Tag: Learning

  • Making human learning visible in a world of invisible AI

    Making human learning visible in a world of invisible AI

    The mainstreaming of disruptive technology is a familiar experience.

    Consider how quickly contactless payment has become largely unavoidable and assumed for most of us.

    In a similar way, we are already seeing how generative artificial intelligence (GenAI) is, even more rapidly, weaving itself into the fabric of education, work, and wider society.

    In higher education’s search for appropriate responses to the rise of GenAI, much of the emphasis has focused on the technology itself. Yet, as machine learning becomes increasingly embedded in everyday tools and student learning practices, we suggest that this brings new urgency to making the ongoing value of human learning visible. Not to do so risks leaving universities struggling to explain, in an era of increasingly invisible GenAI, what is distinctive about higher education at all.

    A revealing weakness

    Our starting point for a meaningful response to this has been a focus on critical thinking. For a long time, institutions have expressed the importance of students developing as capable critical thinkers through high-level signifiers like graduate attributes, employability skills, and course learning outcomes. But these often substitute for shared understanding, signalling value without making it visible. The rise of GenAI does not challenge critical thinking so much as it reveals our existing weakness in articulating its substance and connection to practice.

    If we were to ask you what critical thinking meant to you, what would you say? And would your students think the same? Through a QAA-funded Collaborative Enhancement Project with colleagues from Stellenbosch University, we have been asking teachers these same questions. While each person we spoke to was quick to value it as an essential learning outcome, we were struck by the extent to which staff acknowledged how little time they had spent reflecting on what it meant to them.

    Through extended conversations with colleagues from our two universities we were able to explore what critical thinking meant in a range of disciplines, and to capture the diverse richness of associated practices, from a search for truth, a testing of beliefs, and an openness to critique to systematic analysis and structured argumentation.

    The right answer?

    Colleagues also identified both strengths and barriers in students’ engagement with critical thinking. Some highlighted students’ social awareness and willingness to experiment, while others noted that students often demonstrate criticality in everyday life but struggle to transfer it to academic tasks. Barriers included a tendency to seek “right answers” rather than engage with ambiguity. As one lecturer observed, “students want the correct answer, not the messy process”. Participants also reflected on the influence of GenAI, with some warning that this technology “gives answers too easily” – allowing students to “skip the hard thinking” – while others suggested it could create space for deeper critical engagement if used thoughtfully.

    From the student perspective, surveys at both institutions also revealed broadly positive perceptions of critical thinking as an essential graduate capability, with respondents articulating their belief in its long-term value including in relation to GenAI, but expressing uncertainty as to how such skills were embedded in their programmes.

    The depth of staff responses demonstrates that a collective wellspring of understanding exists. What we need to do more is find ways to bring this to the surface to inform teaching and learning, communicate explicitly to students, and give substance to the claims we make for higher education’s purpose.

    With this practical end in mind, we used our initial findings to develop a Critical Thinking Framework structured around three interrelated dimensions: Critical Clarity, Critical Context, and Critical Capital. This framework supports educators in identifying the forms of critical thinking they wish to prioritise, recognising barriers that may inhibit its development, and situating these within disciplinary and institutional contexts. It serves both as a reflective tool and a practical design resource, guiding staff in creating learning activities and assessments that make human thinking processes visible in a GenAI-rich educational landscape. This framework and a set of supporting resources, along with our full project report, are now available on the QAA website.

    The slowdown and the human factor

    By working with educators in this way, we have seen the adoption of approaches that slow learning down, providing space to support reflection and make the mechanics of critical thinking more visible to learners. Drawing on popular culture through the use of materials that are familiar to students, such as advertising, music and film, has been used as an approach to reduce cognitive load, enabling learners to focus on actually practising thinking critically in ways that are more visible and explicit.

    Having put this approach into practice, the feedback received across both institutions suggests that our framework not only supports staff in designing effective approaches to promote critical thinking but also gives students opportunity to articulate what it means to them to think critically. As students and staff have been given the opportunity to pause and reflect, it has underpinned meaningful awareness of the value of the human component in learning.

    The growth of GenAI has disrupted the higher education sector and challenged leaders and practitioners alike to think differently and creatively about how they prepare graduates for the future. As an international collaboration, this project has reinforced the view that this challenge is not limited to any single institution, and that there is much to be gained from fostering shared understanding. The results have reminded us that effective solutions can include those that are low-cost and low-risk, simple and practical.

    GenAI makes visible what universities have left implicit for too long. Higher education needs to slow down, not to resist GenAI, but to better articulate and advocate for human learning.

    Join us at The Secret Life of Students on Tuesday 17 March at the Shaw Theatre in London to keep the conversation going about what it means to learn as a human in the age of AI. 

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  • Sparking civic engagement as we approach America’s 250th

    Sparking civic engagement as we approach America’s 250th

    Key points:

    Imagine students who understand how government works and who see themselves as vital contributors to their communities. That’s what happens when students are given opportunities to play a role in their school, district, and community. In my work as a teacher librarian, I have learned that even the youngest voices can be powerful, and that students embrace civic responsibility and education when history is taught in a way that’s relevant and meaningful. 

    Now is the moment to build momentum and move our curriculum forward. It’s time to break past classroom walls and unite schools and communities. As our nation’s 250th anniversary approaches, education leaders have a powerful opportunity to teach through action and experience like never before. 

    Kids want to matter. When we help them see themselves as part of the world instead of watching it pass by, they learn how to act with purpose. By practicing civic engagement, students gain the skills to contribute solutions–and often offer unique viewpoints that drive real change. In 2023, I took my students [CR1] to the National Mall. They were in awe of how history was represented in stone, how symbolism was not always obvious, and they connected with rangers from the National Park Service as well as visitors in D.C. that day. 

    When students returned from the Mall, they came back with a question that stuck: “Where are the women?” In 2024, we set out to answer two questions together: “Whose monuments are missing?” and “What is HER name?” 

