assessment

Here are my favorite back-to-school activities to strengthen learning — from retrievalpractice.org by Pooja K. Agarwal, Ph.D.

Welcome back to school! For most of us (myself included), the whirlwind of lesson prep, meetings, professional development—and of course, teaching—is here. Keep reading for my favorite back-to-school activities to engage students with retrieval practice during the first week of class.
…
It may (or may not) surprise you to know that my first day of class is full of retrieval practice. Even if you haven’t introduced content yet, use retrieval practice the first day or week of class. Here’s how, with quick activities you can adapt for K–12 students, higher ed courses, and all content areas:

Get students familiar with retrieval practice from day 1 with no-stakes trivia questions and warm up questions where everyone knows the answer (click here to download my free warm up slides)
Build a welcoming class culture with mnemonics to remember student names (spoiler alert: trying to memorize names with students’ LMS photos doesn’t work)
Jumpstart students’ prior knowledge with an engaging ungraded pre/post worksheet (check out an example of my worksheet online)
Boost students’ long-term learning from previous classes with a brain dump or two things activity in one minute or less
Make students’ break memorable with a simple question to model how we retrieve in everyday life

How to Teach a Good First Day of Class — by James Lang; via Dr. Pooja Agarwal’s posting above

What you can expect to find here:

I’ll start, as we academics so love to do, with a little bit of theory — specifically, four core principles that can help shape your planning for the first day of your course.
Next, I’ll cover the logistics of a successful first day, including managing the space and technology as well as getting to know your students.
To show you how to put the principles and the logistics into practice, I will provide examples of what a good set of first-day activities might look like in four disciplines.
I’ll finish with some suggestions for how to support the good work you have done on the first day with some follow-up activities.

7 Pieces of Advice for New Teachers — from edutopia.org by Brienne May
Focus on relationships with students and colleagues to make a good start to the year—and remember to ask for what you need.

Too often, teacher preparation programs are rich in theory but light on practical guidance. After working hard through my undergraduate classes, completing student teaching, and spending countless hours laminating and cutting, I still found myself on the first day of school, standing in front of a room full of expectant faces with eager eyes, and realized I had no idea what to do next. I didn’t know what to say to students in that moment, let alone how to survive the following 180 days. Twelve years later, I have collected a trove of advice I wish I could have shared with that fresh-faced teacher.

The Transient Information Effect: Why Great Explanations Don’t Always Stick — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
In this post, Dr. John Sweller describes how the Transient Information Effect can overload student working memory and what teachers can do about it.

Highlights:

The Transient Information Effect happens when important information disappears before learners can process and remember it.
Dr. John Sweller, who first studied the Transient Information Effect, answers our questions about this overlooked learning challenge.
Turning transient information into something students can revisit (like writing key steps on the board) can help explanations stick.

41 Elementary Classroom Jobs to Build Shared Responsibility and Community — from edutopia.org by Donna Paul
Classroom jobs help students feel seen, trusted, and excited to contribute to their classroom community.

Each fall, one of the first routines I introduce is our classroom job board. It’s more than a list of tasks—it helps students feel that they belong and have real roles in our shared space. Over the years, I’ve expanded beyond classic jobs like Line Leader and Pencil Sharpener to include creative roles with quirky titles that engage and resonate with students.

Here are the jobs that have helped my students feel seen, trusted, and excited to contribute.

Guiding Students to Overcome Learned Helplessness — from edutopia.org by Michelle Singh
New teachers can create an environment where students feel supported and understand that mistakes are part of the learning process.

Creating a Kid-Led Hall of Fame for Books — from edutopia.org by Eric Hall
Allowing elementary students to nominate and vote for their favorite books of the year can create a culture of celebration in the classroom.

When I started teaching, I remembered that conversation with my elementary school librarian. I thought, “Why should adults have all the fun?” I wanted my students to experience the excitement of recognizing books they thought were the best. And just like that, the Hallbery Awards were born and continued twice a year for over 15 years. (Why Hallbery? Because my last name is Hall.)

Understanding Diagnostic, Formative, and Summative Assessments — from edmentum.com

Today, we’re taking a look at the three primary forms of assessments—diagnostic, formative, and summative—with the goal of not only differentiating between them but also better understanding the purpose and potential power of each.

At their core, each of the three primary assessment types serves a distinct purpose. Diagnostic assessments are used before instruction to help identify where students are in their comprehension of academic content. Formative assessments are used while content is being taught to understand what students are picking up, to guide their learning, and to help teachers determine what to focus on moving forward. Summative assessments are used after instruction to evaluate the outcomes of student learning: what, or how much, they ultimately learned.

How one state revamped high school to reflect reality: Not everyone goes to college — from hechingerreport.org by Kavitha Cardoza
Indiana’s initial plan for revised graduation requirements was criticized for prioritizing workforce skills over academic preparedness. The state has tried to find a balance between the two

This story is part of Hechinger’s ongoing coverage about rethinking high school. Read about high school apprenticeships in Indiana, a new diploma in Alabama that trades chemistry for carpentry, and “career education for all” in Kentucky.

