Higher ed’s ‘hunker-down mindset’— from open-campus-dispatch.beehiiv.com by Colleen Murphy A tight housing market and a fragile job market mean those working in higher ed have fewer options than ever.
Faculty and administrators could be just as constrained by the golden handcuffs of a 2% interest rate as everybody else. That makes them less likely to move for a new job, Kelchen said, especially since they’re unlikely to get the type of salary increase they’d need to offset more pricey mortgage payments. Plus, even finding an affordable house in the first place could be a challenge right now.
All of this contributes to what Kelchen called a “hunker-down mindset” in higher ed.
“Even if the institutions are giving out pay raises, the pay raises aren’t matching housing costs,” Kelchen said. “And then that creates a pressure to stay.”
While that might seem like a “first-world problem,” it also affects college and university staff members, Kelchen told me. Often the only way for staff members to make more money is to move universities — there aren’t the same in-house growth opportunities as there are for faculty. But that’s easier said than done.
Bottom line: The best engineers became 100x better with AI coding tools. Now the same transformation is hitting law. Joel [the CTO at Thomson Reuters] predicts the best attorneys who master these tools will become 100x more powerful than before.
4. Legal Startups Reshape the Market for Judges and Practitioners
Legal services are no longer dominated by traditional providers. Business Insider reports on a new wave of nimble “Law Firm 2.0” entities—AI-enabled startups offering fixed cost services for specific tasks such as contract reviews or drafting. The LegalTech Lab is helping launch such disruptors with funding and guidance.
At the same time, alternative legal service providers or ALSPs are integrating generative AI, moving beyond cost-efficient support to providing legal advice and enhanced services—often on subscription models.
In 2025 so far, legal technology has moved from incremental adoption to integral transformation. Generative AI, investments, startups, and regulatory readiness are reshaping the practice of law—for lawyers, judges, and the rule of law.
I recently finished reading Ethan Mollick‘s excellent book on artificial intelligence, entitled Co-Intelligence: Living and Working with AI. He does a great job of explaining what it is, how it works, how it best can be used, and where it may be headed.
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The first point that resonated with me is that artificial intelligence tools can take those with poor skills in certain areas and significantly elevate their output. For example, Mollick cited a study that demonstrated that the performance of law students at the bottom of their class got closer to that of the top students with the use of AI.
Lawyers and law firms need to begin thinking and planning for how the coming skill equalization will impact competition and potentially profitability. They need to consider how the value of what they provide to their clients will be greater than their competition. They need to start thinking about what skill will set them apart in the new AI driven world.
Welcome to the new normal: the AI First Draft. Clients—from everyday citizens to solo entrepreneurs to sophisticated in-house counsel—are increasingly using AI to create the first draft of legal documents before outside counsel even enters the conversation. Contracts, memos, emails, issue spotters, litigation narratives: AI can now do it all.
This means outside counsel is now navigating a very different kind of document review and client relationship. One that comes with hidden risks, awkward conversations, and new economic pressures.
Here are the three things every lawyer needs to start thinking about when reviewing client-generated work product.
1. The Prompt Problem: What Was Shared, and With Whom?… 2. The Confidence Barrier: When AI Sounds Right, But Isn’t… 3. The Economic Shift: Why AI Work Can Cost More, Not Less…
Business leaders across the world are grappling with a reality that would have seemed like science fiction just a few decades ago: Artificial intelligence systems dubbed AI agents are becoming colleagues, not just tools. At many organizations, HR pros are already developing balanced and thoughtful machine-people workforces that meet business goals.
At Skillsoft, a global corporate learning company, Chief People Officer Ciara Harrington has spent the better part of three years leading digital transformation in real time. Through her front-row seat to CEO transitions, strategic pivots and the rapid acceleration of AI adoption, she’s developed a strong belief that organizations must be agile with people operations.