    Ranger Jen at the National Mall, with whom I worked with before, introduced me to Dr. Linda Booth Sweeney, author of Monument Maker, which inspired my approach. Her book asks, “History shapes us–how will we shape history?” Motivated by this challenge, students researched key women in U.S. history and designed monuments to honor their contributions. 

    We partnered with the Women’s Suffrage National Monument, and some students even displayed their work at the Belmont-Paul Women’s Equality National Monument. Through this project, questions were asked, lessons were learned, and students discovered the power of purpose and voice. By the end of our community-wide celebration, National Mall Night, they were already asking, “What’s next?” 

    The experience created moments charged with importance and emotion–moments students wanted to revisit and replicate as they continue shaping history themselves. 

    Reflecting on this journey, I realized I often looked through a narrow lens, focusing only on what was immediately within my school. But the broader community, both local and online, is full of resources that can strengthen relationships, provide materials, and offer strategies, mentors, and experiences that extend far beyond any initial lesson plan. 

    Seeking partnerships is not a new idea, but it can be easily overlooked or underestimated. I’ve learned that a “no” often really means “not yet” or “not now,” and that persistence can open doors. Ford’s Theatre introduced me to Ranger Jen, who in turn introduced me to Dr. Sweeney and the Trust for the National Mall. When I needed additional resources, the Trust for the National Mall responded, connecting me with the new National Mall Gateway: a new digital platform inspired by America’s 250th that gives all students, educators and visitors access to explore and connect with history and civics through the National Mall. 

    When I first shared the Gateway with students, it took their breath away. They could reconnect with the National Mall–a place they were passionate about–with greater detail and depth. I now use the platform to teach about monuments and memorials, to prepare for field trips, and to debrief afterward. The platform brings value for in-person visits to the National Mall, and for virtual field trips in the classroom, where they can almost reach out and touch the marble and stone of the memorials through 360-degree video tours. 

    Another way to spark students’ interest in civics and history is to weave civic learning into every subject. The first step is simple but powerful: Give teachers across disciplines the means to integrate civic concepts into their lessons. This might mean collaborating with arts educators and school librarians to design mini-lessons, curate primary sources, or create research challenges that connect past and present. It can also take shape through larger, project-based initiatives that link classroom learning to real-world issues. Science classes might explore the policies behind environmental conservation, while math lessons could analyze community demographics or civic data. In language arts, students might study speeches, letters, or poetry to see how language drives change. When every subject and resource become hubs for civic exploration, students begin to see citizenship as something they live, not just study. 

    Students thrive when their learning has purpose and connection. They remember lessons tied to meaningful experiences and shared celebrations. For instance, one of our trips to the National Mall happened when our fourth graders were preparing for a Veterans Day program with patriotic music. Ranger Jen helped us take it a step further, building on previous partnerships and connections–she arranged for the students to sing at the World War II Memorial. As they performed “America,” Honor Flights unexpectedly arrived. The students were thrilled to sing in the nation’s capital, of course. But the true impact came from their connection with the veterans who had lived the history they were honoring. 

    As our nation approaches its 250th anniversary, we have an extraordinary opportunity to help students see themselves as part of the story of America’s past, present, and future.

    Encourage educator leaders to consider how experiential civics can bring this milestone to life. Invite students to engage in authentic ways, whether through service-learning projects, policy discussions, or community partnerships that turn civic learning into action. Create spaces in your classes for collaboration, reflection, and application, so that students are shaping history, not just studying it. Give students more than a celebration. Give them a sense of purpose and belonging in the ongoing story of our nation. 

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  • Measuring student global competency learning using direct peer connections

    Measuring student global competency learning using direct peer connections

    Key points:

    Our students are coming of age in a world that demands global competency. From economic interdependence to the accelerating effects of climate change and mass migration, students need to develop the knowledge and skills to engage and succeed in this diverse and interconnected world. Consequently, the need for global competency education is more important than ever.

    “Being born into a global world does not make people global citizens,” Andreas Schleicher of the Organization for Economic Cooperation and Development (OECD) has said. “We must deliberately and systematically educate our children in global competence.” 

    Here at Global Cities, we regularly talk with educators eager to bring global competency into their classrooms in ways that engage and excite students to learn. Educators recognize the need, but ask a vital question: How do we teach something we can’t measure?

    It’s clear that in today’s competitive and data-driven education environment, we need to expand and evaluate what students need to know to be globally competent adults. Global competency education requires evaluation tools to determine what and whether students are learning.

    The good news is that two recent independent research studies found that educators can use a new tool, the Global Cities’ Codebook for Global Student Learning Outcomes, to identify what global competency learning looks like and to assess whether students are learning by examining student writing. The research successfully used the evaluation tool for global competency programs with different models and curricula and across different student populations.

    Global Cities developed the Codebook to help researchers, program designers, and educators identify, teach, and measure global competency in their own classrooms. Created in partnership with Harvard Graduate School of Education’s The Open Canopy, the Codebook captures 55 observable indicators across four core global learning outcomes: Appreciation for Diversity, Cultural Understanding, Global Knowledge, and Global Engagement. The Codebook was developed using data from our own Global Scholars virtual exchange program, which since 2014 has connected more than 139,000 students in 126 cities worldwide to teach global competency.

    In Global Scholars, we’ve seen firsthand the excitement of directly connecting students with their international peers and sparking meaningful discussions about culture, community, and shared challenges. We know how teachers can effectively use the Codebook and how Global Cities workshops extend the reach of this approach to a larger audience of K-12 teachers. This research was designed to determine whether the same tool could be used to assess global competency learning in other virtual exchange programs, not only Global Cities’ Global Scholars program.

    These studies make clear that the Codebook can reliably identify global learning in diverse contexts and help educators see where and how their students are developing global competency skills in virtual exchange curricula. You can examine the tool (the Codebook) here. You can explore the full research findings here.

    The first study looked at two AFS Intercultural Programs curricula, Global You Changemaker and Global Up Teen. The second study analyzed student work from The Open Canopy‘s Planetary Health and Remembering the Past learning journeys.

