Making Learning Matter— from emilypittsdonahoe.substack.com by Emily Pitts Donahoe We’ve got to get better at talking to students
In a recent newsletter, John Warner articulated a problem I’ve been mulling over for quite some time now:
“The challenge is to convince students that there is a genuine benefit in the struggle of learning as something distinct from the steady forced march of schooling. How do I convey the genuine value of thinking when the cultural message of the moment is the opposite?”
If higher education is to have any meaningful future at all, we have to find real answers to this question.
So, for a long time, I’ve been lamenting that we don’t talk enough with students about the value of work in our disciplines. We should devote more time to exploring how this knowledge operates in the real world! We should explicitly communicate its benefits not only for students’ future professional lives but also for their personal lives, and for the world at large! We should give them a self-transcendent purpose for learning! We should show them that what they learn has real, tangible meaning beyond the classroom!
The vast majority of today’s college students — 93% — believe generative AI training should be included in degree programs,according to a recent Coursera report. What’s more, 86% of students consider gen AI the most crucial technical skill for career preparation, prioritizing it above in-demand skills such as data strategy and software development. And 94% agree that microcredentials help build the essential skills they need to achieve career success.
For itsMicrocredentials Impact Report 2025, Coursera surveyed more than 1,200 learners and 1,000 employers around the globe to better understand the demand for microcredentials and their impact on workforce readiness and hiring trends.
A quarter of employers surveyed said they will remove bachelor’s degree requirements for some roles by the end of 2025, according to a May 20 report from Resume Templates.
In addition, 7 in 10 hiring managers said their company looks at relevant experience over a bachelor’s degree while making hiring decisions.
…
In the survey of 1,000 hiring managers, 84% of companies that recently removed degree requirements said it has been a successful move. Companies without degree requirements also reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.
Cultivating a responsible innovation mindset among future tech leaders — from timeshighereducation.com by Andreas Alexiou The classroom is a perfect place to discuss the messy, real-world consequences of technological discoveries, writes Andreas Alexiou. Beyond ‘How?’, students should be asking ‘Should we…?’ and ‘What if…?’ questions around ethics and responsibility
University educators play a crucial role in guiding students to think about the next big invention and its implications for privacy, the environment and social equity. To truly make a difference, we need to bring ethics and responsibility into the classroom in a way that resonates with students. Here’s how.
…
Debating with industry pioneers on incorporating ethical frameworks in innovation, product development or technology adoption is eye-opening because it can lead to students confronting assumptions they hadn’t questioned before. For example, students could discuss the roll-out of emotion-recognition software. Many assume it’s neutral, but guest speakers from industry can highlight how cultural and racial biases are baked into design decisions.
Leveraging alumni networks and starting with short virtual Q&A sessions instead of full lectures can work well.
Are we overlooking the power of autonomy when it comes to motivating students? — from timeshighereducation.com by Danny Oppenheimer Educators fear giving students too much choice in their learning will see them making the wrong decisions. But structuring choice without dictating the answers could be the way forward
So, how can we get students to make good decisions while still allowing them agency to make their own choices, maintaining the associated motivational advantages that agency provides? One possibility is to use choice architecture, more commonly called “nudges”: structuring choices in ways that scaffold better decisions without dictating them.
…
Higher education rightly emphasises the importance of belonging and mastery, but when it ignores autonomy – the third leg of the motivational tripod – the system wobbles. When we allow students to decide for themselves how they’ll engage with their coursework, they consistently rise to the occasion. They choose to challenge themselves, perform better academically and enjoy their education more.
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.
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).
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.
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’ — 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.
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:
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.
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.
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.
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.
.Get the 2025 Student Guide to Artificial Intelligence — from studentguidetoai.org This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U). .