‘No role that’s not a tech role’ Under these modern conditions, she says, technology is becoming a common language in the workplace. “There is no role that’s not a tech role,” Harrington said during a recent discussion about the future of work. It’s a statement that gets at the heart of a shift many HR leaders are still coming to terms with.
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But a key question remains: Who will manage the AI agents, specifically, HR leaders or someone else?
SINGAPORE Sept. 3, 2025 /PRNewswire/ — Today, Midoo AIproudly announces the launch of the world’s first AI language learning agent, a groundbreaking innovation set to transform language education forever.
For decades, language learning has pursued one ultimate goal: true personalization. Traditional tools offered smart recommendations, gamified challenges, and pre-written role-play scripts—but real personalization remained out of reach. Midoo AI changes that. Here is the >launch video of Midoo AI.
Imagine a learning experience that evolves with you in real time. A system that doesn’t rely on static courses or scripts but creates a dynamic, one-of-a-kind language world tailored entirely to your needs. This is the power of Midoo’s Dynamic Generation technology.
“Midoo is not just a language-learning tool,” said Yvonne, co-founder of Midoo AI. “It’s a living agent that senses your needs, adapts instantly, and shapes an experience that’s warm, personal, and alive. Learning is no longer one-size-fits-all—now, it’s yours and yours alone.”
Language learning apps have traditionally focused on exercises, quizzes, and progress tracking. Midoo AI introduces a different approach. Instead of presenting itself as a course provider, it acts as an intelligent learning agent that builds, adapts, and sustains a learner’s journey.
This review examines how Midoo AI operates, its feature set, and what makes it distinct from other AI-powered tutors.
Midoo AI in Context: Purpose and Position
Midoo AI is not structured around distributing lessons or modules. Its core purpose is to provide an agent-like partner that adapts in real time. Where many platforms ask learners to select a “level” or “topic,”
Midoo instead begins by analyzing goals, usage context, and error patterns. The result is less about consuming predesigned units and more about co-constructing a pathway.
Turning Time Saved Into Better Learning
AI can save teachers time, but what can that time be used for (besides taking a breath)? For most of us, it means redirecting energy into the parts of teaching that made us want to pursue this profession in the first place: connecting with our students and helping them grow academically.
Differentiation Every classroom has students with different readiness levels, language needs, and learning preferences. AI tools like Diffit or MagicSchool can instantly create multiple versions of a passage or assignment, differentiated by grade level, complexity, or language. This allows every student to engage with the same core concept, moving together as one cohesive class. Instead of spending an evening retyping and rephrasing, teachers can review and tweak AI drafts in minutes, ready for the next lesson.
Mass Intelligence — from oneusefulthing.org by Ethan Mollick From GPT-5 to nano banana: everyone is getting access to powerful AI
When a billion people have access to advanced AI, we’ve entered what we might call the era of Mass Intelligence. Every institution we have — schools, hospitals, courts, companies, governments — was built for a world where intelligence was scarce and expensive. Now every profession, every institution, every community has to figure out how to thrive with Mass Intelligence. How do we harness a billion people using AI while managing the chaos that comes with it? How do we rebuild trust when anyone can fabricate anything? How do we preserve what’s valuable about human expertise while democratizing access to knowledge?
By the time today’s 9th graders and college freshman enter the workforce, the most disruptive waves of AGI and robotics may already be embedded into part society.
What replaces the old system will not simply be a more digital version of the same thing. Structurally, schools may move away from rigid age-groupings, fixed schedules, and subject silos. Instead, learning could become more fluid, personalized, and interdisciplinary—organized around problems, projects, and human development rather than discrete facts or standardized assessments.
AI tutors and mentors will allow for pacing that adapts to each student, freeing teachers to focus more on guidance, relationships, and high-level facilitation. Classrooms may feel less like miniature factories and more like collaborative studios, labs, or even homes—spaces for exploring meaning and building capacity, not just delivering content.