The “New Indiana Diploma” — which was signed into law in April and goes into effect for all incoming first-year students this academic year — gives students the option to earn different “seals” in addition to a basic diploma, depending on whether they plan to attend college, go straight to work or serve in the military. Jenner describes it as an effort to tailor the diploma to students’ interests, expose students to careers and recognize different forms of student achievement.

How Teachers in This District Pushed to Have Students Spend Less Time Testing — from edweek.org by Elizabeth Heubeck

Students in one Arizona district will take fewer standardized tests this school year, the result of an educator-led push to devote less time to testing.

The Tucson Education Association, backed by the school board and several parents, reached an agreement with the Tucson Unified school system in May to reduce the number of district-mandated standardized assessments students take annually starting in the 2025-26 academic year.

Just 25 percent of educators agreed that state-mandated tests provide useful information for the teachers in their school, according to a 2023 EdWeek Research Center survey of teachers, principals, and district leaders.

30 Ways to Bring Calm to a Noisy High School Classroom — from edutopia.org by Anne Noyes Saini
From ‘finding the lull’ to the magic of a dramatic whisper, these teacher-tested strategies quickly get high school students focused and back on track.

Approaching Experiential Learning as a Continuum — from edutopia.org by Bill Manchester
Teachers can consider 12 characteristics of experiential learning to make lessons more or less active for students.

AI and Higher Ed: An Impending Collapse [Niebuhr]

On 07/30/2025, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, assessment, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, cost of getting a degree, dangers of the status quo, disruption, education technology, emerging technologies, face-to-face, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, productivity / tips and tricks, reinvent, staying relevant, student-related, surviving, teaching & learning, trends, United States, universities, by Daniel Christian

AI and Higher Ed: An Impending Collapse — from insidehighered.com by Robert Niebuhr; via George Siemens; I also think George’s excerpt (see below) gets right to the point.
Universities’ rush to embrace AI will lead to an untenable outcome, Robert Niebuhr writes.

Herein lies the trap. If students learn how to use AI to complete assignments and faculty use AI to design courses, assignments, and grade student work, then what is the value of higher education? How long until people dismiss the degree as an absurdly overpriced piece of paper? How long until that trickles down and influences our economic and cultural output? Simply put, can we afford a scenario where students pretend to learn and we pretend to teach them?

This next report doesn’t look too good for traditional institutions of higher education either:

No Country for Young Grads — from burningglassinstitute.org

For the first time in modern history, a bachelor’s degree is no longer a reliable path to professional employment. Recent graduates face rising unemployment and widespread underemployment as structural—not cyclical—forces reshape entry?level work. This new report identifies four interlocking drivers: an AI?powered “Expertise Upheaval” eliminating many junior tasks, a post?pandemic shift to lean staffing and risk?averse hiring, AI acting as an accelerant to these changes, and a growing graduate glut. As a result, young degree holders are uniquely seeing their prospects deteriorate – even as the rest of the economy remain robust. Read the full report to explore the data behind these trends.

The above article was via Brandon Busteed on LinkedIn:

Osgoode’s new simulation-based learning tool aims to merge ethical and practical legal skills — from canadianlawyermag.com by Tim Wilbur
The designer speaks about his vision for redefining legal education through an innovative platform

The disconnection between legal education and the real world starkly contrasted with what he expected law school to be. “I thought rather naively…this would be a really interesting experience…linked to lawyers and what lawyers are doing in society…Far from it. It was solidly academic, so uninteresting, and I thought it’s got to be better than this.”

These frustrations inspired his work on simulation-based education, which seeks to produce “client-ready” lawyers and professionals who reflect deeply on their future roles. Maharg recently worked as a consultant with Osgoode Professional Development at Osgoode Hall Law School to design a platform that eschews many of the assumptions about legal education to deliver practical skills with real-world scenarios.

Osgoode’s SIMPLE platform – short for “simulated professional learning environment” – integrates case management systems and simulation engines to immerse students in practical scenarios.

“It’s actually to get them thinking hard about what they do when they act as lawyers and what they will do when they become lawyers…putting it into values and an ethical framework, as well as making it highly intensively practical,” Maharg says.

And speaking of legal training, also see:

AI in law firms should be a training tool, not a threat, for young lawyers — from canadianlawyermag.com by Tim Wilbur
Tech should free associates for deeper learning, not remove them from the process

AI is rapidly transforming legal practice. Today, tools handle document review and legal research at a pace unimaginable just a few years ago. As recent Canadian Lawyer reporting shows, legal AI adoption is outpacing expectations, especially among in-house teams, and is fundamentally reshaping how legal services are delivered.

Crucially, though, AI should not replace associates. Instead, it should relieve them of repetitive tasks and allow them to focus on developing judgment, client management, and strategic thinking. As I’ve previously discussed regarding the risks of banning AI in court, the future of law depends on blending technological fluency with the human skills clients value most.

