Category: Teaching & Learning

  • Capability for change – preparing for digital learning futures

    Capability for change – preparing for digital learning futures

    Digital transformation is an ongoing journey for higher education institutions, but there is something quite distinctive about the current moment.

    The combination of financial uncertainty, changing patterns of student engagement, and the seismic arrival of artificial intelligence is pointing to a future for higher education learning and teaching and a digital student experience that will certainly have some core elements in common with current practice but is likely in many respects to look rather different.

    At the moment I see myself and my colleagues trying to cling to what we always did and what we always know. And I really do think the whole future of what we do and how we teach our students, and what we teach our students is going to accelerate and change very, very quickly now, in the next five years. Institutional leader

    Our conversations with sector leaders and experts over the past six months indicate an ambition to build consistent, inclusive and engaging digital learning environments and to deploy data much more strategically. Getting it right opens up all kinds of possibilities to extend the reach of higher education and to innovate in models for engagement. But future change demands different kinds of technological capabilities, and working practices, and institutions are saying that they are hindered by legacy systems, organisational silos, and a lack of a unified vision.

    Outdated systems do not “talk to each other,” and on a cultural level as departments and central teams also do not “talk to each other” – or may struggle to find a common language. And rather than making life easier, many feel that technology creates significant inefficiencies, forcing staff to spend more time on administrative tasks and less on what truly matters.

    I think the problem always is when we hope something’s going to make it more efficient. But then it just adds a layer of complexity into what we’re doing…I think that’s what we struggle with – what can genuinely deliver some time savings and efficiencies as opposed to putting another layer in a process? Institutional leader

    In the spirit of appreciative inquiry, our report Capability for change – preparing for digital learning futures draws on a series of in depth discussions with leaders of learning and teaching, and digital technology, digital experts and students’ union representatives. We explore the sorts of change that are already in train, and surface insight about how institutions are thinking in terms of building whole-organisation capabilities. “Digital dexterity” – the ability to deploy technology strategically, efficiently, and innovatively to achieve core objectives – may be yet another tech buzzword, but it captures a sense of where organisations are trying to get to.

    While immediate financial pressures may require cutting costs and reprofiling investment, long term sustainability depends on moving forward with change, finding ways, not to do more with less but to do things differently. To realise the most value from technology investment institutional leaders need to find ways to ensure that across the institution staff teams have the knowledge, the motivation and the tools to deploy technology in the service of student success.

    How institutions are building organisational capability

    Running through all our conversations was a tension, albeit a potentially productive one: there needs to be much more consistency and clarity about the primary strategic objectives of the institution and the core technology platforms and applications that enable them. But the effect of, in essence, imposing a more streamlined “central” vision, expectations and processes should be to enable and empower the academic and professional teams to do the things that make for a great student experience. Our research indicates that institutions are focusing on three areas: leadership and strategy; digital capabilities of institutional staff; and breaking down the vertical silos that can hamper effective cross-organisational working.

    A number of reflections point to strategy-level improvements – such as ensuring there is strategic alignment between institutional objectives for student success, and technology and digital strategies; listening to the feedback from students and staff about what they need from technology; setting priorities, and resourcing those priorities from end to end from technology procurement to deployment and evaluation of impact. One institutional leader described what happens when digital strategies get lost in principles and forget to align with the wider success of the organisation:

    The old strategy is fairly similar, I imagine, to many digital strategies that you would have seen – it talks about being user focused, talks about lean delivery, talks about agile methodologies, product and change management and delivering value through showing, not telling. So it was a very top level strategy, but really not built with outcomes at its absolute core, like, what are the things that are genuinely going to change for people, for students? Institutional leader

    Discussions of staff digital capabilities recognised that institutional staff are often hampered by organisational complexity and bureaucracy which too often is mirrored in the digital sphere. One e-learning professional suggested that there is a need for research to really understand why there is a tendency towards proliferation of processes and systems, and confront the impact on staff workloads.

    There may also be limits to what can reasonably be expected from teaching staff in terms of digital learning design:

    You need to establish minimum benchmarks and get everyone to that place, and then some people will be operating well beyond that. You can be clear about basic benchmark expectations around student experience – and then beyond that you need to put in actual support [such as learning design experts] to implement the curriculum framework. E-learning professional

    But the broader insight on staff development was around shifting from provision of training on how to operate systems or tools to a more context-specific exploration of how the available technologies and data can help educators achieve their student success ambitions. Value is more systematically created across the organisation when those academic and professional teams who work directly with students are able to use the technology and data available creatively to enhance their practice and to problem solve.

    Where data has been used before it’s very much sat with senior colleagues in the institution. And you know it’s helped in decision making. But the next step is to try and empower colleagues at the coal face to use data in their day to day interventions with their students… How can they use the data to inform how they support their students? Institutional leader

    Decisive leadership may be successful in setting priorities and streamlining the processes and technologies that underpin them; strong focus on professional development may engage and enable institutional staff. But culture change will come when institutions find ways to systematically build “horizontals” across silos – mechanisms for collaborative and shared activity that bridge different perspectives, languages and disciplinary and professional cultures.

    Some examples we saw included embedding digital professionals in faculties and academic business processes such as recruitment panels, convening of cross-organisation thinking on shared challenges, and appointment of “change agent” roles with a skillset and remit to roam across boundaries.

    Technology providers must be part of the solution – acting as strategic partners rather than suppliers. One way to do that is to support institutions to pilot, test, and develop proof of concept before they decide to invest in large-scale change. Another is to work with institutions to understand how technology is deployed in practice, and the evolving needs of user communities. To be a great partner to the higher education sector means having a deep understanding not only of the technological capabilities that could help the sector but how these might weave into an organisation’s wider mission and values. In this way, technology providers can help to build capability for change.

    This article is published in association with Kortext. You can download the Capability for change report on Kortext’s website. The authors would like to thank all those who shared their insight to inform the report. 

