Despite possible drawbacks, an exciting wondering has been—What if AI was a tipping point helping us finally move away from a standardized, grade-locked, ranking-forced, batched-processing learning model based on the make believe idea of “the average man” to a learning model that meets every child where they are at and helps them grow from there?
I get that change is indescribably hard and there are risks. But the integration of AI in education isn’t a trend. It’s a paradigm shift that requires careful consideration, ongoing reflection, and a commitment to one’s core values. AI presents us with an opportunity—possibly an unprecedented one—to transform teaching and learning, making it more personalized, efficient, and impactful. How might we seize the opportunity boldly?
California and NVIDIA Partner to Bring AI to Schools, Workplaces — from govtech.com by Abby Sourwine The latest step in Gov. Gavin Newsom’s plans to integrate AI into public operations across California is a partnership with NVIDIA intended to tailor college courses and professional development to industry needs.
California Gov. Gavin Newsom and tech company NVIDIA joined forces last week to bring generative AI (GenAI) to community colleges and public agencies across the state. The California Community Colleges Chancellor’s Office (CCCCO), NVIDIA and the governor all signed a memorandum of understanding (MOU) outlining how each partner can contribute to education and workforce development, with the goal of driving innovation across industries and boosting their economic growth.
Listen to anything on the go with the highest-quality voices — from elevenlabs.io; via The Neuron
The ElevenLabs Reader App narrates articles, PDFs, ePubs, newsletters, or any other text content. Simply choose a voice from our expansive library, upload your content, and listen on the go.
Per The Neuron
Some cool use cases:
Judy Garland can teach you biology while walking to class.
James Dean can narrate your steamy romance novel.
Sir Laurence Olivier can read you today’s newsletter—just paste the web link and enjoy!
Why it’s important: ElevenLabs shared how major Youtubers are using its dubbing services to expand their content into new regions with voices that actually sound like them (thanks to ElevenLabs’ ability to clone voices).
Oh, and BTW, it’s estimated that up to 20% of the population may have dyslexia. So providing people an option to listen to (instead of read) content, in their own language, wherever they go online can only help increase engagement and communication.
How Generative AI Improves Parent Engagement in K–12 Schools — from edtechmagazine.com by Alexadner Slagg With its ability to automate and personalize communication, generative artificial intelligence is the ideal technological fix for strengthening parent involvement in students’ education.
As generative AI tools populate the education marketplace, the technology’s ability to automate complex, labor-intensive tasks and efficiently personalize communication may finally offer overwhelmed teachers a way to effectively improve parent engagement.
… These personalized engagement activities for students and their families can include local events, certification classes and recommendations for books and videos. “Family Feed might suggest courses, such as an Adobe certification,” explains Jackson. “We have over 14,000 courses that we have vetted and can recommend. And we have books and video recommendations for students as well.”
Including personalized student information and an engagement opportunity makes it much easier for parents to directly participate in their children’s education.
Will AI Shrink Disparities in Schools, or Widen Them? — edsurge.com by Daniel Mollenkamp Experts predict new tools could boost teaching efficiency — or create an “underclass of students” taught largely through screens.
The Burden of Misunderstanding — from onedtech.philhillaa.com by Phil Hill How ED’s outdated consumer-protection view of online education could lead to bureaucratic burden on every online course in US higher ed
Time to Comment There are plenty of other points to be made on this proposed rule:
the lack of evidence supporting the treatment of online ed differently than f2f or hybrid;
the redefinition of regular and substantive interaction;
the impact of this simplification rule actually complicating matters for compliance; and
the risk of auto-withdrawal for 14-day inactivity periods, etc.
For now, I wanted to be more precise on what I believe is a misunderstood compliance burden of ED’s proposed rule, and ED’s inability to listen to feedback from colleges and universities and associations representing them. And that while the details of this proposed rule might seem arcane, it will have a major impact across higher ed.
It is very important to note that we are in the middle of the public comment period for these proposed rules, and that ED should hear directly from colleges and universities about the impact of the proposed rules. You can comment here through next Friday (August 23rd).