Also, the following relates to legaltech as well:

Agentic AI in Legaltech: Proceed with Supervision! — from directory.lawnext.com by Ken Crutchfield
Semi-Autonomous agents can transform work if leaders maintain oversight

The term autonomous agents should raise some concern. I believe semi-autonomous agents is a better term. Do we really want fully autonomous agents that learn and interact independently, to find ways to accomplish tasks?

We live in a world full of cybersecurity risks. Bad actors will think of ways to use agents. Even well-intentioned systems could mishandle a task without proper guardrails.

Legal professionals will want to thoughtfully equip their agent technology with controlled access to the right services. Agents must be supervised, and training must be required for those using or benefiting from agents. Legal professionals will also want to expand the scope of AI Governance to include the oversight of agents.
…
Agentic AI will require supervision. Human review of Generative AI output is essential. Stating the obvious may be necessary, especially with agents. Controls, human review, and human monitoring must be part of the design and the requirements for any project. Leadership should not leave this to the IT department alone.

15 Quick (and Mighty) Retrieval Practices — from edutopia.org by Daniel Leonard
From concept maps to flash cards to Pictionary, these activities help students reflect on—and remember—what they’ve learned.

But to genuinely commit information to long-term memory, there’s no replacement for active retrieval—the effortful practice of recalling information from memory, unaided by external sources like notes or the textbook. “Studying this way is mentally difficult,” Willingham acknowledged, “but it’s really, really good for memory.”
…
From low-stakes quizzes to review games to flash cards, there are a variety of effective retrieval practices that teachers can implement in class or recommend that students try at home. Drawing from a wide range of research, we compiled this list of 15 actionable retrieval practices.

And speaking of cognitive science, also see:

‘Cognitive Science,’ All the Rage in British Schools, Fails to Register in U.S. — from the74million.org by Greg Toppo
Educators blame this ‘reverse Beatles effect’ on America’s decentralized system and grad schools that are often hostile to research.

When Zach Groshell zoomed in as a guest on a longstanding British education podcast last March, a co-host began the interview by telling listeners he was “very well-known over in the U.S.”

Groshell, a former Seattle-area fourth-grade teacher, had to laugh: “Nobody knows me here in the U.S.,” he said in an interview.

But in Britain, lots of teachers know his name. An in-demand speaker at education conferences, he flies to London “as frequently as I can” to discuss Just Tell Them, his 2024 book on explicit instruction. Over the past year, Groshell has appeared virtually about once a month and has made two personal appearances at events across England.

The reason? A discipline known as cognitive science. Born in the U.S., it relies on decades of research on how kids learn to guide teachers in the classroom, and is at the root of several effective reforms, including the Science of Reading.

“Faculty AI Guides” + “Teachers using AI tools more regularly” + other items re: AI in our learning ecosystems

On 05/27/2025, in Artificial Intelligence/Agents/LLMs/and Related, assessment, Australia, colleges, community colleges, content development, aggregation, repositories, digital learning, digital textbooks, education, education reform, education technology, educational games / serious games, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, personalized/customized learning, skills, student-related, teachers, teaching & learning, tools, trends, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

AI & Schools: 4 Ways Artificial Intelligence Can Help Students — from the74million.org by W. Ian O’Byrne
AI creates potential for more personalized learning

I am a literacy educator and researcher, and here are four ways I believe these kinds of systems can be used to help students learn.

Differentiated instruction
Intelligent textbooks
Improved assessment
Personalized learning

5 Skills Kids (and Adults) Need in an AI World — from oreilly.com by Raffi Krikorian
Hint: Coding Isn’t One of Them

Five Essential Skills Kids Need (More than Coding)
I’m not saying we shouldn’t teach kids to code. It’s a useful skill. But these are the five true foundations that will serve them regardless of how technology evolves.

Loving the journey, not just the destination
Being a question-asker, not just an answer-getter
Trying, failing, and trying differently
Seeing the whole picture
Walking in others’ shoes

The AI moment is now: Are teachers and students ready? — from iblnews.org

Day of AI Australia hosted a panel discussion on 20 May, 2025. Hosted by Dr Sebastian Sequoiah-Grayson (Senior Lecturer in the School of Computer Science and Engineering, UNSW Sydney) with panel members Katie Ford (Industry Executive – Higher Education at Microsoft), Tamara Templeton (Primary School Teacher, Townsville), Sarina Wilson (Teaching and Learning Coordinator – Emerging Technology at NSW Department of Education) and Professor Didar Zowghi (Senior Principal Research Scientist at CSIRO’s Data61).

Teachers using AI tools more regularly, survey finds — from iblnews.org

As many students face criticism and punishment for using artificial intelligence tools like ChatGPT for assignments, new reporting shows that many instructors are increasingly using those same programs.