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  • Student experience is becoming more transactional – but that doesn’t make it less meaningful

    Student experience is becoming more transactional – but that doesn’t make it less meaningful

    It seems that few can agree about what the future student experience will look like but there is a growing consensus that for the majority of higher education institutions (bar a few outliers) it will – and probably should – look different from today.

    For your institution, that might look like a question of curriculum – addressing student demand for practical skills, career competencies and civic values to be more robustly embedded in academic courses. It might be about the structure of delivery – with the Lifelong Learning Entitlement funding per credit model due to roll out in the next few years and the associated opportunity to flex how students access programmes of study and accrue credit. It might be a question of modality and responding to demands for flexibility in accessing learning materials remotely using technology.

    When you combine all these changes and trends you potentially arrive at a more fragmented and transient model of higher education, with students passing through campus or logging in remotely to pick up their higher education work alongside their other commitments. Academic community – at least in the traditional sense of the campus being the locus of daily activity for students and academics – already appears at risk, and some worry that there is a version of the future in which it is much-reduced or disappears altogether.

    Flexibility, not fragmentation

    With most higher education institutions facing difficult financial circumstances without any immediate prospect of external relief, the likelihood is that cost-saving measures reduce both the institutional capacity to provide wraparound services and the opportunities for the kind of human-to-human contact that shows up organically when everyone is co-located. Sam Sanders

    One of the challenges for higher education in the decade ahead will be how to sustain motivation and engagement, build connection and belonging, and support students’ wellbeing, while responding to that shifting pattern of how students practically encounter learning.

    The current model still relies on high-quality person to person interaction in classrooms, labs, on placement, in accessing services, and in extra-curricular activities. When you have enough of that kind of rich human interaction it’s possible to some extent to tolerate a degree of (for want of a better word) shonky-ness in students’ functional and administrative interactions with their institution.

    That’s not a reflection of the skills and professionalism of the staff who manage those interactions; it’s testament to the messiness of decades of technology systems procurement that has not kept up with the changing demands of higher education operational management. The amount of institutional resource devoted to maintaining and updating these systems, setting up workarounds when they don’t serve desired institutional processes, and extracting and translating data from them is no longer justifiable in the current environment.

    Lots of institutional leaders accept that change is coming. Many are leading significant transformation and reform programmes that respond to one or more of the changes noted above. But they are often trying – at some expense – to build a change agenda on top of a fragile foundational infrastructure. And this is where a change in mindset and culture will be needed to allow institutions to build the kind of student experiences that we think are likely to become dominant within the next decade.

    Don’t fear the transactional

    Maintaining quality when resources are constrained requires a deep appreciation of the “moments that matter” in student experience – those that will have lasting impact on students’ sense of academic identity and connection, and by association their success – and those that can be, essentially, transactional. Pete Moss

    If, as seems to be the case, the sector is moving towards a world in which students need a greater bulk of their interaction with their institution to be in that “transactional” bucket two things follow:

    One is that the meaningful bits of learning, teaching, academic support and student development have to be REALLY meaningful, enriching encounters for both students and the staff who are educating them – because it’s these moments that will bring the education experience to life and have a transformative effect on students. To some degree how each institution creates that sense of meaningfulness and where it chooses to focus its pedagogical efforts may act as a differentiator to guide student choice.

    The second is that the transactional bits have to REALLY work – at a baseline be low-friction, designed with the user in mind, and make the best possible use of technologies to support a more grab-and-go, self-service, accessible-anywhere model that can be scaled for a diverse student body with complicated lives.

    Transactional should not mean ‘one-size-fits-all’ – in fact careful investment in technology should mean that it is possible to build a more inclusive experience through adapting to students’ needs, whether that’s about deploying translation software, integrating assistive technologies, or natural language search functionality. Lizzie Falkowska

    Optimally, institutions will be seeking to get to the point where it is possible to track a student right from their first interaction with the institution all the way through becoming an alumnus – and be able to accommodate a student being several things at once, or moving “backwards” along that critical path as well as “forwards.” Having the data foundations in place to understand where a student is now, as well as where they have come from, and even where they want to get to, makes it possible to build a genuinely personalised experience.

    In this “transactional” domain, there is much less opportunity for strategic differentiation with competitor institutions – though there is a lot of opportunity for hygiene failure, if students who find their institution difficult to deal with decide to take their credits and port them elsewhere. Institutional staff, too, need to be able to quickly and easily conduct transactional business with the institution, so that their time is devoted as much as possible to the knowledge and student engagement work that is simply more important.

    Critically, the more that institutions adopt common core frameworks and processes in that transactional bucket of activity, the more efficient the whole sector can be, and the more value can be realised in the “meaningful” bucket. That means resisting the urge to tinker and adapt, letting go of the myth of exceptionalism, and embracing an “adopt not adapt” mindset.

    Fixing the foundations

    To get there, institutions need to go back to basics in the engine-room of the student experience – the student record system. The student system of 15-20 years ago was a completely internally focused statutory engine, existing for award board grids and HESA returns. Student records is now seen as a student-centric platform that happens to support other outputs and outcomes, both student-facing interactions, and management information that can drive decision-making about where resource input is generating the best returns.

    The breadth of things in the student experience that need to be supported has expanded rapidly, and will continue to need to be adapted. Right now, institutions need their student record system to be able to cope with feeding data into other platforms to allow (within institutional data ethics frameworks) useful reporting on things like usage and engagement patterns. Increasingly ubiquitous AI functionality in information search, student support, and analytics needs to be underpinned by high quality data or it will not realise any value when rolled out.

    Going further, as institutions start to explore opportunities for strategic collaboration, co-design of qualifications and pathways in response to regional skills demands, or start to diversify their portfolio to capture the benefits of the LLE funding model, moving toward a common data framework and standards will be a key enabler for new opportunities to emerge.

    The extent to which the sector is able to adopt a common set of standards and interoperability expectations for student records is the extent to which it can move forward collectively with establishing a high quality baseline for managing the bit of student experience that might be “transactional” in their function, but that will matter greatly as creating the foundations for the bits that really do create lasting value.