    In the AFS Intercultural Programs data, researchers found clear examples of students from across the globe showing Appreciation for Diversity and Cultural Understanding. In these AFS online discussion boards, students showed evidence they were learning about their own and other cultures, expressed positive attitudes about one another’s cultures, and demonstrated tolerance for different backgrounds and points of view. Additionally, the discussion boards offered opportunities for students to interact with each other virtually, and there were many examples of students from different parts of the world listening to one another and interacting in positive and respectful ways. When the curriculum invited students to design projects addressing community or global issues, they demonstrated strong evidence of Global Engagement as well.

    Students in The Open Canopy program demonstrated the three most prevalent indicators of global learning that reflect core skills essential to effective virtual exchange: listening to others and discussing issues in a respectful and unbiased way; interacting with people of different backgrounds positively and respectfully; and using digital tools to learn from and communicate with peers around the world. Many of the Remembering the Past posts were especially rich and coded for multiple indicators of global learning.

    Together, these studies show that global competency can be taught–and measured. They also highlight simple, but powerful strategies educators everywhere can use:

    • Structured opportunities for exchange help students listen and interact respectfully with one another
    • Virtual exchange prompts students to share their cultures and experiences across lines of difference in positive, curious ways
    • Assignments that include reflection questions–why something matters, not just what it is–help students think critically about culture and global issues
    • Opportunities for students to give their opinion and to decide to take action, even hypothetically, builds their sense of agency in addressing global challenges

    The Codebook is available free to all educators, along with hands-on professional development workshops that guide teachers in using the tool to design curriculum, teach intentionally, and assess learning. Its comprehensive set of indicators gives educators and curriculum designers a menu of options–some they might not have initially considered–that can enrich students’ global learning experiences.

    Our message to educators is simple: A community of educators (Global Ed Lab), a research-supported framework, and practical tools can help you teach students global competency and evaluate their work.

    The question is no longer whether we need more global competency education. We clearly do. Now with the Codebook and the Global Ed Lab, teachers can learn how to teach this subject matter effectively and use tools to assess student learning.

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  • Florida’s Syllabus Regulations Will Stunt Learning (opinion)

    Florida’s Syllabus Regulations Will Stunt Learning (opinion)

    Over the past five years, I have adapted to a litany of new policies, procedures and restructurings at both the level of the college and the state: a shift in summer semester length, increased class sizes, a collegewide administrative reorganization, a syllabus review searching for language related to the Israel-Palestine conflict and state rewriting of course outcomes. Throughout all this, I remained radically optimistic, suspending any criticism—and the anticipated upheaval usually subsided. Most changes happen for good reason (they are not, usually, implemented arbitrarily) and are unobtrusive to my activities as a professor. In short, I am noncynical and receptive to change, up to a reasonable threshold.

    Florida’s newly amended regulations for college syllabi, which require professors at public universities to publish their syllabi at least 45 days before the first day of class, crosses the threshold of reason. While there are concerns about the laboriousness of submitting a syllabus 45 days prior to the term, as well as potential political issues of censorship (some faculty argue syllabi are being made public to persecute unfavored views), my objection to this new policy is neither labor-based nor political. What is plainly concerning to me is the stipulation that all “required and recommended” readings must be included on the syllabus before the semester starts. This means that no new readings can be added (since that would violate the binding, prepublished syllabus), making the reading list inflexible and leading to pedagogically stunted classrooms.

    This is not a proxy for a covert political argument. Actually, my criticism of static reading lists has nothing to do with politics, though the policies reflect a partisan political agenda: It is about pedagogy. The problem is not that the readings would be made public, but instead that they would be fixed, circumscribing professors’ creative interventions after a term has begun. Transparency is not what is at stake here; it is agency. Every instructor collates readings for a course before the start date (and, to be charitable, ensuring faculty prepare courses early—when possible—may be a good thing), but losing the ability to substitute readings during a semester is a diminution of effective teaching, which demands perpetual refinement.

    A good class will always evolve, however subtly, from semester to semester—a change in course policy, an additional reading (or omitted reading), a tweaked assignment or a new in-class activity that one discovers at a teaching conference. Occasionally, these changes are made intrasemesterly, spurred by the realization that another approach will better serve student learning. To be clear, an instructor probably should not outright replace their entire reading list midsemester, yet they must retain the ability to make decisions regarding readings as the semester unfolds, rather than be tethered to a static reading list. A college classroom necessitates instructor agency, and anything meaningfully restricting that agency renders the classroom, in turn, less dynamic for students.

    Consider how limiting an instructor’s ability to change readings, as needed, undermines a course’s engagement with the outside world. In the fall, I took a doctoral-level course on AI in the humanities. Although there were set readings each week, the professor provided weekly readings on AI software that was being developed in real time. The static readings, no matter how meticulously chosen, simply could not keep pace with this emergent technology, and the newly added weekly readings were often the most insightful. Florida’s new syllabus policy will preclude a practice like this. It is crucial to note that this was not, in any way, an unprepared instructor lazily adding readings as the term went on, but rather an instructor who was working harder by supplementing an already-robust reading list with freshly published material.

    In my own courses, as an instructor of first-year composition, I walk a continually renegotiated line between challenging students and facilitating discussion and interest. I’m aware that some of the readings may be difficult for students (for instance, when teaching them how to read peer-reviewed academic articles), yet other times, I want more accessible readings, ones that develop arguments that students can become really invested in, frequently on a topic they are already familiar with. That way, students can reflect on how compelling they find an argument (on something they may already have a partially developed position on)—and then, from there, we can dissect the argument together.

    Last semester, I swapped out some in-class readings for two recently published argumentative essays on the Labubu toy trend (a polished, well-researched article from a national publication and an imperfect opinion piece from a smaller publication). In this instance, the readings worked perfectly: The essays generated a lively discussion, not only about their content (Labubus and fleeting collectible trends in general) but also about the structure of the essays and their rhetorical effectiveness. Assigning texts like these demonstrates to students that writing isn’t a practice only occurring in the classroom, but an activity contending with the actual world, whether the subject is as timeless as poverty or as ephemeral as Labubus.