Addendum on 5/28/25:

A Museum of Real Use: The Field Guide to Effective AI Use — from mikekentz.substack.com by Mike Kentz
Six Educators Annotate Their Real AI Use—and a Method Emerges for Benchmarking the Chats

Our next challenge is to self-analyze and develop meaningful benchmarks for AI use across contexts. This research exhibit aims to take the first major step in that direction.

With the right approach, a transcript becomes something else:

A window into student decision-making
A record of how understanding evolves
A conversation that can be interpreted and assessed
An opportunity to evaluate content understanding

This week, I’m excited to share something that brings that idea into practice.

Over time, I imagine a future where annotated transcripts are collected and curated. Schools and universities could draw from a shared library of real examples—not polished templates, but genuine conversations that show process, reflection, and revision. These transcripts would live not as static samples but as evolving benchmarks.

This Field Guide is the first move in that direction.

‘What I learned when students walked out of my AI class’ [Hogg] + other items re: AI in our learning ecosystems

On 05/19/2025, in Artificial Intelligence/Agents/LLMs/and Related, assessment, business side of he, change, colleges, communications, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, liberal arts, metacognition / metacognitive skills, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, UK, United States, universities, vendors, workplace, youth, by Daniel Christian

‘What I learned when students walked out of my AI class’ — from timeshighereducation.com by Chris Hogg
Chris Hogg found the question of using AI to create art troubled his students deeply. Here’s how the moment led to deeper understanding for both student and educator

Teaching AI can be as thrilling as it is challenging. This became clear one day when three students walked out of my class, visibly upset. They later explained their frustration: after spending years learning their creative skills, they were disheartened to see AI effortlessly outperform them at the blink of an eye.

This moment stuck with me – not because it was unexpected, but because it encapsulates the paradoxical relationship we all seem to have with AI. As both an educator and a creative, I find myself asking: how do we engage with this powerful tool without losing ourselves in the process? This is the story of how I turned moments of resistance into opportunities for deeper understanding.

In the AI era, how do we battle cognitive laziness in students? — from timeshighereducation.com by Sean McMinn
With the latest AI technology now able to handle complex problem-solving processes, will students risk losing their own cognitive engagement? Metacognitive scaffolding could be the answer, writes Sean McMinn

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.

Make Instructional Design Fun Again with AI Agents — from drphilippahardman.substack.com by Dr. Philippa Hardman
A special edition practical guide to selecting & building AI agents for instructional design and L&D

Exactly how we do this has been less clear, but — fuelled by the rise of so-called “Agentic AI” — more and more instructional designers ask me: “What exactly can I delegate to AI agents, and how do I start?”

In this week’s post, I share my thoughts on exactly what instructional design tasks can be delegated to AI agents, and provide a step-by-step approach to building and testing your first AI agent.

Here’s a sneak peak….

AI Personality Matters: Why Claude Doesn’t Give Unsolicited Advice (And Why You Should Care) — from mikekentz.substack.com by Mike Kentz
First in a four-part series exploring the subtle yet profound differences between AI systems and their impact on human cognition

After providing Claude with several prompts of context about my creative writing project, I requested feedback on one of my novel chapters. The AI provided thoughtful analysis with pros and cons, as expected. But then I noticed what wasn’t there: the customary offer to rewrite my chapter.
…
Without Claude’s prompting, I found myself in an unexpected moment of metacognition. When faced with improvement suggestions but no offer to implement them, I had to consciously ask myself: “Do I actually want AI to rewrite this section?” The answer surprised me – no, I wanted to revise it myself, incorporating the insights while maintaining my voice and process.

The contrast was striking. With ChatGPT, accepting its offer to rewrite felt like a passive, almost innocent act – as if I were just saying “yes” to a helpful assistant. But with Claude, requesting a rewrite required deliberate action. Typing out the request felt like a more conscious surrender of creative agency.

Also re: metacognition and AI, see:

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.

By prompting students to articulate their cognitive processes, such tools reinforce the internalisation of self-regulated learning strategies essential for navigating AI-augmented environments.

EDUCAUSE Panel Highlights Practical Uses for AI in Higher Ed — from govtech.com by Abby Sourwine
A webinar this week featuring panelists from the education, private and nonprofit sectors attested to how institutions are applying generative artificial intelligence to advising, admissions, research and IT.

Many higher education leaders have expressed hope about the potential of artificial intelligence but uncertainty about where to implement it safely and effectively. According to a webinar Tuesday hosted by EDUCAUSE, “Unlocking AI’s Potential in Higher Education,” their answer may be “almost everywhere.”

Panelists at the event, including Kaskaskia College CIO George Kriss, Canyon GBS founder and CEO Joe Licata and Austin Laird, a senior program officer at the Gates Foundation, said generative AI can help colleges and universities meet increasing demands for personalization, timely communication and human-to-human connections throughout an institution, from advising to research to IT support.