    This article is published in association with KPMG.

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  • Breaking out of Borgentown – the case for hope in higher education

    Breaking out of Borgentown – the case for hope in higher education

    It started, as so many great conversations do, over coffee.

    On a chilly January day as we swapped tales of small children and shared cultural touchstones, we found ourselves riffing on the Trolls movie (which it turns out we have both seen a painful number of times). In particular, we found ourselves in Borgentown: a drab, grey world of monotony and drudgery, where fleeting joy depends on eating the vibrant, music-loving Trolls.

    There’s an uncomfortable resonance with the current temperature of higher education where we can see the joy and possibility at the heart of education being overshadowed by a grinding sense of the need for survival. The drip-feed of news of more institutions in financial trouble, the dissipation of expectation that the Westminster government would pursue bold action early in its term of office, the existential dread of global geopolitics.

    The sense that the sector desperately needs a fresh vision and plan for the future, combined with unease about whether that vision will ever materialise and where it will materialise from. It’s hardly surprising that even relentless chirpy people like us can sometimes feel a bit…Borgeny.

    Ode to joy

    Mark is an educator and Debbie a policy wonk, but we share the conviction that education should be a joyful act. It is the engineering of possibility, the building of capability, the empowerment of individuals to deliver positive impact in the world. It is an act of creation (and creation by proxy), and any such act is joyous. Done well, policymaking can also be creative and empowering, in the ways it seeks to adjust the conditions for good and desirable outcomes to flourish.

    But the mood in higher education often feels very different. It feels negative and ground down, paralysed, even fatalistic. Educators, long asked to do more with less, feel denied, their good ideas drowned out by demands for managerial efficiency. Meanwhile, leaders are navigating hostile, contradictory, resource-constrained times. The result is a collective energy that’s fraught and disempowered. This is dangerous, because fatalism is a trap.

    Paolo Freire wrote of the ways that fatalism denies people the ability to imagine change. It leaves us believing that what is, is all that ever can be. Education is the opposite of fatalism – it equips us with the power to critically appraise the way things are and to imagine alternatives. Freire said that the primary goal of educators should be to punctuate fatalism with critical hope. And so there is a double tragedy if even educators are deprived of their potential to imagine and enable better futures. Similarly, policymakers at all levels need to take seriously their responsibility to convene, lead, and enable change, lest fatalism set in and undermine the social fabric.

    When we talk to sector colleagues, we see a creeping fatalism that comes with dealing with a proliferation of things that are difficult, not in a stretching or challenging or inspiring way, but in a way that chips away at mental and emotional bandwidth. But we also see lots to get excited about – an underlying energy and continued appetite to engage in imaginative discussion, an empathy for the challenges individuals and teams are facing that is breaking down some of the traditional silos, and a curiosity and openness to finding new ways to solve old problems.

    The higher education sector is going through some tough times. It may not look exactly the same as it does now a decade hence, but it retains an extraordinary capacity to shape its own future. And this is where we think there is scope for some “interdisciplinary” thinking to happen.

    Coming to a website near you

    As Wonkhe’s newest contributing editor, in the months ahead Mark will intentionally explore ideas that seem unachievable on the surface, not to frustrate, but to provoke and to encourage us to see what those ideas tell us about what is possible. We will poke at old orthodoxies – and unsettle some new ones before they sediment fully.

    Are our narratives on how research environments benefit students really compelling (really?)? Is our defensiveness around grade inflation obscuring that classifications are just a really stupid way of signalling talent? And while we’re at that, can assessment be freed from the stranglehold of compliance? Is “belonging” already becoming a hollow buzzword? And what happens if we fully lean into AI rather than mitigating it? We’ll play with the notion of “co-creation” as only currently skimming at the surface of possibility – and explore pedagogy as a device to more authentically deliver civic aspirations.

    In that spirit, we will also have one eye on policy, and the changes that would be needed to policy to help bring new ideas and thinking into being. Imagining different possibilities has to include tackling questions of what concepts like “quality” and “access” mean in the changing higher education landscape, and what they can or ought to mean in the future, what accountabilities and enabling relationships educators, professionals, and institutions should have and how/the extent to which these can be mediated through policy.

    This is not an exercise in naive utopianism, nor is it an attempt to attack the sector. Rather it is an affirmation of the sector’s talent, creativity, and intellectual energy. We want to rally the dreamers, the thinkers, and the doers in education – those who are already innovating, those waiting for permission to dream, and those who believe another world is possible – to prise open the Overton window of what is politically acceptable, and push at the boundaries that various sector sacred cows make appear as if they are set in stone.

    If you share our optimism that there is still plenty of creative energy out there that has yet to be tapped, please bring us your own ideas and imagined futures to contribute to the conversation. As the Borgens learn at the end of Trolls, their potential for joy was inside them all along.

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  • HESA’s AI Observatory: What’s new in higher education (March 16, 2025)

    HESA’s AI Observatory: What’s new in higher education (March 16, 2025)

    International Frameworks

    With the right opportunities we can become AI makers, not takers
    Michael Webb.  FE Week. February 21, 2025.

    The article reflects on the UK’s AI Opportunities Action Plan, aiming to position the country as a leader in AI development rather than merely a consumer. It highlights the crucial role of education in addressing AI skills shortages and emphasizes the importance of focusing both on the immediate needs around AI literacy, but also with a clear eye on the future, as the balance moves to AI automation and to a stronger demand for uniquely human skills.

    Living guidelines on the responsible use of generative AI in research : ERA Forum Stakeholder’s document
    European Commission, Directorate-General for Research and Innovation. March 2024.

    These guidelines include recommendations for researchers, recommendations for research organisations, as well as recommendations for research funding organisations. The key recommendations are summarized here.

    Industry Collaborations

    OpenAI Announces ‘NextGenAI’ Higher-Ed Consortium
    Kim Kozlowski. Government Technology.  March 4, 2025.