    How would it be possible to assign readings about a passing trend—to capture student interest—when all readings must be fixed before the trend even begins? A course can only be responsive to the world if the instructor has the requisite agency over the readings they assign. To a reasonable degree, reading lists must be adjustable.

    Of course, my example of arguments about Labubus is, in a sense, trivial—it isn’t actually about the content of the essays, but the fact that students could relate to the topical content (my courses teach students writing, argumentation and research—not consumer trends). Consider, though, a course in the hard sciences: If an instructor becomes aware of a new discovery, rendering a previous scientific claim outdated, should they not be permitted to exchange readings about the old claim with those about the new discovery? Or should they remain bound to outdated science in the name of “transparency”?

    I view the new mandate on syllabi and reading lists as an unfortunate precursor to overstandardization (the kind pervasive in the K–12 educational environment), which is explicitly restrictive. Pragmatically, as I’ve argued, there are grounds to avoid this encroachment into the instructor’s classroom since it subdues pedagogical inventiveness. However, we should think not only about the utility of autonomy, but also about the principle. A professor should retain autonomy over the delivery of material—structured around the state- and college-mandated outcomes of the course—because this is what it means for a student to take a course in college. A professor is not a convenient vessel for predetermined content; they are, at their best, an expert curator of material to facilitate student learning.

    Ask anyone, instructor or student, if they are better served by increased standardization and attenuated classroom novelty (whether in the name of transparency or not), and it seems to me beyond doubt that neither will say they prefer rote modes of learning to those that enable improvisation and up-to-the-moment expert curation.

    Teddy Duncan Jr. is an assistant professor of English at Valencia College.

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  • The 3 learning advantages of 3D printing

    The 3 learning advantages of 3D printing

    Key points:

    It’s truly incredible how much new technology has made its way into the classroom. Where once teaching consisted primarily of whiteboards and textbooks, you can now find tablets, smart screens, AI assistants, and a trove of learning apps designed to foster inquiry and maximize student growth.

    While these new tools are certainly helpful, the flood of options means that educators can struggle to discern truly useful resources from one-time gimmicks. As a result, some of the best tools for sparking curiosity, creativity, and critical thinking often go overlooked.

    Personally, I believe 3D printing is one such tool that doesn’t get nearly enough consideration for the way it transforms a classroom.

    3D printing is the process of making a physical object from a three-dimensional digital model, typically by laying down many thin layers of material using a specialized printer. Using 3D printing, a teacher could make a model of a fossil to share with students, trophies for inter-class competitions, or even supplies for construction activities.

    At first glance, this might not seem all that revolutionary. However, 3D printing offers three distinct educational advantages that have the potential to transform K–12 learning:

    1. It develops success skills: 3D printing encourages students to build a variety of success skills that prepare them for challenges outside the classroom. For starters, its inclusion creates opportunities for students to practice communication, collaboration, and other social-emotional skills. The process of moving from an idea to a physical, printed prototype fosters perseverance and creativity. Meanwhile, every print–regardless of its success–builds perseverance and problem-solving confidence. This is the type of hands-on, inquiry-based learning that students remember.
    2. It creates cross-curricular connections: 3D printing is intrinsically cross-curricular. Professional scientists, engineers, and technicians often use 3D printing to create product models or build prototypes for testing their hypotheses. This process involves documentation, symbolism, color theory, understanding of narrative, and countless other disciplines. It doesn’t take much imagination to see how these could also be beneficial to classroom learning. Students can observe for themselves how subjects connect, while teachers transform abstract concepts into tangible points of understanding.     
    3. It’s aligned with engineering and NGSS: 3D printing aligns perfectly with Next Gen Science Standards. By focusing on the engineering design process (define, imagine, plan, create, improve) students learn to think and act like real scientists to overcome obstacles. This approach also emphasizes iteration and evidence-based conclusions. What better way to facilitate student engagement, hands-on inquiry, and creative expression?

    3D printing might not be the flashiest educational tool, but its potential is undeniable. This flexible resource can give students something tangible to work with while sparking wonder and pushing them to explore new horizons.

    So, take a moment to familiarize yourself with the technology. Maybe try running a few experiments of your own. When used with purpose, 3D printing transforms from a common classroom tool into a launchpad for student discovery.

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  • From policy to practice: preparing for the Lifelong Learning Entitlement

    From policy to practice: preparing for the Lifelong Learning Entitlement

    This blog was kindly authored by Mark Jones, Executive Vice President – Education, TechnologyOne.

    Having worked with higher education institutions globally for three decades, I’ve seen policy-driven transformation succeed and fail. The difference comes down to whether institutions treat fundamental change as a strategic and commercial opportunity, or merely as a compliance burden.

    Across UK universities, conversations are increasingly centred on what the Lifelong Learning Entitlement (LLE) will mean in practice. The LLE fundamentally restructures how higher education is funded and accessed. Learners will be able to study modular provision at levels 4 to 6 in government-prioritised subjects, pay for individual credits, accumulate learning over decades, and transfer credits between providers.

    The policy intent – making higher education more accessible – is clear. For institutions built around three-year undergraduate programmes, delivering on that requires more than administrative adjustment. It demands a rethink of curriculum design, digital systems, academic regulations and student support models.

    A technology inflection point

    The LLE is more than a policy change. It represents a technology inflection point for higher education. For years, institutions have made incremental adjustments to systems designed for cohort-based, September-to-June academic cycles. The LLE exposes the limitations of those systems.

    Institutions will need to track lifetime credit accumulation across multiple providers, process granular payments that may be months or years apart, verify external prerequisites in real-time, and maintain learning relationships that span decades rather than discrete degree programmes.

    This creates space for innovation. The challenge is not simply to adapt existing platforms, but to reimagine student record systems, finance integration, and learner engagement from the ground up. The technologies that enable personalised digital experiences in sectors such as media streaming or retail banking offer relevant models. International developments – for example, micro-credentials in Australia – provide both cautionary tales and promising precedents.

    The question shifts from ‘How do we make current systems cope?’ to ‘What would we build if we designed for modular, lifelong, multi-provider learning from the outset?’

