Online higher education is projected to pass an impressive if little-noticed milestone this year: For the first time, more American college students will be learning entirely online than will be learning 100 percent in person.
Online higher education is projected to pass an impressive if little-noticed milestone this year: For the first time, more American college students will be learning entirely online than will be learning 100 percent in person.
Bittner’s confusion about the price is widespread. Eighty percent of Americans think online learning after high school should cost less than in-person programs, according to a 2024 survey of 1,705 adults by New America.
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.
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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.
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.
AI Agents are now deeply embedded in everyday life and?quickly transforming industry after industry. The global AI market is expected to explode up to $1.59 trillion by 2030! That is a?ton of intelligent agents operating behind the curtains.
That’s why in this article, we explore?20 real-life AI Agents that are causing a stir today.
?In the latest edition of Andreessen Horowitz’s “Top 100 Gen AI Consumer Apps,” the generative AI landscape has undergone significant shifts.
Notably, DeepSeek has emerged as a leading competitor to ChatGPT, while AI video models have advanced from experimental stages to more reliable tools for short clips. Additionally, the rise of “vibecoding” is broadening the scope of AI creators.
The report also introduces the “Brink List,” highlighting ten companies poised to enter the top 100 rankings.?
I do these comparisons frequently to measure the improvements in different models for text or image to video prompts. I hope it is helpful for you, as well!
I included 6 models for an image to video comparison:
Pika 2.1 (I will do one with Pika’s new 2.2 model soon)
This time I used an image generated with Magnific’s new Fluid model ( Google DeepMind’s Imagen + Mystic 2.5 ), and the same… pic.twitter.com/rH1gRbhynB
Why Smart Companies Are Granting AI Immunity to Their Employees — from builtin.com by Matt Almassian Employees are using AI tools whether they’re authorized or not. Instead of cracking down on AI usage, consider developing an AI amnesty program. Learn more.
But the smartest companies aren’t cracking down. They’re flipping the script. Instead of playing AI police, they’re launching AI amnesty programs, offering employees a safe way to disclose their AI usage without fear of punishment. In doing so, they’re turning a security risk into an innovation powerhouse.
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Before I dive into solutions, let’s talk about what keeps your CISO or CTO up at night. Shadow AI isn’t just about unauthorized tool usage — it’s a potential dirty bomb of security, compliance and operational risks that could explode at any moment.
… 6 Steps to an AI Amnesty Program
Build your AI governance foundation.
Transform your IT department from gatekeeper to innovation partner.
What they discovered might change how you interact with AI:
Consistency is a major problem. The researchers asked the same questions 100 times and found models often give different answers to the same question.
Formatting matters a ton. Telling the AI exactly how to structure its response consistently improved performance.
Politeness is… complicated. Saying “please” helped the AI answer some questions but made it worse at others. Same for being commanding (“I order you to…”).
Standards matter. If you need an AI to be right 100% of the time, you’re in trouble.
That’s also why we think you, an actual human, should always place yourself as a final check between whatever your AI creates and whatever goes out into the world.
Leave it to Manus “Manus is a general AI agent that bridges minds and actions: it doesn’t just think, it delivers results. Manus excels at various tasks in work and life, getting everything done while you rest.”
From DSC: What could possibly go wrong?!
AI Search Has A Citation Problem — from cjr.org (Columbia Journalism Review) by Klaudia Ja?wi?ska and Aisvarya Chandrasekar We Compared Eight AI Search Engines. They’re All Bad at Citing News.
We found that…
Chatbots were generally bad at declining to answer questions they couldn’t answer accurately, offering incorrect or speculative answers instead.
Premium chatbots provided more confidently incorrect answers than their free counterparts.
Multiple chatbots seemed to bypass Robot Exclusion Protocol preferences.
Generative search tools fabricated links and cited syndicated and copied versions of articles.
Content licensing deals with news sources provided no guarantee of accurate citation in chatbot responses.
Our findings were consistent with our previous study, proving that our observations are not just a ChatGPT problem, but rather recur across all the prominent generative search tools that we tested.
Hundreds of AI tools emerge every week. I’ve picked five new ones worth exploring. They’re free to try, easy to use, and signal new directions for useful AI.
Example:
Career Dreamer
A playful way to explore career possibilities with AI
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.
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
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.
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.
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
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.
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….
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.