    OpenAI has launched the ‘NextGenAI’ consortium, committing $50M to support AI research and technology across 15 institutions, including the University of Michigan, the California State University system, the Harvard University, the MIT and the University of Oxford. This initiative aims to accelerate AI advancements by providing research grants, computing resources, and collaborative opportunities to address complex societal challenges.

    AI Literacy

    A President’s Journey to AI Adoption
    Cruz Rivera, J. L. Inside Higher Ed. March 13, 2025.

    José Luis Cruz Rivera, President of Northern Arizona University, shares his AI exploration journey. « As a university president, I’ve learned that responsible leadership sometimes means […] testing things out myself before asking others to dive in ». From using it to draft emails, he then started using it to analyze student performance data and create tailored learning materials, and even used it to navigate conflicting viewpoints and write his speechs – in addition to now using it for daily tasks.

    Teaching and Learning

    AI Tools in Society : Impacts on Cognitive Offloading and the Future of Critical Thinking
    Gerlich, M. SSRN. January 14, 2025.

    This study investigates the relationship between AI tool usage and critical thinking skills, focusing on cognitive offloading as a mediating factor. The findings revealed a significant negative correlation between frequent AI tool usage and critical thinking abilities, mediated by increased cognitive offloading. Younger participants exhibited higher dependence on AI tools and lower critical thinking scores compared to older participants. Furthermore, higher educational attainment was associated with better critical thinking skills, regardless of AI usage. These results highlight the potential cognitive costs of AI tool reliance, emphasising the need for educational strategies that promote critical engagement with AI technologies.

    California went big on AI in universities. Canada should go smart instead
    Bates, S. University Affairs. March 12, 2025.

    In this opinion piece, Simon Bates, Vice-Provost and Associate Vice-President for Teaching and Learning at UBC, reflects on how the ‘fricitonless efficiency’ promised by AI tools comes at a cost. « Learning is not frictionless. It requires struggle, persistence, iteration and deep focus. The risk of a too-hasty full scale AI adoption in universities is that it offers students a way around that struggle, replacing the hard cognitive labour of learning with quick, polished outputs that do little to build real understanding. […] The biggest danger of AI in education is not that students will cheat. It’s that they will miss the opportunity to build the skills that higher education is meant to cultivate. The ability to persist through complexity, to work through uncertainty, to engage in deep analytical thought — these are the foundations of expertise. They cannot be skipped over. »

    We shouldn’t sleepwalk into a “tech knows best” approach to university teaching
    Mace, R. et al. Times Higher Education. March 14, 2025.

    The article discusses the increasing use of generative AI tools like among university students, with usage rising from 53% in 2023-24 to 88% in 2024-25. It states that instead of banning these tools, instructors should ofcus on rethinking assessment strategies to integrate AI as a collaborative tool in academic work. The authors share a list of activities, grounded in the constructivist approach to education, that they have successfully used in their lectures that leverage AI to support teaching and learning.

    Accessibility & Digital Divide

    AI Will Not Be ‘the Great Leveler’ for Student Outcomes
    Richardson, S. and Redford, P. Inside Higher Ed. March 12, 2025.

    The authors share three reasons why AI tools are only deepening existing divides : 1) student overreliance on AI tools; 2) post-pandemic social skills deficit; and 3) business pivots. « If we hope to continue leveling the playing field for students who face barriers to entry, we must tackle AI head-on by teaching students to use tools responsibly and critically, not in a general sense, but specifically to improve their career readiness. Equally, career plans could be forward-thinking and linked to the careers created by AI, using market data to focus on which industries will grow. By evaluating student need on our campuses and responding to the movements of the current job market, we can create tailored training that allows students to successfully transition from higher education into a graduate-level career. »

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  • How is artificial intelligence actually being used in higher education?

    How is artificial intelligence actually being used in higher education?

    With a wide range of applications, including streamlining administrative tasks and tailoring learning experiences, AI is being used in innovative ways to enhance higher education.

    Course design and content preparation

    AI tools are changing the way academic staff approach course design and content preparation. By leveraging AI, lecturers can quickly generate comprehensive plans, create engaging sessions, and develop quizzes and assignments.

    For instance, tools like Blackboard Ultra can create detailed course plans and provide suggestions for content organisation and course layout. They can produce course materials in a fraction of the time it would traditionally take and suggest interactive elements that could increase student engagement.

    AI tools excel at aligning resources with learning outcomes and institutional policies. This not only saves time but also allows lecturers to focus more on delivering high-quality instruction and engaging with students.

    Enhancing learning experience

    AI and virtual reality (VR) scenarios and gamified environments are offering students unique, engaging learning experiences that go beyond traditional lectures. Tools like Bodyswaps use VR to simulate realistic scenarios for practicing soft and technical skills safely. These immersive and gamified environments enhance learning by engaging students in risk-free real-world challenges and provide instant feedback, helping them learn and adjust more effectively.

    Self-tailored learning

    AI also plays a role in supporting students to tailor learning materials to meet their individual and diverse needs. Tools like Jamworks can enhance student interaction with lecture content by converting recordings into organised notes and interactive study materials, such as flashcards.

    Similarly, Notebook LLM offers flexibility in how students engage with their courses by enabling them to generate content in their preferred form such as briefing documents, podcasts, or taking a more conversational approach. These tools empower students to take control of their learning processes, making education more aligned with their individual learning habits and preferences.

    Feedback and assessment

    Feedback and assessment is the most frequently referenced area when discussing how reductions in workload could be achieved with AI. Marking tools like Graide, Keath.ai, and Learnwise are changing this process by accelerating the marking phase. These tools leverage AI to deliver consistent and tailored feedback, providing students with clear, constructive insights to enhance their academic work. However, the adoption of AI in marking raises valid ethical concerns about its acceptability such as the lack of human judgement and whether AI can mark consistently and fairly.