    The market waiting to be served

    The demand signals are clear. UCAS 2025 data shows UK mature acceptances (aged 21+) have declined 3.3% to 106,120, with steeper drops among those aged 30 and over. Meanwhile, 31% of UK 18-year-olds now intend to live at home while studying (89,510 students, up 6.9% from 2024), driven by affordability constraints.

    The Post-16 education and skills white paper explicitly recognises the need for workforce upskilling at scale. Career transitions require targeted learning rather than full degrees and learners need options that fit alongside work and caring responsibilities.

    The technology enabling this market – flexible enrolment, credit portability, lifetime learner accounts – represents a fundamental refresh of how higher education operates digitally. The LLE removes the policy barriers. The remaining question is whether institutions can build the infrastructure to deliver on the opportunity.

    The curriculum challenge that unlocks it

    Serving this market demands more than breaking degrees into smaller units. Each module must function as both a standalone learning experience and as a component that can stack with credits from other providers. Prerequisites must enable learners to navigate pathways independently. Assessment models must work for twelve-week episodes rather than three-year relationships.

    Academic regulations designed for continuous programmes need to adapt to episodic engagement over decades. Student services built around sustained relationships must be reimagined for twelve-week presences. These aren’t minor adjustments; they’re fundamental policy framework redesigns.

    Recognition of Prior Learning (RPL) becomes central rather than peripheral. The issue is not whether institutions can scale existing processes, but whether they can reimagine how learning is valued when it originates elsewhere.

    Timeline realism

    LLE applications open in September 2026. For institutions targeting January 2027 launches, timelines are extremely tight. Across the sector, universities are planning phased September 2027 launches with limited subject scope, rather than ambitious early rollouts that risk operational failure.

    Institutions making meaningful progress are treating LLE as a strategic transformation requiring executive vision. They are testing actual workflows, allocating dedicated resources, and making deliberate scope decisions that acknowledge building capability takes time. Importantly, they’re approaching LLE as an opportunity, not just an obligation.

    The transformation ahead

    The LLE creates space for institutions to rethink digital infrastructure fundamentally rather than incrementally. The most successful technology transformations occur when external pressure aligns with internal ambition – when ’we have to change’ meets ‘here’s what we could build’.

    Institutions approaching this purely as a compliance exercise experience compressed timelines and onerous requirements. Those that view it as an innovation catalyst find that it justifies investments in modern, integrated platforms that have been deferred for years. It enables a more ambitious question: ‘What would a student system designed for lifelong, modular, multi-provider learning actually look like?’

    The opportunity to serve learners historically excluded from higher education is genuine. So too is the opportunity to modernise infrastructure that has struggled under incremental adaptation. The sector’s challenge is translating policy ambition into operational reality for institutions, students, and the communities higher education serves. Those that thrive will be the ones that treat the LLE as permission to innovate, not just an obligation to comply.

    These implementation challenges and more will be explored at TechnologyOne Showcase London on 25 February at HERE & NOW at Outernet, featuring an executive panel with voices from UCISA, ARC, HEPI, SUMS, and institutional leaders discussing how governance, culture, technology, and commercial strategies need to adapt to this new policy landscape. Register for TechnologyOne Showcase here.

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  • Designing the 2026 Classroom: Emerging Learning Trends in an AI-Powered Education System – Faculty Focus

    Designing the 2026 Classroom: Emerging Learning Trends in an AI-Powered Education System – Faculty Focus

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  • The Future of Online Learning Is AI-Powered

    The Future of Online Learning Is AI-Powered

    AI-powered online learning is reshaping how higher education supports students, scales care, and prepares learners for an evolving workforce. This article explores how AI can help institutions close support gaps, improve outcomes, and lead intentionally in the future of online education—grounded in insights from Carnegie’s Online Learner & Leader Study.

    Online Learning Is Now Central to Institutional Strategy

    Higher education has always evolved in response to new tools, new learners, and new expectations. What makes this moment different is not just the pace of change, but the opportunity it presents.

    Online learning now sits at the center of institutional strategy. It is where access, innovation, workforce relevance, and financial sustainability intersect. And increasingly, it is where presidents and academic leaders have the greatest leverage to shape the future rather than react to it.

    AI is accelerating that shift toward AI-powered online learning. 

    Not as a disruption to fear, but as a capability to design for scale, support students more intentionally, and lead with clarity in a complex moment.

    This Moment Is About More Than Technology

    There is growing recognition that online learners are not a monolith. They are career builders, caregivers, degree completers, and explorers and they’re often balancing work, family, financial pressure, and uncertainty about what the future of work will demand.

    At the same time, higher education leaders are navigating an equally complex reality. Online enrollment growth is a priority. Budgets are not keeping pace. Staffing models were not designed for always-on, asynchronous, national audiences. Support teams are stretched thin.

    The result is a widening gap between what students need and what institutions can sustainably provide.

    This is not a failure of commitment. It is a structural mismatch.

    And it is precisely where AI creates a meaningful opportunity.

    AI as the Bridge Between Need and Capacity in Online Learning

    When leaders talk about AI in higher education, the conversation often jumps to tools, policies, or risk. Those matter. But they miss the larger shift underway.

    AI as Institutional Infrastructure

    AI is not just another system to adopt. It is a new layer of infrastructure.

    AI is like water. It should not live in a single pipe or department. It should flow through the entire institution—quietly, consistently, and in service of core needs.

    Nowhere is that more evident than in online student support.

    What Online Learners Say They Need

    Findings from Carnegie’s Online Learner & Leader Study demonstrated this clearly. Learners overwhelmingly said they value flexibility and autonomy. Most prefer asynchronous formats. But that same flexibility increases demand for timely, personalized, and reliable support—often outside traditional business hours. 

    Higher ed leaders in our study acknowledge the challenge. They also acknowledge the constraint: limited staffing and limited budgets.

    Scaling Support Without Replacing Human Connection

    This is where AI in online education can change the equation.

    Thoughtfully deployed AI support does not replace human connection. It scales it.