… Implications for Educators and Developers
For Educators:
Combine ChatGPT with Structured Activities: …
Use ChatGPT as a Supplement, Not a Replacement:…
Promote Self-Reflection and Evaluation:
For Developers:
Reimagine AI for Reflection-First Design: …
Develop Tools that Foster Critical Thinking: …
Integrate Adaptive Support: …
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
to create sophisticated assessments that promote learning
to develop clearer and more effective assignment instructions
to provide more constructive feedback on student work, and
to support student learning through guided tutoring
Now is the time for visionary leadership in education.The era of artificial intelligence is reshaping the demands on education systems. Rigid policies, outdated curricula, and reliance on obsolete metrics are failing students. A recent survey from Resume Genius found that graduates lack skills in communication, collaboration, and critical thinking. Consequently, there is a growing trend in companies hiring candidates based on skills instead of traditional education or work experience. This underscores the urgent need for educational leaders to prioritize adaptability and innovation in their systems. Educational leaders must embrace a transformative approach to keep pace.
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[Heretical leaders] bring courage, empathy, and strategic thinking to reimagine education’s potential. Here are their defining characteristics:
Visionary Thinking: They identify bold, innovative paths to progress.
Courage to Act: These leaders take calculated risks to overcome resistance and inertia.
Relentless Curiosity: They challenge assumptions and seek better alternatives.
Empathy for Stakeholders: Understanding the personal impact of change allows them to lead with compassion.
Strategic Disruption: Their deliberate actions ensure systemic improvements.
These qualities enable Heretical leaders to reframe challenges as opportunities and drive meaningful change.
From DSC: Readers of this blog will recognize that I believe visionary leadership is extremely important — in all areas of our society, but especially within our learning ecosystems. Vision trumps data, at least in my mind. There are times when data can be used to support a vision, but having a powerful vision is more lasting and impactful than relying on data to drive the organization.
So while I’d vote for a different term other than “heretical leaders,” I get what Dan is saying and I agree with him. Such leaders are going against the grain. They are swimming upstream. They are espousing perspectives that others often don’t buy into (at least initially or for some time).
Such were the leaders who introduced online learning into the K-16 educational systems back in the late ’90s and into the next two+ decades. The growth of online-based learning continues and has helped educate millions of people. Those leaders and the people who worked for such endeavors were going against the grain.
We haven’t seen the end point of online-based learning. I think it will become even more powerful and impactful when AI is used to determine which jobs are opening up, and which skills are needed for those jobs, and then provide a listing of sources of where one can obtain that knowledge and develop those skills. People will be key in this vision. But so will AI and personalized learning. It will be a collaborative effort.
By the way, I am NOT advocating for using AI to outsource our thinking. Also, having basic facts and background knowledge in a domain is critically important, especially to use AI effectively. But we should be teaching students about AI (as we learn more about it ourselves). We should be working collaboratively with our students to understand how best to use AI. It’s their futures at stake.
“I mean, that’s what I’ll always want for my own children and, frankly, for anyone’s children,” Khan said. “And the hope here is that we can use artificial intelligence and other technologies to amplify what a teacher can do so they can spend more time standing next to a student, figuring them out, having a person-to-person connection.”
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“After a week you start to realize, like, how you can use it,” Brockman said. “That’s been one of the really important things about working with Sal and his team, to really figure out what’s the right way to sort of bring this to parents and to teachers and to classrooms and to do that in a way…so that the students really learn and aren’t just, you know, asking for the answers and that the parents can have oversight and the teachers can be involved in that process.”
More than 100 colleges and high schools are turning to a new AI tool called Nectir, allowing teachers to create a personalized learning partner that’s trained on their syllabi, textbooks, and assignments to help students with anything from questions related to their coursework to essay writing assistance and even future career guidance.
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With Nectir, teachers can create an AI assistant tailored to their specific needs, whether for a single class, a department, or the entire campus. There are various personalization options available, enabling teachers to establish clear boundaries for the AI’s interactions, such as programming the assistant to assist only with certain subjects or responding in a way that aligns with their teaching style.
“It’ll really be that customized learning partner. Every single conversation that a student has with any of their assistants will then be fed into that student profile for them to be able to see based on what the AI thinks, what should I be doing next, not only in my educational journey, but in my career journey,” Ghai said.
How Will AI Influence Higher Ed in 2025? — from insidehighered.com by Kathryn Palmer No one knows for sure, but Inside Higher Ed asked seven experts for their predictions.
As the technology continues to evolve at a rapid pace, no one knows for sure how AI will influence higher education in 2025. But several experts offered Inside Higher Ed their predictions—and some guidance—for how colleges and universities will have to navigate AI’s potential in the new year.
In the short term, A.I. will help teachers create lesson plans, find illustrative examples and generate quizzes tailored to each student. Customized problem sets will serve as tools to combat cheating while A.I. provides instant feedback.