    Supporting accessibility

    AI can play a crucial role in enhancing accessibility within educational environments, ensuring that learning materials are inclusive and accessible to all students. By integrating AI-driven tools such as automated captioning, and text-to-speech applications, universities can significantly improve the accessibility of digital resources.

    AI’s capability to tailor learning materials is particularly beneficial for students with diverse educational needs. It can reformat text, translate languages, and simplify complex information to make it more digestible. This ensures that all students, regardless of their learning abilities or language proficiency, have equal opportunities to access and understand educational content.

    Despite the benefits, the use of AI tools like Grammarly raises concerns about academic integrity. These tools have the potential to enhance or even alter students’ original work, which may lead to questions about the authenticity of their submissions. This issue highlights the need for clear guidelines and ethical considerations in the use of AI to support academic work without compromising integrity.

    Another significant issue is equity of access to these tools. Many of the most effective AI-driven accessibility tools are premium services, which may not be affordable for all students, potentially widening the digital divide.

    Student support – chatbots

    AI chatbots are increasingly recognised as valuable tools in the tertiary education sector, streamlining student support and significantly reducing staff workload. These increasingly sophisticated systems are adept at managing a wide array of student queries, from routine administrative questions to more detailed academic support, thereby allowing human resources to focus on tasks requiring more nuanced and personal interactions. They can be customised to meet the specific needs of a university, ensuring that they provide accurate and relevant information to students.

    Chatbots such as LearnWise are designed to enhance student interactions by providing more tailored and contextually aware responses. For instance, on a university’s website, if a student expresses interest in gaming, they can suggest relevant courses, highlight the available facilities and include extra curriculum activities available, integrating seamlessly with the student’s interests and academic goals. This level of tailoring enhances the interaction quality and improves the student experience.

    Administrative efficiency

    AI is positively impacting the way administrative tasks are handled within educational institutions, changing the way everyday processes are managed. By automating routine and time-consuming tasks, AI technologies can alleviate the administrative load on staff, allowing them to dedicate more time to strategic and student-focused activities.

    AI tools such as Coplot and Gemini can help staff draft, organise, and prioritise emails. These tools can suggest responses based on the content received, check the tone of emails and manage scheduling by integrating with calendar apps, and remind lecturers of pending tasks or follow-ups, enhancing efficiency within the institution.

    Staff frequently deal with extensive documentation, from student reports to research papers and institutional policies. AI tools can assist in checking, proofreading and summarising papers and reports, and can help with data analysis, generating insights, graphs and graphics to help make data more easily digestible.

    How is AI being used in your institution?

    At Jisc we are collating practical case studies to create a comprehensive overview of how AI is being used across tertiary education. This includes a wide range of examples supporting the effective integration of AI into teaching and administration which will be used to highlight best practice, support those just getting started with the use of AI, overcome challenges being faced across the sector and to highlight the opportunities available to all.

    We want to hear how AI is being used at your organisation, from enhancing everyday tasks to complex and creative use cases. You can explore these resources and find out how to contribute by visiting the Jisc AI Resource Hub.

    For more information around the use of digital and AI in tertiary education, sign up to receive on-demand access to key sessions from Jisc’s flagship teaching and learning event – Digifest running 11–12 March.

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  • The case against impartial university teaching

    The case against impartial university teaching

    “I don’t share my political or religious perspectives at work; I never have”, asserted my experienced professorial colleague over an informal coffee. “A bit of shame, but kind of admirable, right?”, I thought.

    I recalled a politics lecturer during my time as an undergraduate, who, like seemingly most of that generation of academics (1990s-00s), believed in impartiality and explicitly stated his liberal neutrality when presenting challenging topics: may the best arguments win. The problem was that through reading his online bio and finding his works in the library, one could very quickly discern his political and philosophical leanings!

    When I began teaching philosophy at the same university a few years later, I too attempted to feign neutrality; neither sharing my political nor religious leanings, nor ethnic or cultural heritage. It wasn’t the done thing. Autobiography and self-disclosure had no place in the philosophy seminar room.

    I’ve since thawed. I’m now leaning far more towards disclosure than when I started teaching. I long held neutral impartiality as the gold standard of instruction, whereby challenging – and perhaps controversial – topics were discussed, but the educator held the space for students to explore perspectives, without sharing their own. This, while often the received wisdom, and certainly well-intentioned, is, I now reflect, limited.

    For an academic to be teaching on a module, especially if they’ve created it, means they’re very likely to be published in that field of inquiry. Engaged students will find such materials, understand their lecturer’s perspectives, and recognise when they’re playing devil’s advocate in sessions. Furthermore, given that we teach face to face, and not in confession booths, the visibility of us as lecturers often speaks volumes; students will make an array of assumptions. For example, if in a session led by the university’s chaplain, it’s safe for students to assume that they’re a member of the Church of England.

    Kelly’s heuristic quartet

    There is a case to be argued for “committed impartiality” as per Social Scientist Thomas Kelly’s (1986) heuristic quartet:

    • Exclusive neutrality: The educator takes a neutral position and eschews any potentially controversial issues; i.e. appropriate in a school context, but too reductive for HE.
    • Exclusive partiality: The educator takes a biased position; i.e. traditionally a big no no. Think here of educators who use their classes to enact their activism.
    • Neutral impartiality: The educator is impartial and neutral, encouraging students to explore controversial issues; i.e. the gold standard of HE instruction based on received wisdom.
    • Committed impartiality: The educator takes a biased position while also being impartial; i.e. seen with scepticism by those who practise neutral impartiality. This is a potentially slippery slope into exclusive partiality.

    While referring principally to the teaching of “controversial” topics in school education, I think the quartet can be helpfully adapted to fit the context of contemporary HE teaching in the social sciences and humanities. Kelly claimed that owing to its contradictory position, “committed impartiality” is the most defensible course of action for educators to engage in teaching controversial issues. This is because it requires the educator to put their cards on the table and encourage debate without claiming an unbiased standpoint.