Partly Cloudy with a Chance of Chatbots — from derekbruff.org by Derek Bruff

Here are the predictions, our votes, and some commentary:

“By 2028, at least half of large universities will embed an AI ‘copilot’ inside their LMS that can draft content, quizzes, and rubrics on demand.” The group leaned toward yes on this one, in part because it was easy to see LMS vendors building this feature in as a default.
“Discipline-specific ‘digital tutors’ (LLM chatbots trained on course materials) will handle at least 30% of routine student questions in gateway courses.” We learned toward yes on this one, too, which is why some of us are exploring these tools today. We would like to be ready how to use them well (or avoid their use) when they are commonly available.
“Adaptive e-texts whose examples, difficulty, and media personalize in real time via AI will outsell static digital textbooks in the U.S. market.” We leaned toward no on this one, in part because the textbook market and what students want from textbooks has historically been slow to change. I remember offering my students a digital version of my statistics textbook maybe 6-7 years ago, and most students opted to print the whole thing out on paper like it was 1983.
“AI text detectors will be largely abandoned as unreliable, shifting assessment design toward oral, studio, or project-based ‘AI-resilient’ tasks.” We leaned toward yes on this. I have some concerns about oral assessments (they certainly privilege some students over others), but more authentic assignments seems like what higher ed needs in the face of AI. Ted Underwood recently suggested a version of this: “projects that attempt genuinely new things, which remain hard even with AI assistance.” See his post and the replies for some good discussion on this idea.
“AI will produce multimodal accessibility layers (live translation, alt-text, sign-language avatars) for most lecture videos without human editing.” We leaned toward yes on this one, too. This seems like another case where something will be provided by default, although my podcast transcripts are AI-generated and still need editing from me, so we’re not there quite yet.

‘We Have to Really Rethink the Purpose of Education’
The Ezra Klein Show

Description: I honestly don’t know how I should be educating my kids. A.I. has raised a lot of questions for schools. Teachers have had to adapt to the most ingenious cheating technology ever devised. But for me, the deeper question is: What should schools be teaching at all? A.I. is going to make the future look very different. How do you prepare kids for a world you can’t predict?

And if we can offload more and more tasks to generative A.I., what’s left for the human mind to do?

Rebecca Winthrop is the director of the Center for Universal Education at the Brookings Institution. She is also an author, with Jenny Anderson, of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.” We discuss how A.I. is transforming what it means to work and be educated, and how our use of A.I. could revive — or undermine — American schools.

2025 EDUCAUSE Horizon Report | Teaching and Learning Edition

On 05/12/2025, in 21st century, accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, assessment, Bias | Diversity Equity & Inclusion (DE&I), colleges, community colleges, credentialing, digital audio, disruption, economics, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, immersion, innovation, instructional design, intelligent systems, learning, learning ecosystem, Learning Experience Design, liberal arts, neurodivergent/special needs, pedagogy, privacy, skills, social learning / networks, society, student-related, teaching & learning, technology (general), trends, United States, universities, Virtual Reality (VR) / worlds / learning, workplace, XR - extended reality, by Daniel Christian

2025 EDUCAUSE Horizon Report | Teaching and Learning Edition — from library.educause.edu

Higher education is in a period of massive transformation and uncertainty. Not only are current events impacting how institutions operate, but technological advancement—particularly in AI and virtual reality—are reshaping how students engage with content, how cognition is understood, and how learning itself is documented and valued.

Our newly released 2025 EDUCAUSE Horizon Report | Teaching and Learning Edition captures the spirit of this transformation and how you can respond with confidence through the lens of emerging trends, key technologies and practices, and scenario-based foresight.

#teachingandlearning #highereducation #learningecosystems #learning #futurism #foresight #trends #emergingtechnologies #AI #VR #gamechangingenvironment #colleges #universities #communitycolleges #faculty #staff #IT

Something alarming is happening to the job market [Thompson] + other items re: AI in our learning ecosystems and in the workplace

On 05/05/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, change, changing business models, corporate / business world, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Microsoft, new business models, organizational change, platforms, podcasting, productivity / tips and tricks, professional development, research, teachers, teaching & learning, tools, trends, United States, universities, workplace, by Daniel Christian

DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI

— Daniel S. Christian (@dchristian5) May 1, 2025

..which links to:

Duolingo will replace contract workers with AI — from theverge.com by Jay Peters
The company is going to be ‘AI-first,’ says its CEO.

Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by cofounder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.

According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”

Relevant links:

Something strange, and potentially alarming, is happening to the job market for young, educated workers.

According to the New York Federal Reserve, labor conditions for recent college graduates have “deteriorated noticeably” in the past few months, and the unemployment rate now stands at an unusually high 5.8 percent. Even newly minted M.B.A.s from elite programs are struggling to find work. Meanwhile, law-school applications are surging—an ominous echo of when young people used graduate school to bunker down during the great financial crisis.

What’s going on? I see three plausible explanations, and each might be a little bit true.