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If students are no longer the default source of action, then we need to teach them to:
Design agents,
Collaborate with agents,
Align agentic systems with human values,
And most of all, retain moral and civic agency in a world where machines act on our behalf.
We are no longer educating students to be just doers.
We must now educate them to be judges, designers, and stewards of agency.
Meet Your New AI Tutor — from wondertools.substack.com by Jeremy Caplan Try new learning modes in ChatGPT, Claude, and Gemini
AI assistants are now more than simple answer machines. ChatGPT’s new Study Mode, Claude’s Learning Mode, and Gemini’s Guided Learningrepresent a significant shift. Instead of just providing answers, these free tools act as adaptive, 24/7 personal tutors.
That’s why, in preparation for my next bootcamp which kicks off September 8th 2025, I’ve just completed a full refresh of my list of the most powerful & popular AI tools for Instructional Designers, complete with tips on how to get the most from each tool.
The list has been created using my own experience + the experience of hundreds of Instructional Designers who I work with every week.
It contains the 50 most powerful AI tools for instructional design available right now, along with tips on how to optimise their benefits while mitigating their risks.
Addendums on 9/4/25:
AI Companies Roll Out Educational Tools — from insidehighered.com by Ray Schroeder This fall, Google, Anthropic and OpenAI are rolling out powerful new AI tools for students and educators, each taking a different path to shape the future of learning.
So here’s the new list of essential skills I think my students will need when they are employed to work with AI five years from now:
They can follow directions, analyze outcomes, and adapt to change when needed.
They can write or edit AI to capture a unique voice and appropriate tone in sync with an audience’s needs
They have a deep understanding of one or more content areas of a particular profession, business, or industry, so they can easily identify factual errors.
They have a strong commitment to exploration, a flexible mindset, and a broad understanding of AI literacy.
They are resilient and critical thinkers, ready to question results and demand better answers.
They are problem solvers.
And, of course, here is a new rubric built on those skills:
What’s changing is not the foundation—it’s the ecosystem. Teams are looking to create more flexible, scalable, and diverse learning experiences that meet people where they are.
What Did We Explore? Everyone seems to have a take on what’s happening in L&D these days. From bold claims about six-figure roles to debates over whether portfolios or degrees matter more, everyone seems to have a take. So, we wanted to get to the heart of it by exploring five of the biggest, most debated areas shaping our work today:
Salaries: Are compensation trends really keeping pace with the value we deliver?
Hiring: What skills are managers actually looking for—and are those ATS horror stories true?
Portfolios: Are portfolios helping candidates stand out, and what are hiring managers actually looking for?
Tools & Modalities: What types of training are teams building, and what tools are they using to build it?
Artificial Intelligence: Who’s using it, how, and what concerns still exist?
These five areas are shaping the future of instructional design—not just for job seekers, but for team leaders, hiring managers, and the entire ecosystem of L&D professionals.
The takeaway? A portfolio is more than a collection of projects—it’s a storytelling tool. The ones that stand out highlight process, decision-making, and results—not just pretty screens.
The Online Education Marketplace Is Increasingly Competitive: …
Alternative Credentials Take Center Stage: …
AI Integration Lacks Strategic Coordination: …
Just 28% of faculty are considered fully prepared for online course design, and 45% for teaching. Alarmingly, only 28% of institutions report having fully developed academic continuity plans for future emergency pivots to online.
Cultural resistance remains strong. Many [Chief Online Learning Officers] COLOs say faculty and deans still believe in-person learning is “just better,” creating headwinds even for modest online growth. As one respondent at a four-year institution with a large online presence put it:
Supportive departments [that] see the value in online may have very different levels of responsiveness compared to academic departments [that] are begrudgingly online. There is definitely a growing belief that students “should” be on-ground and are only choosing online because it’s easy/ convenient. Never mind the very real and growing population of nontraditional learners who can only take online classes, and the very real and growing population of traditional-aged learners who prefer online classes; many faculty/deans take a paternalistic, “we know what’s best” approach.