Agentic AI is taking these already huge strides even further. Rather than simply asking a question and receiving an answer, an AI agent can assess your current level of understanding and tailor a reply to help you learn. They can also help you come up with a timetable and personalized lesson plan to make you feel as though you have a one-on-one instructor walking you through the process. If your goal is to learn to speak a new language, for example, an agent might map out a plan starting with basic vocabulary and pronunciation exercises, then progress to simple conversations, grammar rules and finally, real-world listening and speaking practice.
…
For instance, if you’re an entrepreneur looking to sharpen your leadership skills, an AI agent might suggest a mix of foundational books, insightful TED Talks and case studies on high-performing executives. If you’re aiming to master data analysis, it might point you toward hands-on coding exercises, interactive tutorials and real-world datasets to practice with.
The beauty of AI-driven learning is that it’s adaptive. As you gain proficiency, your AI coach can shift its recommendations, challenge you with new concepts and even simulate real-world scenarios to deepen your understanding.
Ironically, the very technology feared by workers can also be leveraged to help them. Rather than requiring expensive external training programs or lengthy in-person workshops, AI agents can deliver personalized, on-demand learning paths tailored to each employee’s role, skill level, and career aspirations. Given that 68% of employees find today’s workplace training to be overly “one-size-fits-all,” an AI-driven approach will not only cut costs and save time but will be more effective.
This is one reason why I don’t see AI-embedded classrooms and AI-free classrooms as opposite poles. The bone of contention, here, is not whether we can cultivate AI-free moments in the classroom, but for how long those moments are actually sustainable.
Can we sustain those AI-free moments for an hour? A class session? Longer?
…
Here’s what I think will happen. As AI becomes embedded in society at large, the sustainability of imposed AI-free learning spaces will get tested. Hard. I think it’ll become more and more difficult (though maybe not impossible) to impose AI-free learning spaces on students.
However, consensual and hybrid AI-free learning spaces will continue to have a lot of value. I can imagine classes where students opt into an AI-free space. Or they’ll even create and maintain those spaces.
Duolingo’s AI Revolution — from drphilippahardman.substack.com by Dr. Philippa Hardman What 148 AI-Generated Courses Tell Us About the Future of Instructional Design & Human Learning
Last week, Duolingo announced an unprecedented expansion: 148 new language courses created using generative AI, effectively doubling their content library in just one year. This represents a seismic shift in how learning content is created — a process that previously took the company 12 years for their first 100 courses.
As CEO Luis von Ahn stated in the announcement, “This is a great example of how generative AI can directly benefit our learners… allowing us to scale at unprecedented speed and quality.”
In this week’s blog, I’ll dissect exactly how Duolingo has reimagined instructional design through AI, what this means for the learner experience, and most importantly, what it tells us about the future of our profession.
Medical education is experiencing a quiet revolution—one that’s not taking place in lecture theatres or textbooks, but with headsets and holograms. At the heart of this revolution are Mixed Reality (MR) AI Agents, a new generation of devices that combine the immersive depth of mixed reality with the flexibility of artificial intelligence. These technologies are not mere flashy gadgets; they’re revolutionising the way medical students interact with complicated content, rehearse clinical skills, and prepare for real-world situations. By combining digital simulations with the physical world, MR AI Agents are redefining what it means to learn medicine in the 21st century.
4 Reasons To Use Claude AI to Teach — from techlearning.com by Erik Ofgang Features that make Claude AI appealing to educators include a focus on privacy and conversational style.
After experimenting using Claude AI on various teaching exercises, from generating quizzes to tutoring and offering writing suggestions, I found that it’s not perfect, but I think it behaves favorably compared to other AI tools in general, with an easy-to-use interface and some unique features that make it particularly suited for use in education.
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.
DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI
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.”
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.
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.
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.
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.
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 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.
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.
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 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.
Micro-Credentials Impact Report— from coursera.org Get exclusive insights on how industry-aligned micro- credentials are bridging skill gaps, driving career outcomes, and building a future-ready workforce—with data from 2,000+ students and employers across six regions.