    Wading

    When discussing loaded issues such as race, sexuality and religious perspectives, perhaps this is where the received wisdom about steadfastly refusing to disclose shines through and avoids the – especially contemporary – quagmire of a shallow form of identity politics and virtue signalling that can sometimes turn into a form of oppression Olympics? The “disclosure dilemma” is, of course, ultimately a personal, context bound one.

    In the context of schools, the issue of disclosure is much more vexed, given that teachers are effectively agents of the state who have a moral duty to avoid prosletysing given the power dynamic of the classroom (I recall the example during COvid-19 of a teacher in Nottinghamshire getting national attention for encouraging students to write letters of frustration to the then PM).

    While school curricula are obviously created by groups of individuals with political agendas, in HE we too have areas of expertise, interest, and passion. In an increasingly regulatory framework, the dissemination of our darlings is bound by legislation such as the Equality Act (2010), and The Higher Education Freedom of Speech Act (2023). Furthermore, to adhere to these acts within a localised context, my employer has a university dignity policy, mission statements, and, within my department, enacts the Chatham House Rule. We also provide trigger warnings to create inclusive learning environments.

    Tightrope

    This discussion has implications for those in the social sciences, especially those who deal, like I do, with explicitly political content (I recognise that the personal is also the political). Of course, navigating the tightrope between committed impartiality and exclusive partiality is tricky. The received wisdom is valuable insofar as it helps the educator to avoid this balancing act. But when the educator has a specialism that speaks to a political issue of the day, it is arguably upon them to do so. For example, in March 2023 I was teaching a session for final year UG students on migration in the context of international education when the Gary Lineker “issue” kicked off. I had a well-informed perspective on that issue, and it linked neatly to the scheduled taught content that day. It’s fair to say that I teetered on that tightrope between committed impartiality and exclusive partiality!

    The challenge is not about self-censorship in the service of an apparently noble ideal of neutral impartiality, but enacting personal commitment and setting the groundwork for civic debate. Deciding to disclose may have the intended learning outcome of rapport building, modelling particular behaviours or perspectives, humanising oneself, normalising situations, or problematising a set of affairs; it’s about practising the messy craft of educating, and being open to self-transformation.

    Risk aversion

    I’m sure others could make equally compelling cases for different positions within, and outside of, Kelly’s heuristic quartet. I think a primary driver behind neutrality is, rather than a noble but impossible quest for untainted discourse, perhaps one of nervousness; nervousness of being seen as doctrinaire or unduly influencing students’ perspectives?

    Overall, the disclosing instructor must consider their visibility in terms of gender, age, physical presence, professional titles etc. that starkly reinforce a power imbalance between student and academic, aka judge, jury and executioner in terms of grades and longer-term prospects. Where the stakes are high boldness of speech, disclosing personal leanings in a learning environment are worth the risk.

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  • The importance of consequential feedback

    The importance of consequential feedback

    Imagine this: a business student managing a virtual company makes a poor decision, leading to a simulated bankruptcy. Across campus, a medical student adjusts a treatment in a patient simulation and observes improvements in the virtual patient’s condition.

    When students practice in a simulated real-world environment they have access to a rich set of feedback information, including consequential feedback. Consequential feedback provides vital information about the consequences of students’ actions and decisions. Typically, though, in the perennial NSS-driven hand-wringing about improving feedback in higher education, we are thinking only about evaluative feedback information – when educators or peers critique students’ work and suggest improvements.

    There’s no doubt evaluative feedback, especially corrective feedback, is important. But if we’re only talking about evaluative feedback, we are missing whole swathes of invaluable feedback information crucial to preparing graduates for professional roles.

    In a recently published, open access paper in Assessment and Evaluation in Higher Education, we make the case for educators to design for and support students in noticing, interpreting and learning from consequential feedback information.

    What’s consequential feedback?

    Consequential feedback involves noticing the connection between actions and their outcomes (consequences). For example, if we touch a hot stove, we get burned. In this example, noticing the burn is both immediate and obvious. Connecting it to the action of touching the stove is also easy – little interpretation needs to be made. However, there are many cause-effect (action-consequence) sequences embedded in professional practice that are not so easy to connect. Students may need help in noticing the linkages, interpreting them and making corrections to their actions to lead to better consequences in the future.

    For instance, the business student above might decide on a pricing strategy and observe its effect on market share. The simulation speeds up time so students can observe the effects of price change on sales and market share. In real life, observing the consequences of a pricing change might take weeks or months. Through the simulation, learners can experiment with different pricing strategies, making different assumptions about the market, and observing the effects, to build their understanding of how these two variables are linked under different conditions. Critically, they learn the importance of this linkage so they can monitor in the messier, delayed real life situations they might face as a marketing professional.

    Consequential feedback isn’t just theoretical. It is already making an impact in diverse educational fields such as healthcare, business, mathematics and the arts. But the disparate literature we reviewed almost never names this information as consequential feedback. To improve feedback in higher education, we need to be able to talk to educators and students explicitly about this rich font of feedback information. We need a language for it so we can explore how it is distinct from and complementary to evaluative feedback. Naming it allows us to deliberately practice different ways of enhancing it and build evidence about how to teach students to use it well.

    Why does it matter?

    Attending to consequential feedback shifts the focus from external judgments of quality to an internalised understanding of cause and effect. It enables students to experience the results of their decisions and use these insights to refine their practice. Thus, it forms the grist for reflective thinking and a host of twenty-first century skills needed to solve the world’s most pressing problems.

    In “real-life” after university, graduates are unlikely to have a mentor or teacher standing over them offering the kind of evaluative feedback that dominates discussion of feedback in higher education. Instead, they need to be able to learn independently from the consequential feedback readily available in the workplace and beyond. Drawing on consequential feedback information, professionals can continuously learn and adapt their practice to changing contexts. Thus, educators need to design opportunities that simulate professional practices, paying explicit attention to helping students learn from the consequential feedback afforded by these instructional designs.

    How can educators harness it?