… Ultimately, what we need is not just more ambition but better ambition. Ambition rooted in a realistic understanding of institutional capacity, a shared strategic vision, investments in policy and infrastructure, and a culture that supports online learning as a core part of the academic mission, not an auxiliary one. It’s time we talked about what it really takes to grow online learning , and where ambition needs to be matched by structure.
From DSC: Yup. Culture is at the breakfast table again…boy, those strategies taste good.
I’d like to take some of this report — like the graphic below — and share it with former faculty members and members of a couple of my past job families’ leadership. They strongly didn’t agree with us when we tried to advocate for the development of online-based learning/programs at our organizations…but we were right. We were right all along. And we were LEADING all along. No doubt about it — even if the leadership at the time said that we weren’t leading.
The cultures of those organizations hurt us at the time. But our cultivating work eventually led to the development of online programs — unfortunately, after our groups were disbanded, they had to outsource those programs to OPMs.
Arizona State University — with its dramatic growth in online-based enrollments.
Young workers are getting hit in fields where generative-AI tools such as ChatGPT can most easily automate tasks done by humans, such as software development, according to a paper released Tuesday by three Stanford University economists. They crunched anonymized data on millions of employees at tens of thousands of firms, including detailed information on workers’ ages and jobs, making this one of clearest indicators yet of AI’s disruptive impact.
Young workers in jobs where AI could act as a helper, rather than a replacement, actually saw employment growth, economists found.
The AI Education Revolution — from linkedin.com by Whitney Kilgore We’re witnessing the biggest shift in education since the textbook—and most institutions are still deciding whether to allow it.
Learn something new. Map out a personalized curriculum
Try this: Give an AI assistant context about what you want to learn, why, and how.
Detail your rationale and motivation, which may impact your approach.
Note your current knowledge or skill level, ideally with examples.
Summarize your learning preferences
Note whether you prefer to read, listen to, or watch learning materials.
Mention if you like quizzes, drills, or exercises you can do while commuting or during a break at work.
If you appreciate learning games, task your AI assistant with generating one for you, using its coding capabilities detailed below.
Ask for specific book, textbook, article, or learning path recommendations using the Web search or Deep Research capabilities of Perplexity, ChatGPT, Gemini or Claude. They can also summarize research literature about effective learning tactics.
If you need a human learning partner, ask for guidance on finding one or language you can use in reaching out.
GPT-5 for Instructional Designers — from drphilippahardman.substack.com by Dr Philippa Hardman 10 Hacks to Work Smarter & Safer with OpenAI’s Latest Model
The TLDR is that as Instructional Designers, we can’t afford to miss some of the very real benefits of GPT-5’s potential, but we also can’t ensure our professional standards or learner outcomes if we blindly accept its outputs without due testing and validation.
For this reason, I decided to synthesise the latest GPT-5 research—from OpenAI’s technical documentation to independent security audits to real-world user testing—into 10 essential reality checks for using GPT-5 as an Instructional Designer.
These aren’t theoretical exercises; they’re practical tests designed to help you safely unlock GPT-5’s benefits while identifying and mitigating its most well-documented limitations.
While I regularly use tools like ChatGPT, Grammarly, Microsoft Copilot, and even YouTube Premium (I would cancel Netflix before this), Perplexity has earned a top spot in my toolkit. It blends AI and real-time web search into one seamless, research-driven platform that saves time and improves the quality of information I rely on every day.
As a new academic year begins, many instructors, trainers, and program leaders are bracing for familiar challenges—keeping learners engaged, making complex material accessible, and preparing students for real-world application.
But there’s a quiet shift happening in classrooms and online courses everywhere.
This fall, it’s not the syllabus that’s guiding the learning experience—it’s the conversation between the learner and an AI tool.