See how micro-credentials are driving student success, meeting industry demand, and transforming higher education institutions. Deliver industry-aligned learning with confidence—whether you’re leading a university or designing workforce development programs.
…
Our data shows that 90% of employers are willing to offer higher starting salaries to those with micro-credentials. Most offer 10–15% more for credit-bearing vs. non-credit credentials—even higher for GenAI. Help your graduates earn more by integrating micro-credentials into your programs.
…
Students are 2x as likely to choose programs with micro-credentials—even more if credentials are credit-bearing, the report finds. Higher education leaders echo this trend, with 7 in 10 saying students are more likely to enroll in programs that offer micro-credentials for academic credit.
This report is the first in a series that examines three distinct workforce domains in higher education in 2025 (teaching and learning, cybersecurity and privacy, and IT leadership) to determine the priorities and challenges facing the profession. The findings in this report, taken from a survey of teaching and learning professionals in higher education, highlight their perspectives on a range of topics:
Flexible work arrangements
Integration of technologies
Workload and staffing
Job satisfaction and transition/succession planning
AI agents arrive in US classrooms — from zdnet.com by Radhika Rajkumar Kira AI’s personalized learning platform is currently being implemented in Tennessee schools. How will it change education?
AI for education is a new but rapidly expanding field. Can it support student outcomes and help teachers avoid burnout?
On Wednesday, AI education company Kira launched a “fully AI-native learning platform” for K-12 education, complete with agents to assist teachers with repetitive tasks. The platform hosts assignments, analyzes progress data, offers administrative assistance, helps build lesson plans and quizzes, and more.
“Unlike traditional tools that merely layer AI onto existing platforms, Kira integrates artificial intelligence directly into every educational workflow — from lesson planning and instruction to grading, intervention, and reporting,” the release explains. “This enables schools to improve student outcomes, streamline operations, and provide personalized support at scale.”
“Teachers today are overloaded with repetitive tasks. A.I. agents can change that, and free up their time to give more personalized help to students,” Ng said in a statement.
Kira was co-founded by Andrea Pasinetti and Jagriti Agrawal, both longtime collaborators of Ng. The platform embeds A.I. directly into lesson planning, instruction, grading and reporting. Teachers can instantly generate standards-aligned lesson plans, monitor student progress in real time and receive automated intervention strategies when a student falls behind.
Students, in turn, receive on-demand tutoring tailored to their learning styles. A.I. agents adapt to each student’s pace and mastery level, while grading is automated with instant feedback—giving educators time to focus on teaching.
‘Using GenAI is easier than asking my supervisor for support’ — from timeshighereducation.com Doctoral researchers are turning to generative AI to assist in their research. How are they using it, and how can supervisors and candidates have frank discussions about using it responsibly?
Generative AI is increasingly the proverbial elephant in the supervisory room. As supervisors, you may be concerned about whether your doctoral researchers are using GenAI. It can be a tricky topic to broach, especially when you may not feel confident in understanding the technology yourself.
While the potential impact of GenAI use among undergraduate and postgraduate taught students, especially, is well discussed (and it is increasingly accepted that students and staff need to become “AI literate”), doctoral researchers often slip through the cracks in institutional guidance and policymaking.
When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.
…
The glaring contrast between the perceived ubiquity of GenAI and its actual use also reveals fundamental challenges associated with the practical application of these tools. This article explores two key questions about GenAI to address common misconceptions and encourage broader adoption and more effective use of these tools in higher education.
Like many of you, I spent the first part of this week at Learning Technologies in London, where I was lucky enough to present a session on the current state of AI and L&D.
In this week’s blog post, I summarise what I covered and share an audio summary of my paper for you to check out.
Bridging the AI Trust Gap— from chronicle.com by Ian Wilhelm, Derek Bruff, Gemma Garcia, and Lee Rainie
In a 2024 Chronicle survey, 86 percent of administrators agreed with the statement: “Generative artificial intelligence tools offer an opportunity for higher education to improve how it educates, operates, and conducts research.” In contrast, just 55 percent of faculty agreed, showing the stark divisions between faculty and administrative perspectives on adopting AI.