    AI enables institutions to provide consistent, responsive assistance for high-volume needs—course navigation, program policies, technology troubleshooting—while ensuring students can escalate to a human when it matters most. It helps institutions move from reactive support to proactive guidance. From fragmented touchpoints to a more seamless experience across the student lifecycle.

    Just as importantly, it allows institutions to do so in a way that is financially sustainable. By absorbing routine, high-volume interactions, AI frees human teams to focus on moments that require judgment, empathy, and expertise—protecting both the student experience and the institutional cost structure as online enrollment scales.

    In other words, AI becomes the connective tissue between student expectations and institutional reality.

    Differentiation Will Belong to the Institutions That Embed AI—Not Bolt It On

    As online options proliferate, differentiation has become harder to claim and easier to lose. Program quality remains foundational. But quality alone no longer determines which institutions students consider.

    Students navigate a crowded, search-driven marketplace. They look for clarity. Credibility. Signals that an institution understands their lives and is equipped for what comes next.

    AI as a Signal of Readiness and Relevance

    Increasingly, how institutions use AI in online education will be one of those signals.

    Not because students want novelty. But because they expect modern, technology-forward experiences that reflect the world they already inhabit.

    Integration Across the Student Lifecycle

    The institutions that stand apart will not be those with the most pilots or the flashiest tools. They will be the ones that integrate AI intentionally across systems:

    • Across the student lifecycle, from recruitment and onboarding to advising, persistence, and completion
    • Across support functions, ensuring consistency, transparency, and availability
    • Across academic and co-curricular experiences, reinforcing relevance and readiness

    This kind of integration sends a powerful message: we are prepared for this moment—and for the future our students are walking into.

    The inverse is also true. Institutions that delay or limit AI to isolated pilots risk falling behind not because of rankings or prestige, but because the lived experience they offer no longer matches learner expectations. Inaction is not neutral—it is a strategic choice with competitive consequences.

    Student Success and Workforce Readiness Are Now Intertwined

    AI is reshaping how learners think about their futures. Many express optimism about its potential. Just as many express anxiety—about job stability, ethical use, and keeping pace with change.

    They are not just asking institutions for credentials. They are asking for preparation.

    Preparing Students to Work Alongside AI

    The responsibility for higher education is clear. Institutions must help students develop not only knowledge, but fluency. Not only skills, but judgment.

    That does not require turning every online program into a technical degree. It does require embedding AI literacy, ethical reasoning, and applied use across disciplines—so graduates understand how to work alongside AI, not compete against it.

    Online learning is uniquely positioned to lead here. Its scale, flexibility, and digital foundation make it an ideal environment to normalize responsible AI use as part of learning itself—not an optional add-on, but an expected competency.

    When AI is embedded thoughtfully, student support and workforce preparation reinforce one another. Students experience AI as a tool for organization, exploration, and problem-solving. Institutions model how complex systems can be used responsibly, transparently, and in service of human goals.

    Supporting Faculty While Preserving the Human Core

    The same is true for faculty. 

    When AI is used to reduce administrative burden, support feedback and personalization, and streamline course management, it preserves faculty time for mentorship, inquiry, and teaching—reinforcing, rather than eroding, the human core of education.

    Governance Matters—But It Cannot Be the Only Strategy

    Many institutions are appropriately focused on AI governance, ethics, and integrity. Policies are essential. Guardrails matter.

    But governance alone does not constitute leadership.

    Balancing Discipline With Momentum

    The risk is not that institutions move too quickly. It is that they move cautiously without moving strategically.

    The Online Learner & Leader Study reveals a familiar pattern: learners are already engaging with AI in their daily lives, even as institutions deliberate. They are experimenting, adapting, and forming habits—often without institutional guidance.

    This creates an opportunity for higher education to lead with purpose.

    The most effective approaches balance discipline with momentum:

    • Clear guidance on ethical and acceptable use
    • Transparency about where and how AI is deployed
    • Human-centered design that keeps people—not tools—at the center
    • A focus on outcomes, not novelty

    Central to this balance is trust. Responsible stewardship of student data, clear boundaries around use, and transparency about decision-making are not compliance exercises—they are differentiators in a landscape where trust increasingly shapes choice.

    AI readiness is not about perfection. It is about alignment.

    What This Means for Higher Ed Leadership

    For senior leaders, the question is no longer whether AI will shape online learning. It already is.

    The question is whether institutions will allow that future to emerge unevenly—or design it intentionally.

    What Leadership Looks Like in an AI-Powered Future

    The institutions that lead will:

    • Treat AI as enterprise infrastructure, not a side project
    • Use AI to close support gaps, not widen them
    • Embed AI across the student lifecycle to improve experience and outcomes
    • Prepare students for an AI-enabled workforce with confidence and clarity
    • Differentiate themselves through coherence, not complexity

    Practically, this means starting where impact is greatest—often at key lifecycle moments like onboarding, advising, and student support—while building governance and implementation in parallel. AI readiness is not an IT initiative; it is a cabinet-level responsibility.

    This is not about replacing what makes education human. It is about protecting it—by ensuring systems can scale care, guidance, and opportunity in a moment of constraint.

    Looking Ahead: The Future of Online Learning

    Online learning is no longer peripheral. It is central to institutional resilience, relevance, and reach.

    AI will not determine the future of online education on its own. Leadership will.

    The data is clear. The expectations are rising. The tools are here.

    The opportunity now is to integrate AI in higher education like water—quietly, purposefully, and everywhere it can make learning more accessible, more supportive, and more aligned with the futures students are trying to build.

    For leaders interested in grounding these decisions in research and real learner insight, the Online Learner & Leader Study offers a clear view into where expectations and realities diverge—and where alignment can unlock meaningful impact.

    Frequently Asked Questions About AI in Online Education

    How is AI being used in online education today?

    AI is increasingly used to support online learners through personalized assistance, timely support, and scalable student services. Common applications include course navigation, advising support, technology troubleshooting, and proactive outreach.

    Why is AI important for online student support?