From bootcamp to bust: How AI is upending the software development industry — from reuters.com by Anna Tong; via Paul Fain Coding bootcamps have been a mainstay in Silicon Valley for more than a decade. Now, as AI eliminates the kind of entry-level roles for which they trained people, they’re disappearing.
Coding bootcamps have been a Silicon Valley mainstay for over a decade, offering an important pathway for non-traditional candidates to get six-figure engineering jobs. But coding bootcamp operators, students and investors tell Reuters that this path is rapidly disappearing, thanks in large part to AI.
“Coding bootcamps were already on their way out, but AI has been the nail in the coffin,” said Allison Baum Gates, a general partner at venture capital fund SemperVirens, who was an early employee at bootcamp pioneer General Assembly.
Gates said bootcamps were already in decline due to market saturation, evolving employer demand and market forces like growth in international hiring.
To rise above the threshold, consider the skills that our board member and Northeastern University President Joseph Aoun outlines as essential literacies in Robot-Proof: Higher Education in the Age of Artificial Intelligence. In addition to technical and data literacies, he shares two key components of human literacy.
First, a set of “catalytic capacities” that include:
Initiative and self-reliance
Comfort with risk
Flexibility and adaptability
Second, a set of “creative capacities” that include:
Opportunity recognition, or the ability to see and experience problems as opportunities to create solutions
Creative innovation, or the ability to create solutions without clearly defined structures
Future innovation, or the disposition to orient toward future developments in society
The most effective approach to achieve these outcomes? Interdisciplinary models that embed skills flexibly across curriculum, that engage learners as part of networks, teams, and exploration, and that embed applied experiences in real-world contexts. Scott Carlson and Ned Laff have laid out some great examples of what this looks like in action in Hacking College.
The bottom line: the expectations of entry-level talent are rising while the systems to achieve that level of context and understanding are not necessarily keeping pace.
The GPT-5 Backlash, Explained: OpenAI users revolted against GPT-5… then things got weird.
What a vibe shift a day or two makes, huh? As you all know by now, GPT-5 dropped last Thursday, and at first, it seemed like a pretty successful launch.
Early testers loved it. Sam Altman called it “the most powerful AI model ever made.”
Then the floodgates opened to 700 million users.. and all hell broke loose.
Here’s what happened: Within hours, Reddit and Twitter turned into digital pitchforks. The crime? OpenAI had quietly sunset GPT-4o—the model everyone apparently loved more than their morning coffee—without warning. Users weren’t just mad. They were devastated.
ChatGPT Changes — from getsuperintel.com by Kim “Chubby” Isenberg 4o is back, and Plus users get 3000 reasoning requests per week with GPT-5!
Who would have thought that the “smartest model ever” would trigger one of the loudest user revolts in AI history? The return of GPT-4o after only 24 hours shows how attached people are to the personality of their AI—and how quickly trust crumbles when expectations are not met. In this issue, we not only look at OpenAI’s response, but also at how the balance of power between developers and the community is shifting.
The backlash over the more emotionally neutral GPT-5 shows that the smartest AI models might have striking reasoning, coding, and math skills, but advancing their psychological intelligence safely remains very much unsolved.
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Since the all-new ChatGPT launched on Thursday, some users have mourned the disappearance of a peppy and encouraging personality in favor of a colder, more businesslike one (a move seemingly designed to reduce unhealthy user behavior.) The backlash shows the challenge of building artificial intelligence systems that exhibit anything like real emotional intelligence.
Researchers at MIT have proposed a new kind of AI benchmark to measure how AI systems can manipulate and influence their users—in both positive and negative ways—in a move that could perhaps help AI builders avoid similar backlashes in the future while also keeping vulnerable users safe.
OpenAI is bringing back GPT-4o in ChatGPT just one day after replacing it with GPT-5. In a post on X, OpenAI CEO Sam Altman confirmed that the company will let paid users switch to GPT-4o after ChatGPT users mourned its replacement.
“We will let Plus users choose to continue to use 4o,” Altman says. “We will watch usage as we think about how long to offer legacy models for.”