It’s Time To Get Concerned As More Companies Replace Workers With AI — from forbes.com by Jack Kelly

The new workplace trend is not employee friendly. Artificial intelligence and automation technologies are advancing at blazing speed. A growing number of companies are using AI to streamline operations, cut costs, and boost productivity. Consequently, human workers are facing facing layoffs, replaced by AI. Like it or not, companies need to make tough decisions, including layoffs to remain competitive.

Corporations including Klarna, UPS, Duolingo, Intuit and Cisco are replacing laid-off workers with AI and automation. While these technologies enhance productivity, they raise serious concerns about future job security. For many workers, there is a big concern over whether or not their jobs will be impacted.

The future of career navigation — from medium.com by Sami Tatar

Career navigation market overview

Key takeaway:
Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. The advent of AI is changing this, offering personalised career pathways, better job matching, democratised job application support, democratised access to career advice/coaching, and tailored skill development to help you get to where you need to be. Hundreds of millions of people start new jobs every year, this transformation opens up a multi-billion dollar opportunity for innovation in the global career navigation market.
…

A.4 How will AI disrupt this segment?
Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even youtube history, and x/twitter feeds), standardise this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam, and working in Strategy at Uber and want to work in a Product role in the future? Here are X,Y,Z specific things YOU can do in your role today to align yourself perfectly. E.g. find opportunities to manage cross functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did Strategy and moved to Product, etc.

Tales from the Front – What Teachers Are Telling Me at AI Workshops — from aliciabankhofer.substack.com by Alicia Bankhofer
Real conversations, real concerns: What teachers are saying about AI

“Do I really have to use AI?”

No matter the school, no matter the location, when I deliver an AI workshop to a group of teachers, there are always at least a few colleagues thinking (and sometimes voicing), “Do I really need to use AI?”

Nearly three years after ChatGPT 3.5 landed in our lives and disrupted workflows in ways we’re still unpacking, most schools are swiftly catching up. Training sessions, like the ones I lead, are springing up everywhere, with principals and administrators trying to answer the same questions: Which tools should we use? How do we use them responsibly? How do we design learning in this new landscape?

But here’s what surprises me most: despite all the advances in AI technology, the questions and concerns from teachers remain strikingly consistent.
…
In this article, I want to pull back the curtain on those conversations. These concerns aren’t signs of reluctance – they reflect sincere feelings. And they deserve thoughtful, honest answers.

Welcome To AI Agent World! (Everything you need to know about the AI Agent market.) — from joshbersin.com by Josh Bersin

This week, in advance of major announcements from us and other vendors, I give you a good overview of the AI Agent market, and discuss the new role of AI governance platforms, AI agent development tools, AI agent vendors, and how AI agents will actually manifest and redefine what we call an “application.”

I discuss ServiceNow, Microsoft, SAP, Workday, Paradox, Maki People, and other vendors. My goal today is to “demystify” this space and explain the market, the trends, and why and how your IT department is going to be building a lot of the agents you need. And prepare for our announcements next week!

DeepSeek Unveils Prover V2 — from theaivalley.com

DeepSeek has quietly launched Prover V2, an open-source model built to solve math problems using Lean 4 assistant, which ensures every step of a proof is rigorously verified.

What’s impressive about it?

Massive scale: Based on DeepSeek-V3 with 671B parameters using a mixture-of-experts (MoE) architecture, which activates only parts of the model at a time to reduce compute costs.
Theorem solving: Uses long context windows (32K+ tokens) to generate detailed, step-by-step formal proofs for a wide range of math problems — from basic algebra to advanced calculus theorems.
Research grade: Assists mathematicians in testing new theorems automatically and helps students understand formal logic by generating both Lean 4 code and readable explanations.
New benchmark: Introduces ProverBench, a new 325-question benchmark set featuring problems from recent AIME exams and curated academic sources to evaluate mathematical reasoning.

Artificial Intelligence: Lessons Learned from a Graduate-Level Final Exam — from er.educause.edu by Craig Westling and Manish K. Mishra

The need for deep student engagement became clear at Dartmouth Geisel School of Medicine when a potential academic-integrity issue revealed gaps in its initial approach to artificial intelligence use in the classroom, leading to significant revisions to ensure equitable learning and assessment.

Deep Research with AI: 9 Ways to Get Started — from wondertools.substack.com by Jeremy Caplan
Practical strategies for thorough, citation-rich AI research
.

From George Siemens “SAIL: Transmutation, Assessment, Robots e-newsletter on 5/2/25

All indications are that AI, even if it stops advancing, has the capacity to dramatically change knowledge work. Knowing things matters less than being able to navigate and make sense of complex environments. Put another way, sensemaking, meaningmaking, and wayfinding (with their yet to be defined subelements) will be the foundation for being knowledgeable going forward.