    While consequential feedback is powerful, capitalising on it during higher education requires careful design. Here are some strategies for educators to try in their practice:

    Use simulations, role-plays, and projects: Simulations provide a controlled environment where students can explore the outcomes of their actions. For example, in a healthcare setting, students might use patient mannequins or virtual reality tools to practice diagnostic and treatment skills. In a human resources course, students might engage in mediation role plays. In an engineering course, students could design and test products like model bridges or rockets.

    Design for realism: Whenever possible, feedback opportunities should replicate real-world conditions. For instance, a law student participating in a moot court can see how their arguments hold up under cross-examination or a comedy student can see how a real audience responds to their show.

    Encourage reflection: Consequential feedback is most effective when paired with reflection. Educators can prompt students to consider questions such as: What did you do? Why? What happened when you did x? Was y what you expected or wanted? How do these results compare to professional standards? Why did you get that result? What could you change to get the results you want?

    Pair with evaluative feedback: Students may see that they didn’t get the result they wanted but not know how to correct their actions. Consequential feedback doesn’t replace evaluative feedback; it complements it. For example, after a business simulation, an instructor might provide additional guidance on interpreting KPIs or suggest strategies for improvement. This pairing helps students connect outcomes with actionable next steps.

    Shifting the frame

    Focusing on consequential feedback represents a shift in how we think about assessment, feedback, and learning itself. By designing learning experiences that allow students to act and observe the natural outcomes of their actions, we create opportunities for deeper, more meaningful engagement in the learning process. As students study the impact of their actions, they learn to take responsibility for their choices. This approach fosters the problem-solving, adaptability, independence, and professional and social responsibility they’ll need throughout their lives.

    A key question educators should be asking is: how can I help students recognise and learn from the outcomes of their actions? The answer lies in designing for and highlighting consequential feedback.

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  • The potential of educational podcasts for commuter students

    The potential of educational podcasts for commuter students

    Engaging students in learning outside the classroom can often be a challenge, but podcasts might be a simple yet versatile tool we’re overlooking.

    As the number of commuting students rises across institutions, we recognise that students are time poor. There is, however, the potential of using travel time as an opportunity for students to work but also relax and many students use their commute time as an opportunity to prepare for teaching. Podcasting is one of the ways we can design our pedagogy to fit the busy lives of commuter students.

    Think about how you listen to podcasts, most likely while you’re doing other things like driving, cooking or walking. There’s a versatility to it.

    How many of the learning resources we offer allow students to learn on-the-go?

    Education on-the-go

    Most podcast listeners will tell you the convenience of audio-centric and on-the-go content is key to their success. BBC data suggests that about three in four podcast listeners do so while doing something else, so even podcasts that have a video option available need to be planned and created with an audio-only format in mind.

    Offering that versatility also comes at a cost. It’s important to recognise the fact that students might be on a busy bus, or looking for the timetable for their next train connection. We probably won’t have a student’s full attention, and that means that we need to carefully consider the kind of educational content that’s going to work in this format.

    Successful podcasts tend to be focused on experiential storytelling. They are usually fluid and conversational, so don’t be afraid to lean into that. Storytelling gives us emotional responses, helping students connect abstract ideas to real-world implications. A podcast will be much more successful if you give depth and meaning to something a student has already learned, rather than delivering the learning itself.

    Let’s take data analysis as an example. Instead of focusing on the technical process of analysing data, you could discuss stories of the impact of data bias or ethical dilemmas in data usage. Give your students food for thought rather than core learning, use it to turn the numbers into narrative and give a deeper meaning to your classroom content.

    It can also be a good idea to supplement your podcast with a short interactive activity, either online or at the start of your next learning session. Ask students to reflect on the podcast and their key takeaways from it. It can be a great starting point to encourage deeper learning.

    A how to guide

    Another core aspect of successful podcasts is authenticity. You don’t want your podcast to sound like a job interview. Natural conversations foster a sense of authenticity, which is key to keeping listeners engaged. A key part of this comes from the way you prepare for a podcast. Discussion points as opposed to questions allows both you and your guest to think more holistically about the topic and can make a huge difference when it comes to making the conversation flow authentically.

    We’ve found it’s best to give more flexibility and aim for shorter episodes. Splitting a conversation up into bitesize chunks gives students the option to listen to all episodes in one go, or a bit at a time. Starting with a few episodes, around 12-20 minutes each, will offer your students a lot more flexibility than a single 1-hour long podcast.

    Thankfully the technical and logistical aspects of recording podcasts have developed rapidly over the last few years and it’s very easy to get started. Advancements like text-to-speech editing and speech enhancement let you record fully online and get incredible results without any technical knowledge or high-end equipment. A lot of podcasting software now produces automatic text transcription supporting accessibility and allowing students to engage with the content in multiple formats.

    And by framing these resources as useful for students to “listen to on-the-go,” gives students permission to use and access resources in ways which work for them during their busy lives. It recognises commuter students and acknowledges busy student lives and gives them a new innovative way to engage with their studies.

    Getting started

    If you’re interested in giving it a go, here are some ideas to get you started.

    A conversation about a specific assessment: contact a student who did well on an assessment last year and ask if they would be happy to share their experiences. Students can get ideas and inspiration from how they have approached it, what worked well and what they would do differently.

    Interviews with industry experts is another way to frame a podcast. Working professionals don’t always have the time to travel to campus and prepare a lecture for your students. That might be different if they just had to join an online call for a natural conversation. Recording it as a podcast also gives you a reusable resource for future cohorts.

    Student Q&As where students can submit their own questions about a topic or assessment and discuss them in a podcast. This could be an idea to explore on your own, with another lecturer, or with professionals in the industry.

    It’s clear that using podcasts as a form of education comes with a lot of challenges, but it also offers a vast world of opportunities and flexibility for students. Where students face further challenges to engage and attend classes, it is worth considering how educational podcasts may be a mechanism so that resources work around busy and complex student lives. For commuting students, a great deal of time is spent on public transport and in maximising their time, providing resources that are engaging, useful and timely is a step in the right direction. And in designing resources specifically with commuter students in mind it recognises their experiences and allows them to engage authentically.