For months, ChatGPT fans have been waiting for the launch of GPT-5, which OpenAI says comes with major improvements to writing and coding capabilities over its predecessors. But shortly after the flagship AI model launched, many users wanted to go back.
This articles focuses on five core AI agent trends for 2025: Agentic Retrieval-Augmented Generation (RAG), Voice Agents, AI Agent Protocols, DeepResearch Agents, Coding Agents, and Computer Using Agents (CUA).
“The rhetoric was, if you just learned to code, work hard and get a computer science degree, you can get six figures for your starting salary,” Ms. Mishra, now 21, recalls hearing as she grew up in San Ramon, Calif.
Those golden industry promises helped spur Ms. Mishra to code her first website in elementary school, take advanced computing in high school and major in computer science in college. But after a year of hunting for tech jobs and internships, Ms. Mishra graduated from Purdue University in May without an offer.
“I just graduated with a computer science degree, and the only company that has called me for an interview is Chipotle,” Ms. Mishra said in a get-ready-with-me TikTok video this summer that has since racked up more than 147,000 views.
But now, the spread of A.I. programming tools, which can quickly generate thousands of lines of computer code — combined with layoffs at companies like Amazon, Intel, Meta and Microsoft — is dimming prospects in a field that tech leaders promoted for years as a golden career ticket. The turnabout is derailing the employment dreams of many new computing grads and sending them scrambling for other work.
Why it matters: GPT-5 embodies a “team of specialists” approach—fast small models for most tasks, powerful ones for hard problems—reflecting NVIDIA’s “heterogeneous agentic system” vision. This could evolve into orchestration across dozens of specialized models, mirroring human collective intelligence.
Bottom line: GPT-5 isn’t AGI, but it’s a leap in usability, reliability, and breadth—pushing ChatGPT toward being a truly personal, expert assistant.
…and another article from Grant Harvey:
GPT-5 is here… here’s everything you need to know (so far…). OpenAI launched GPT-5—described as its most capable model to date—now in ChatGPT (with higher usage limits for paid tiers) and the API, bringing stronger reasoning/coding/math/writing and safety improvements, yet, per Sam Altman, still short of AGI.
Why it matters: OpenAI’s move to replace its flurry of models with a unified GPT-5 simplifies user experience and gives everyone a PhD-level assistant, bringing elite problem-solving to the masses. The only question now is how long it can hold its edge in this fast-moving AI race, with Anthropic, Google, and Chinese giants all catching up.
OpenAI’s ChatGPT-5 released — from getsuperintel.com by Kim “Chubby” Isenberg GPT-5’s release marks a new era of productivity, from specialized AI tool to universal intelligence partner
The Takeaway
GPT-5’s unified architecture eliminates the effort of model switching and makes it the first truly seamless AI assistant that automatically applies the right level of reasoning for each task.
With 45% fewer hallucinations and 94.6% accuracy on complex math problems, GPT-5 exceeds the reliability threshold required for business-critical applications.
The model’s ability to generate complete applications from single prompts signals the democratization of software development and could revolutionize traditional coding workflows.
OpenAI’s “Safe Completions” training approach represents a new paradigm in AI safety, providing nuanced responses instead of blanket rejections for dual-use scenarios.
GPT-5 is live – but the community is divided— from getsuperintel.com by Kim “Chubby” Isenberg For some, it’s a lightning-fast creative partner; for others, it’s a system that can’t even decide when to think properly
Many had hoped that GPT-5 would finally unite all models – reasoning, image and video generation, voice – “one model to rule them all,” but this expectation has not been met.
GPT-5 marks a profound change in the human/machine relationship.
OBSERVATION #1: Up until yesterday, using OpenAI, you could pick the exact model variant for your task: the one tuned for reasoning, for writing, for code, or for math. Each had its own strengths, and experienced users learned which to reach for and when. In GPT-5, those choices are gone. There’s just “GPT-5,” and the routing decisions of which mode, which tool, which underlying approach is made by the model.