From DSC: Phil brings up numerous excellent points in the above posting. If the Department of Education’s (ED’s) proposed rules on online attendance taking get finalized, the impacts could be huge — and negative/costly in several areas. Faculty members, directors and staff of teaching and learning centers, directors of online programs, provosts and other members of administrations, plus other relevant staff should comment– NOW — before the comment period ends next Friday (August 23rd).
Using generative artificial intelligence (GenAI) tools such as ChatGPT, Gemini, or CoPilot as intelligent assistants in instructional design can significantly enhance the scalability of course development. GenAI can significantly improve the efficiency with which institutions develop content that is closely aligned with the curriculum and course objectives. As a result, institutions can more effectively meet the rising demand for flexible and high-quality education, preparing a new generation of future professionals equipped with the knowledge and skills to excel in their chosen fields.1 In this article, we illustrate the uses of AI in instructional design in terms of content creation, media development, and faculty support. We also provide some suggestions on the effective and ethical uses of AI in course design and development. Our perspectives are rooted in medical education, but the principles can be applied to any learning context.
… Table 1 summarizes a few low-hanging fruits in AI usage in course development. .
Table 1. Types of Use of GenAI in Course Development
Practical Use of AI
Use Scenarios and Examples
Inspiration
Exploring ideas for instructional strategies
Exploring ideas for assessment
Course mapping
Lesson or unit content planning
Supplementation
Text to audio
Transcription for audio
Alt text auto-generation
Design optimization (e.g., using Microsoft PPT Design)
10 Ways Artificial Intelligence Is Transforming Instructional Design — from er.educause.edu by Rob Gibson Artificial intelligence (AI) is providing instructors and course designers with an incredible array of new tools and techniques to improve the course design and development process. However, the intersection of AI and content creation is not new.
I have been telling my graduate instructional design students that AI technology is not likely to replace them any time soon because learning and instruction are still highly personalized and humanistic experiences. However, as these students embark on their careers, they will need to understand how to appropriately identify, select, and utilize AI when developing course content. Examples abound of how instructional designers are experimenting with AI to generate and align student learning outcomes with highly individualized course activities and assessments. Instructional designers are also using AI technology to create and continuously adapt the custom code and power scripts embedded into the learning management system to execute specific learning activities.Footnote1 Other useful examples include scripting and editing videos and podcasts.
Here are a few interesting examples of how AI is shaping and influencing instructional design. Some of the tools and resources can be used to satisfy a variety of course design activities, while others are very specific.
The world of a medieval stone cutter and a modern instructional designer (ID) may seem separated by a great distance, but I wager any ID who upon hearing the story I just shared would experience an uneasy sense of déjà vu. Take away the outward details, and the ID would recognize many elements of the situation: the days spent in projects that fail to realize the full potential of their craft, the painful awareness that greater things can be built, but are unlikely to occur due to a poverty of imagination and lack of vision among those empowered to make decisions.
Finally, there is the issue of resources. No stone cutter could ever hope to undertake a large-scale enterprise without a multitude of skilled collaborators and abundant materials. Similarly, instructional designers are often departments of one, working in scarcity environments, with limited ability to acquire resources for ambitious projects and — just as importantly — lacking the authority or political capital needed to launch significant initiatives. For these reasons, instructional design has long been a profession caught in an uncomfortable stasis, unable to grow, evolve and achieve its full potential.
That is until generative AI appeared on the scene. While the discourse around AI in education has been almost entirely about its impact on teaching and assessment, there has been a dearth of critical analysis regarding AI’s potential for impacting instructional design.
We are at a critical juncture for AI-augmented learning. We can either stagnate, missing opportunities to support learners while educators continue to debate whether the use of generative AI tools is a good thing, or we can move forward, building a transformative model for learning akin to the industrial revolution’s impact.
Too many professional educators remain bound by traditional methods. The past two years suggest that leaders of this new learning paradigm will not emerge from conventional educational circles. This vacuum of leadership can be filled, in part, by instructional designers, who are prepared by training and experience to begin building in this new learning space.