That will require being able to personalize learning to each individual learner so that who they are (not what our content is) forms the pedagogical entry point to learning.(DSC: And I would add WHAT THEY WANT to ACHIEVE.)LLMs are particularly good and transmutation. Want to explain AI to a farmer? A sentence or two in a system prompt achieves that. Know that a learner has ADHD? A few small prompt changes and it’s reflected in the way the LLM engages with learning. Talk like a pirate. Speak in the language of Shakespeare. Language changes. All a matter of a small meta comment send to the LLM. I’m convinced that this capability to change, transmute, information will become a central part of how LLMS and AI are adopted in education.
…
Speaking of Duolingo– it took them 12 years to develop 100 courses. In the last year, they developed an additional 148. AI is an accelerant with an impact in education that is hard to overstate. “Instead of taking years to build a single course with humans the company now builds a base course and uses AI to quickly customize it for dozens of different languages.”

FutureHouse Platform: Superintelligent AI Agents for Scientific Discovery — from futurehouse.org by Michael Skarlinski, Tyler Nadolski, James Braza, Remo Storni, Mayk Caldas, Ludovico Mitchener, Michaela Hinks, Andrew White, & Sam Rodriques

FutureHouse is launching our platform, bringing the first publicly available superintelligent scientific agents to scientists everywhere via a web interface and API. Try it out for free at https://platform.futurehouse.org.

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

On 04/10/2025, in 21st century, 24x7x365 access, accreditation, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, Blockchain, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, credentialing, culture, curriculum, dangers of the status quo, Daniel S. Christian, data related items, Design Thinking, digital learning, disruption, education technology, emerging technologies, Emotion, engagement / engaging students, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, leadership, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, lifelong learning, MBA, Michigan, new business models, online learning, online media, online tutoring, organizational change, pace of change, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, technologies for your home, tools, trends, United States, universities, usability, user experience (UX), virtual tutoring, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

.
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.

“8 Weeks Left to Prepare Students for the AI-Enhanced Workplace” [Schroeder] + other items re: AI in our LEs

On 03/21/2025, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, assessment, career development, change, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, corporate / business world, curriculum, digital learning, education technology, emerging technologies, expectations, experimentation, faculty/staff, future, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, learning, Learning Experience Design, liberal arts, new business models, online learning, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, research, staying relevant, student-related, surviving, teaching & learning, teaching online, trends, United States, universities, workplace, by Daniel Christian

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.

2025 College Hopes & Worries Survey Report [princetonreview.com]

On 03/12/2025, in assessment, colleges, community colleges, cost of getting a degree, credentialing, Emotion, funding / grants, higher education, learning ecosystem, parents/guardians, participation, society, student-related, United States, universities, user experience (UX), by Daniel Christian

2025 College Hopes & Worries Survey Report — from princetonreview.com
We surveyed 9,317 college applicants and parents about their dream schools and their biggest college admission and financial aid challenges.
.

Market scan: What’s possible in the current skills validation ecosystem? [eddesignlab.org]

On 02/20/2025, in Alternatives, assessment, business, career development, change, changing business models, credentialing, experimentation, future, game-changing environment, ideas, skills, training / L&D, vendors, workplace, by Daniel Christian

Market scan: What’s possible in the current skills validation ecosystem? — from eddesignlab.org
Education Design Lab provides an overview of emerging practices + tools in this 2025 Skills Validation Market Scan.

Employers and opportunity seekers are excited about the possibilities of a skills-based ecosystem, but this new process for codifying a person’s experiences and abilities into skills requires one significant, and missing, piece: Trust. Employers need to trust that the credentials they receive from opportunity seekers are valid representations of their skills. Jobseekers need to trust that their digital credentials are safe, accurate, and will lead to employment and advancement.

Our hypothesis
We posit that the trust needed for the validation of skills to be brought into a meaningful reality is established through a network of skills validation methods and opportunities. We also recognize that the routes through which an individual can demonstrate skills are as varied as the individuals themselves. Therefore, in order to equitably create a skills-based employment ecosystem, the routes by which skills are validated must be held together with common standards and language, but flexible enough to accommodate a multitude of validation practices.

“Half A Million Students Given ChatGPT As CSU System Makes AI History” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 02/07/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, change, colleges, community colleges, content development, aggregation, repositories, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, graphics, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, research, student-related, teachers, teaching & learning, tools, trends, United States, universities, vendors, by Daniel Christian

Half A Million Students Given ChatGPT As CSU System Makes AI History — from forbes.com by Dan Fitzpatrick

The California State University system has partnered with OpenAI to launch the largest deployment of AI in higher education to date.

The CSU system, which serves nearly 500,000 students across 23 campuses, has announced plans to integrate ChatGPT Edu, an education-focused version of OpenAI’s chatbot, into its curriculum and operations. The rollout, which includes tens of thousands of faculty and staff, represents the most significant AI deployment within a single educational institution globally.

We’re still in the early stages of AI adoption in education, and it is critical that the entire ecosystem—education systems, technologists, educators, and governments—work together to ensure that all students globally have access to AI and develop the skills to use it responsibly

Leah Belsky, VP and general manager of education at OpenAI.