For a beginner, that’s a blessing. Most novice users never knew the differences between the models anyway. They used the same one regardless of the task.
For an experienced user, the jury’s still out. On one hand, the routing could save time. On the other, it introduces unpredictability: you can no longer reliably choose the optimal model for your purpose. If GPT-5’s choice is wrong, you’re stuck re-prompting rather than switching.
Why it matters:
GPT-5 signals a shift in AI’s evolution: progress through refinement, not revolution. While benchmarks show incremental gains, the real win is accessibility. Cheaper models (from $0.05 per million tokens) make AI more available to developers and casual users. This aligns with the Jevons Paradox, where lower costs could drive explosive adoption. However, the AGI hype faces reality checks. Fundraising may slow as investors focus on real-world utility over moonshots. For now, GPT-5 strengthens OpenAI’s market lead, proving AI’s future lies in practical applications, not just raw power.
I have had early access to GPT-51, and I wanted to give you some impressions of what it is and what it means. But the answer to the first question everyone will have is: Yes, this is a big deal. I asked GPT-5 to show you why by pasting this intro paragraph, exactly as you’re reading it, into ChatGPT, including the phrase: “you are GPT-5, do something very dramatic to illustrate my point, it has to fit into the next paragraph.”
That was the only prompt I gave it. It “thought” for 24 seconds and wrote:
Thunderstruck. Here, watch. I build worlds. See ideas become instruments. I code, compose, and converse. Stories synthesize science; solutions spark, swiftly. Asks arrive; answers appear, astonishingly, across domains. Behold: business plans, blueprints, briefs, beautifully built, briskly. I infer intent, integrate insight, and iterate instantly, indefatigably. Gaps get gauged; goals get generated, guarded, and guaranteed gracefully. During dialogue, disparate data distills down; decisions develop deliberately, deftly, dependably. Everything explained efficiently, even ethics: evidence examined, empathy engaged, everywhere, everyday, equitably. All at once, ambiguous arguments align as actionable, accurate advice awaits anyone anywhere. Look: language, logic, learning, and long-term memory link, lifting lives and labor limitlessly worldwide.
As today’s college graduates struggle to start a steady career, 1 in 2 Americans say their college major didn’t prepare them for the job market, according to a June 18 report from Preply.
Beyond that, 1 in 6 Americans who went to college said they regret it. When thinking about their college experience, college graduates said their top regrets included taking out student loans, not networking more and not doing internships.
College graduates said they felt unprepared in numerous ways, especially finding a job after graduation and navigating student debt and personal finances.
From DSC: The Career Placement Office at Northwestern University did not help build my skills to get a job, at all. I had no clue what I was doing. I had no idea what networking was even about, nor the power of it, and why it would be useful throughout my career. They provided conference rooms for interviews to occur…and that was about it, at least in my experience. In terms of my education, I didn’t get any real-world experience (such as apprenticeships, internships, capstone courses, etc.), nor did I pick up many practical or technical skills.
The call for transformation in higher education has never been louder, yet the path forward remains unclear for many institutions. Leaders often struggle with the “how” of meaningful change. This five-part playbook by higher education author and strategist Jeff Selingo as well as other experts draws on proven methodologies to provide clear, actionable guidance from mapping current institutional culture to sustaining long-term momentum.
A mismatch exists between the importance employers are putting on skilled trades and how the generation that’s newly joining the workforce views those jobs, a Harris poll finds.
Gen Z, the oldest members of which are 28, is the age cohort least focused on skilled trades, in part because they’re misinformed about the jobs, says the report based on 2,200 respondents to survey questions posted online in June.
“Only 38% of Gen Z says skilled trades offer the best job opportunities today” and “only 36% strongly agree skilled trades offer a faster and more affordable path to a good career,” the report says.