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In the longer term, it’s possible to imagine a world where A.I. can ingest rich learner data and create personalized learning paths for students, all within a curriculum established by the teacher. Teachers can continue to be deeply involved in fostering student discussions, guiding group projects and engaging their students, while A.I. handles grading and uses the Socratic method to help students discover answers on their own. Teachers provide encouragement and one-on-one support when needed, using their newfound availability to give students some extra care.
Let’s be clear: A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.
Today, I want to reflect on two recent OpenAI developments that highlight this evolution: their belated publication of advice for students on integrating AI into writing workflows, and last week’s launch of the full GPTo1 Pro version. When OpenAI released their student writing guide, there were plenty of snarky comments about how this guidance arrives almost a year after they thoroughly disrupted the educational landscape. Fair enough – I took my own side swipes initially. But let’s look at what they’re actually advising, because the details matter more than the timing.
Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.
That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil.
Faculty must have the time and support necessary to come to terms with this new technology and that requires us to change how we view professional development in higher education and K-12. We cannot treat generative AI as a one-off problem that can be solved by a workshop, an invited talk, or a course policy discussion. Generative AI in education has to be viewed as a continuum. Faculty need a myriad of support options each semester:
Course buyouts
Fellowships
Learning communities
Reading groups
AI Institutes and workshops
Funding to explore the scholarship of teaching and learning around generative AI
Education leaders should focus on integrating AI literacy, civic education, and work-based learning to equip students for future challenges and opportunities.
Building social capital and personalized learning environments will be crucial for student success in a world increasingly influenced by AI and decentralized power structures.
…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.
I assert that in the future, people will be able to see this information on a 24x7x365 basis.
Which jobs are in demand?
What skills do I need to do those jobs?
WHERE do I get/develop those skills?
And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.
BUT PEOPLE are the key! Oftentimes, we need to — and prefer to — learn with others!
The Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Ben Kornell, Alex Sarlin, Sarah Morin, and Laurence Holt A market map and database featuring 60+ use cases for GenAI in education and 300+ GenAI powered education tools.
Used thoughtfully, ChatGPT can be a powerful tool to help students develop skills of rigorous thinking and clear writing, assisting them in thinking through ideas, mastering complex concepts, and getting feedback on drafts.
There are also ways to use ChatGPT that are counterproductive to learning—like generating an essay instead of writing it oneself, which deprives students of the opportunity to practice, improve their skills, and grapple with the material.
For students committed to becoming better writers and thinkers, here are some ways to use ChatGPT to engage more deeply with the learning process.
The Big Idea: As employers increasingly seek out applicants with AI skills, community colleges are well-positioned to train up the workforce. Partnerships with tech companies, like the AI Incubator Network, are helping some colleges get the resources and funding they need to overhaul programs and create new AI-focused ones.
Along these lines also see:
Practical AI Training — from the-job.beehiiv.com by Paul Fain Community colleges get help from Big Tech to prepare students for applied AI roles at smaller companies.
Miami Dade and other two-year colleges try to be nimble by offering training for AI-related jobs while focusing on local employers. Also, Intel’s business struggles while the two-year sector wonders if Republicans will cut funds for semiconductor production.
In this conversation, Josh Bersin discusses the evolving landscape of AI platforms, particularly focusing on Microsoft’s positioning and the challenges of creating a universal AI agent. He delves into the complexities of government efficiency, emphasizing the institutional challenges faced in re-engineering government operations.
The conversation also highlights the automation of work tasks and the need for businesses to decompose job functions for better efficiency.
Bersin stresses the importance of expertise in HR, advocating for a shift towards full stack professionals who possess a broad understanding of various HR functions.
Finally, he addresses the impending disruption in Learning and Development (L&D) due to AI advancements, predicting a significant transformation in how L&D professionals will manage knowledge and skills.
New Partnership Offers Online Tutoring in Michigan Schools — from govtech.com via GSV The online education nonprofit Michigan Virtual has partnered with Stride Tutoring to offer remote academic support for students in 700 school districts as part of a statewide push to reverse pandemic learning loss.
Online education provider Michigan Virtual is working with a Virginia-based online tutoring company to increase access to personalized academic support for Michigan students, according to a news release last month. The partnership is in line with a statewide push to reverse pandemic learning loss through high-impact tutoring.
Speaking of education — but expanding the scope of this posting to a global scale:
While the conversation clearly focused on a continuing worldwide crisis in education, the UNESCO conference I participated in was different. It emphasized a topic of huge importance to improving student outcomes, and coincided with the release of a report detailing how effective leaders can make a big difference in the lives of children.
From DSC: Leadership is important, for sure. But being a leader in education is very difficult these days — there are many different (and high) expectations and agendas being thrown your way from a variety of shareholders. But I do appreciate those leaders who are trying to create effective learning ecosystems out there!
One more for high school students considering going to college…
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…
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).