    Online learning increases flexibility but also raises expectations for responsiveness and personalization. AI helps institutions meet these expectations at scale while allowing human teams to focus on moments requiring judgment, empathy, and expertise.

    Does AI replace human interaction in online learning?

    No. When deployed thoughtfully, AI supports and scales human connection rather than replacing it. It handles routine, high-volume needs so faculty and staff can focus on meaningful engagement.

    How does AI prepare students for the future of work?

    AI-enabled online learning helps students build fluency, ethical awareness, and applied experience with AI tools—preparing them to work alongside AI in evolving professional environments.

    What insights does Carnegie’s Online Learner & Leader Study provide?

    The study highlights gaps between learner expectations and institutional capacity, particularly around flexibility, support, and preparedness for an AI-enabled future—offering leaders data-driven guidance for aligning strategy and execution.

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  • Teaching visual literacy as a core reading strategy in the age of AI

    Teaching visual literacy as a core reading strategy in the age of AI

    Key points:

    Many years ago, around 2010, I attended a professional development program in Houston called Literacy Through Photography, at a time when I was searching for practical ways to strengthen comprehension, discussion, and reading fluency, particularly for students who found traditional print-based tasks challenging. As part of the program, artists visited my classroom and shared their work with students. Much of that work was abstract. There were no obvious answers and no single “correct” interpretation.

    Instead, students were invited to look closely, talk together, and explain what they noticed.

    What struck me was how quickly students, including those who struggled with traditional reading tasks, began to engage. They learned to slow down, describe what they saw, make inferences, and justify their thinking. They weren’t just looking at images; they were reading them. And in doing so, they were rehearsing many of the same strategies we expect when reading written texts.

    At the time, this felt innovative. But it also felt deeply intuitive.

    Fast forward to today.

    Students are surrounded by images and videos, from photographs and diagrams to memes, screenshots, and, increasingly, AI-generated visuals. These images appear everywhere: in learning materials, on social media, and inside the tools students use daily. Many look polished, realistic, and authoritative.

    At the same time, AI has made faking easier than ever.

    As educators and school leaders, we now face urgent questions around misinformation, academic integrity, and critical thinking. The issue is no longer just whether students can use AI tools, but whether they can interpret, evaluate, and question what they see.

    This is where visual literacy becomes a frontline defence.

    Teaching students to read images critically, to see them as constructed texts rather than neutral data, strengthens the same skills we rely on for strong reading comprehension: inference, evidence-based reasoning, and metacognitive awareness.

    From photography to AI: A conversation grounded in practice

    Recently, I found myself returning to those early classroom experiences through ongoing professional dialogue with a former college lecturer and professional photographer, as we explored what it really means to read images in the age of AI.

    A conversation that grew out of practice

    Nesreen: When I shared the draft with you, you immediately focused on the language, whether I was treating images as data or as signs. Is this important?

    Photographer: Yes, because signs belong to reading. Data is output. Signs are meaning. When we talk about reading media texts, we’re talking about how meaning is constructed, not just what information appears.

    Nesreen: That distinction feels crucial right now. Students are surrounded by images and videos, but they’re rarely taught to read them with the same care as written texts.

    Photographer: Exactly. Once students understand that photographs and AI images are made up of signs, color, framing, scale, and viewpoint, they stop treating images as neutral or factual.

    Nesreen: You also asked whether the lesson would lean more towards evaluative assessment or summarizing. That made me realize the reflection mattered just as much as the image itself.

    Photographer: Reflection is key. When students explain why a composition works, or what they would change next time, they’re already engaging in higher-level reading skills.

    Nesreen: And whether students are analyzing a photograph, generating an AI image, or reading a paragraph, they’re practicing the same habits: slowing down, noticing, justifying, and revising their thinking.

    Photographer: And once they see that connection, reading becomes less about the right answer and more about understanding how meaning is made.

    Reading images is reading

    One common misconception is that visual literacy sits outside “real” literacy. In practice, the opposite is true.

    When students read images carefully, they:

    • identify what matters most
    • follow structure and sequence
    • infer meaning from clues
    • justify interpretations with evidence
    • revise first impressions

    These are the habits of skilled readers.

    For emerging readers, multilingual learners, and students who struggle with print, images lower the barrier to participation, without lowering the cognitive demand. Thinking comes first. Language follows.

    From composition to comprehension: Mapping image reading to reading strategies

    Photography offers a practical way to name what students are already doing intuitively. When teachers explicitly teach compositional elements, familiar reading strategies become visible and transferable.

    What students notice in an image What they are doing cognitively Reading strategy practiced
    Where the eye goes first Deciding importance Identifying main ideas
    How the eye moves Tracking structure Understanding sequence
    What is included or excluded Considering intention Analyzing author’s choices
    Foreground and background Sorting information Main vs supporting details
    Light and shadow Interpreting mood Making inferences
    Symbols and colour Reading beyond the literal Figurative language
    Scale and angle Judging power Perspective and viewpoint
    Repetition or pattern Spotting themes Theme identification
    Contextual clues Using surrounding detail Context clues
    Ambiguity Holding multiple meanings Critical reading
    Evidence from the image Justifying interpretation Evidence-based responses

    Once students recognise these moves, teachers can say explicitly:

    “You’re doing the same thing you do when you read a paragraph.”

    That moment of transfer is powerful.

    Making AI image generation teachable (and safe)

    In my classroom work pack, students use Perchance AI to generate images. I chose this tool deliberately: It is accessible, age-appropriate, and allows students to iterate, refining prompts based on compositional choices rather than chasing novelty.

    Students don’t just generate an image once. They plan, revise, and evaluate.

    This shifts AI use away from shortcut behavior and toward intentional design and reflection, supporting academic integrity rather than undermining it.

    The progression of a prompt: From surface to depth (WAGOLL)

    One of the most effective elements of the work pack is a WAGOLL (What A Good One Looks Like) progression, which shows students how thinking improves with precision.