Among many faculty members, a prevalent distrust of AI persists — and for valid reasons. How will it impact in-class instruction? What does the popularity of generative AI tools portend for the development of critical thinking skills for Gen-Z students? How can institutions, at the administrative level, develop policies to safeguard against students using these technologies as tools for cheating?
Given this increasing ‘trust gap,’ how can faculty and administrators work together to preserve academic integrity as AI seeps into all areas of academia, from research to the classroom?
Join us for “Bridging the AI Trust Gap,” an extended, 75-minute Virtual Forum exploring the trust gap on campus about AI, the contours of the differences, and what should be done about it.
Boosting Engagement by Taking Math Outdoors— from edutopia.org by Sandy Vorensky Bringing elementary students outside for math lessons provides a welcome change of pace and a chance for new activities.
How to Help Students Avoid Procrastinating — from edutopia.org by Sarah Kesty A simple strategy can help students map out their assignments in manageable chunks so they can stay on top of their work.
Long-term projects and assignments present a unique challenge for many students, requiring several layers of executive function skills, like planning and time management, to be able to manage steps over an extended period of time. Much to our frustration, students may procrastinate or avoid working on an assignment when it seems overwhelming. This can lead to late, missing, or incomplete work, or it can push students into a stressful all-nighter, as they complete an assignment designed to take weeks in the span of just a few hours.
An effective way to address the challenges of overwhelm and procrastination—and a way that requires only a tweak to your teaching instead of another task on your plate—is to teach students to “scan and plan.” Scan and plans happen during the introduction of an assignment, usually one that takes more than a few steps. Teachers organically fold in the scan and plan approach as a layer to the assignment’s announcement to the class.
A market report from Validated Insights released this month notes that fewer colleges and universities hire external online program management (OPM) companies to develop their courses.
For 2024, higher education institutions launched only 81 new partnerships with OPMs — a drop of 42% and the lowest number since 2016.
The report showed that institutions increasingly pay OPMs a fee-for-service instead of following a revenue-sharing model with big service bundles and profit splits.
Experts say revenue-sharing models, which critics denounce as predatory arrangements, incentivize service providers to use aggressive recruiting tactics to increase enrollments and maximize tuition revenue.
According to the report, fee-for-service has become the dominant business model for OPMs.
While school-led professional development can be helpful, there are online professional learning communities on various edtech websites that can be leveraged. Also, some of these community spaces offer the chance to monetize your work.
Here is a summary of six online edtech professional learning spaces.
4 ways community colleges can boost workforce development — from highereddive.com by Natalie Schwartz Higher education leaders at this week’s ASU+GSV Summit gave advice for how two-year institutions can boost the economic mobility of their students.
SAN DIEGO — How can community colleges deliver economic mobility to their students?
College leaders at this week’s ASU+GSV Summit, an annual education and technology conference, got a glimpse into that answer as they heard how community colleges are building support from business and industry and strengthening workforce development.
These types of initiatives may be helping to boost public perception of the value of community colleges vs. four-year institutions.
The student experience in higher education is continually evolving, influenced by technological advancements, shifting student needs and expectations, evolving workforce demands, and broadening sociocultural forces. In this year’s report, we examine six critical aspects of student experiences in higher education, providing insights into how institutions can adapt to meet student needs and enhance their learning experience and preparation for the workforce:
Satisfaction with Technology-Related Services and Supports
Modality Preferences
Hybrid Learning Experiences
Generative AI in the Classroom
Workforce Preparation
Accessibility and Mental Health
DSC: Shame on higher ed for not preparing students for the workplace (see below). You’re doing your students wrong…again. Not only do you continue to heap a load of debt on their backs, but you’re also continuing to not get them ready for the workplace. So don’t be surprised if eventually you’re replaced by a variety of alternatives that students will flock towards. .