HOW educators can use GenAI – where to start and how to progress — from aliciabankhofer.substack.com by Alicia Bankhofer
Part of 3 of my series: Teaching and Learning in the AI Age

As you read through these use cases, you’ll notice that each one addresses multiple tasks from our list above.

1. Researching a topic for a lesson
2. Creating Tasks For Practice
3. Creating Sample Answers
4. Generating Ideas
5. Designing Lesson Plans
6. Creating Tests
7. Using AI in Virtual Classrooms
8. Creating Images
9. Creating worksheets
10. Correcting and Feedback

Creating Assessments for Micro-Credentials in Higher Education Organizations. [Reed & Abramovich]

On 12/29/2024, in assessment, colleges, community colleges, credentialing, faculty/staff, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, liberal arts, microlearning, teaching & learning, teaching online, United States, universities, by Daniel Christian

Reflections on “US College Closures Are Expected to Soar, Fed Research Says” [Bloomberg.com]

On 12/07/2024, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, assessment, business side of he, change, changing business models, colleges, community colleges, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, economics, faculty/staff, game-changing environment, higher education, ideas, law schools, learning ecosystem, Learning from the Living [Class] Room, legislatures / government / legal, liberal arts, new business models, parents/guardians, policy, reinvent, society, staying relevant, student-related, surviving, United States, universities, vendors, by Daniel Christian

US College Closures Are Expected to Soar, Fed Research Says — from bloomberg.com

Fed research created predictive model of college stress
Worst-case scenario forecasts 80 additional closures

The number of colleges that close each year is poised to significantly increase as schools contend with a slowdown in prospective students.

That’s the finding of a new working paper published by the Federal Reserve Bank of Philadelphia, where researchers created predictive models of schools’ financial distress using metrics like enrollment and staffing patterns, sources of revenue and liquidity data. They overlayed those models with simulations to estimate the likely increase of future closures.

Excerpt from the working paper:

We document a high degree of missing data among colleges that eventually close and show that this is a key impediment to identifying at risk institutions. We then show that modern machine learning techniques, combined with richer data, are far more effective at predicting college closures than linear probability models, and considerably more effective than existing accountability metrics. Our preferred model, which combines an off-the-shelf machine learning algorithm with the richest set of explanatory variables, can significantly improve predictive accuracy even for institutions with complete data, but is particularly helpful for predicting instances of financial distress for institutions with spotty data.

From DSC:
Questions that come to my mind here include:

Shouldn’t the public — especially those relevant parents and students — be made more aware of these types of papers and reports?
.
How would any of us like finishing up 1-3 years of school and then being told that our colleges or universities were closing, effective immediately? (This has happened many times already.) and with the demographic cliff starting to hit higher education, this will happen even more now.
.
Adding insult to injury…when we transfer to different institutions, we’re told that many of our prior credits don’t transfer — thus adding a significant amount to the overall cost of obtaining our degrees.
.
Would we not be absolutely furious to discover such communications from our prior — and new — colleges and universities?
.
Will all of these types of closures move more people to this vision here?

Relevant excerpts from Ray Schroeder’s recent articles out at insidehighered.com:

Winds of Change in Higher Ed to Become a Hurricane in 2025

A number of factors are converging to create a huge storm. Generative AI advances, massive federal policy shifts, broad societal and economic changes, and the demographic cliff combine to create uncertainty today and change tomorrow.

Higher Education in 2025: AGI Agents to Displace People

The anticipated enrollment cliff, reductions in federal and state funding, increased inflation, and dwindling public support for tuition increases will combine to put even greater pressure on university budgets.

On the positive side of things, the completion rates have been getting better:

National college completion rate ticks up to 61.1% — from highereddive.com by Natalie Schwartz
Those who started at two-year public colleges helped drive the overall increase in students completing a credential.

Dive Brief:

Completion rates ticked up to 61.1% for students who entered college in fall 2018, a 0.5 percentage-point increase compared to the previous cohort, according to data released Wednesday by the National Student Clearinghouse Research Center.
The increase marks the highest six-year completion rate since 2007 when the clearinghouse began tracking the data. The growth was driven by fewer students stopping out of college, as well as completion gains among students who started at public two-year colleges.
“Higher completion rates are welcome news for colleges and universities still struggling to regain enrollment levels from before the pandemic,” Doug Shapiro, the research center’s executive director, said in a statement dated Wednesday.

Addendum:

Attention Please: Professors Struggle With Student Disengagement — from edsurge.com

The stakes are huge, because the concern is that maybe the social contract between students and professors is kind of breaking down. Do students believe that all this college lecturing is worth hearing? Or, will this moment force a change in the way college teaching is done?

Previous Entries Next Entries

Learning Ecosystems

Market scan: What’s possible in the current skills validation ecosystem? [eddesignlab.org]

Creating Assessments for Micro-Credentials in Higher Education Organizations. [Reed & Abramovich]

Categories

Tags