    • Simple: A photorealistic image of a dog sitting in a park.
    • Secure: A photorealistic image of a dog positioned using the rule of thirds, warm colour palette, soft natural lighting, blurred background.
    • Greater Depth: A photorealistic image of a dog positioned using the rule of thirds, framed by tree branches, low-angle view, strong contrast, sharp focus on the subject, blurred background.

    Students can see and explain how photographic language turns an image from output into meaningful signs. That explanation is where literacy lives.

    When classroom talk begins to change

    Over time, classroom conversations shift.

    Instead of “I like it” or “It looks real,” students begin to say:

    • “The creator wants us to notice…”
    • “This detail suggests…”
    • “At first I thought…, but now I think…”

    These are reading sentences.

    Because images feel accessible, more students participate. The classroom becomes slower, quieter, and more thoughtful–exactly the conditions we want for deep comprehension.

    Visual literacy as a bridge, not an add-on

    Visual literacy is not an extra subject competing for time. It is a bridge, especially in the age of AI.

    By teaching students how to read images, schools strengthen:

    • reading comprehension
    • inference and evaluation
    • evidence-based reasoning
    • metacognitive awarenes

    Most importantly, students learn that literacy is not about rushing to answers, but about noticing, questioning, and constructing meaning.

    In a world saturated with AI-generated images, teaching students how to read visually is no longer optional.

    It is literacy.

    Author’s note: This article grew out of classroom practice and professional dialogue with a former college lecturer and professional photographer. Their contribution informed the discussion of visual composition, semiotics, and reflective image-reading, without any involvement in publication or authorship.

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  • How professional learning transformed our teachers

    How professional learning transformed our teachers

    Key points:

    When you walk into a math classroom in Charleston County School District, you can feel the difference. Students aren’t just memorizing steps–they’re reasoning through problems, explaining their thinking, and debating solutions with their peers. Teachers aren’t rushing to cover content, because their clear understanding of students’ natural learning progressions allows them to spend more time exploring the why behind the math.

    This cultural shift didn’t come from adopting a new curriculum or collecting more data. Instead, we transformed math education by investing deeply in our educators through OGAP (The Ongoing Assessment Project) professional learning–an approach that has reshaped not only instruction, but the confidence and professional identity of our teachers.

    Why we needed a change

    Charleston County serves more than 50,000 students across more than 80 schools. For years, math achievement saw small gains, but not the leaps we hoped for. Our teachers were dedicated, and we had high-quality instructional materials, but something was missing.

    The gap wasn’t our teacher’s effort. It was their insight–understanding the content they taught flexibly and deeply.

    Too often, instruction focused on procedures rather than understanding. Teachers could identify whether a student got a problem right or wrong, but not always why they responded the way they did. To truly help students grow, we needed a way to uncover their thinking and guide next steps more intentionally.

    What makes this professional learning different

    Unlike traditional PD that delivers a set of strategies to “try on Monday,” this learning model takes educators deep into how students develop mathematical ideas over time.

    Across four intensive days, teachers explore research-based learning progressions in additive, multiplicative, fractional, and proportional reasoning. They examine real student work to understand how misconceptions form and what those misconceptions reveal about a learner’s thought process. It is also focused on expanding and deepening teachers’ understanding of the content they teach so they are more flexible in their thinking. Teachers appreciate that the training isn’t abstract; it’s rooted in everyday classroom realities, making it immediately meaningful.

    Instead of sorting responses into right and wrong, teachers ask a more powerful question: What does this show me about how the student is reasoning?

    That shift changes everything. Teachers leave with:

    • A stronger grasp of content
    • The ability to recognize error patterns
    • Insight into students’ conceptual gaps
    • Renewed confidence in their instructional decisions

    The power of understanding the “why”

    Our district uses conceptual math curricula, including Eureka Math², Reveal Math, and Math Nation. These “HQIM” programs emphasize reasoning, discourse, and models–exactly the kind of instruction our students need.

    But conceptual materials only work when teachers understand the purpose behind them.

    Before this professional learning, teachers sometimes felt unsure about lesson sequencing and the lesson intent, including cognitive complexity. Now, they understand why lessons appear in a specific order and how models support deeper understanding. It’s common to hear teachers say: “Oh, now I get why it’s written that way!” They are also much more likely to engage deeply with the mathematical models in the programs when they understand the math education research behind the learning progressions that curriculum developers use to design the content.

    That insight helps them stay committed to conceptual instruction even when students struggle, shifting the focus from “Did they get it?” to “How are they thinking about it?”

    Transforming district culture

    The changes go far beyond individual classrooms.

    We run multiple sessions of this professional learning each year, and they fill within days. Teachers return to their PLCs energized, bringing exit tickets, student work, and new questions to analyze together.

    We also invite instructional coaches and principals to attend. This builds a shared professional language and strengthens communication across the system. The consistency it creates is particularly powerful for new teachers who are still building confidence in their instructional decision-making.

    The result?

    • Teachers now invite feedback.
    • Coaches feel like instructional partners, not evaluators.
    • Everyone is rowing in the same direction.

    This shared understanding has become one of the most transformative parts of our district’s math journey.

    Results we can see

    In the past five years, Charleston County’s math scores have climbed roughly 10 percentage points. But the most meaningful growth is happening inside classrooms:

    • Students are reasoning more deeply.
    • Teachers demonstrate stronger content knowledge and efficacy in using math models.
    • PLC conversations focus on evidence of student thinking.
    • Instruction is more intentional and responsive.

    Teachers are also the first to tell you whether PD is worth their time…and our teachers are asking for more. Many return to complete a second or third strand, and sometimes all four. We even have educators take the same strand more than once just to pick up on something they may have missed the first time. The desire to deepen their expertise shows just how impactful this learning has been. Participants also find it powerful to engage in a room where the collective experience spans multiple grade levels. This structure supports our goal of strengthening vertical alignment across the district.

    Prioritizing professional learning that works

    When professional learning builds teacher expertise rather than compliance, everything changes. This approach doesn’t tell teachers what to teach; it helps them understand how students learn.

    And once teachers gain that insight, classrooms shift. Conversations deepen. Confidence grows. Students stop memorizing math and start truly understanding it.

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