    And to make podcasts work for commuter students in an educational context we need to be realistic about the challenges students face and create content that works in a podcast format rather than shoehorning existing content into a new format. If we nail that, then podcasts could become a very useful tool for delivering educational content that fits around students and heightens engagement.

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  • The higher education sector needs to come together to renew its commitment to enhancing student engagement

    The higher education sector needs to come together to renew its commitment to enhancing student engagement

    “Engagement, to me, is probably…getting the most out of university…taking and making the most of available opportunities.”

    This quote, from Queen’s University Belfast students’ union president Kieron Minto sums up a lot of the essential elements of what we talk about when we talk about student engagement.

    It captures the sense that the higher education experience has multiple dimensions, incorporating personal and professional development as well as academic study. Students will be – and feel – successful to the extent that they invest time and energy in those activities that are the most purposeful. Critically, it captures the element of student agency in their own engagement – higher education institutions might make opportunities available but students need to decide to engage to get the most from them.

    In recent years “student engagement” has suffered from the curse of ubiquity. Its meanings and applications are endlessly debated. Is it about satisfaction, academic success, personal growth, or a combination of factors? There is a wealth of examples of discrete projects and frameworks for thinking about student engagement, but often little read-across from one context to another. We can celebrate the enormous amount of learning and insight that has been created while at the same time accepting that as the environment for higher education changes some of the practices that have evolved may no longer be fit for purpose.

    Higher education institutions and the students that are enrolled in them face a brace of challenges, from the learning and development losses of the Covid pandemic, to rising costs and income constraints, to technological change. Institutions are less able to support provision of the breadth of enriching opportunities to students at the same time as students have less money, time, and emotional bandwidth to devote to making the most of university.

    The answer, as ever, is not to bemoan the circumstances, or worse, blame students for being less able to engage, but to tool up, get strategic, and adapt.

    Students still want to make the most of the opportunities that higher education has to offer. The question is how to design and configure those opportunities so that current and future students continue to experience them as purposeful and meaningful.

    Fresh student engagement thinking

    Our report, Future-proofing student engagement in higher education, brings together the perspectives of academic and professional services staff, higher education leaders, and students, all from a range of institutions, to establish a firm foundation of principles and practices that can support coherent, intentional student engagement strategies.

    A foundational principle for student engagement is that students’ motivations and engagement behaviours are shaped by their backgrounds, prior experiences, current environments, and hopes and expectations for their futures – as explained by Ella Kahu in her socio-cultural framework for student engagement (2013).

    It follows that it is impossible to think about or have any kind of meaningful organisational strategy about student engagement without working closely in partnership with students, drawing on a wide range of data and insight about the breadth of students’ opinions, behaviours, and experiences. Similarly, it follows that a data-informed approach to student engagement must mean that the strategy evolves as students do – taking student engagement seriously means adopting an institutional mindset of preparedness to adapt in light of feedback.

    Where our research indicates that there needs to be a strategic shift is in the embrace of what might be termed a more holistic approach to student engagement, in two important senses.

    The first is understanding at a conceptual level how student engagement is realised in practice throughout every aspect of the student journey, and not just manifested in traditional metrics around attendance and academic performance.

    The second is in how institutions, in partnership with students, map out a shared strategic intent for student engagement for every stage of that journey. That includes designing inclusive and purposeful interventions and opportunities to engage, and using data and insight from students to deepen understanding of what factors enable engagement and what makes an experience feel purposeful and engaging – and ideally creating a flow of data and insight that can inform continuous enhancement of engagement.

    Theory into practice

    Our research also points to how some of that shift might be realised in practice. For example, student wellbeing is intimately linked to engagement, because tired, anxious, excluded or overwhelmed students are much less able to engage. When we spoke to university staff about wellbeing support they were generally likely to focus on student services provision. But students highlighted a need for a more proactive culture of wellbeing throughout the institution, including embedding wellbeing considerations into the curriculum and nurturing a supportive campus culture. Similarly, on the themes of community and belonging, while university staff were likely to point to institutional strategic initiatives to cultivate belonging, students talked more about their need for genuine individual connections, especially with peers.

    There was also a strong theme emerging about how institutions think about actively empowering students to have the confidence and skills to “navigate the maze” of higher education opportunities and future career possibilities. Pedagogies of active learning, for example, build confidence and a sense of ownership over learning, contributing to behavioural and psychological engagement. Developing students’ digital literacy means that students can more readily deploy technology to support connection with academics and course peers, make active critical choices about how they invest time in different platforms, and prepare for their future workplace. Before getting exercised about how today’s students do not arrive in higher education “prepared to engage,” it’s worth remembering just how much larger and more complicated the contemporary university is, and with these, the increased demands on students.

    While there is a lot that institutions can do to move forward their student engagement agenda independently, there is also a need for a renewed focus on student engagement from the higher education sector as a whole. The megathemes contributing to shifting student engagement patterns are shared; they are not distinctive to any institution type, geography, or student demographic.

    The promise of higher education – that you can transform your life, your identity and your future through a higher education experience – only holds true if students are willing and able to engage with it. This demands a unified effort from all involved.

    Institutions must prioritise student engagement, placing it at the heart of their strategies and decisions. Furthermore, the higher education sector as a whole must renew its focus on student engagement, recognising its fundamental role in achieving the goals of higher education. Finally, as regulatory bodies evolve their approach to the assessment and enhancement of academic quality, student engagement must once again be put front and centre of the higher education endeavour.

    This article is published in association with evasys. You can download a copy of Future-proofing student engagement here.

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  • HESA’s AI Observatory: What’s new in higher education (January 31, 2025)

    HESA’s AI Observatory: What’s new in higher education (January 31, 2025)

    Transformation of education

    Leading Through Disruption: Higher Education Leaders Assess AI’s Impacts on Teaching and Learning

    Rainie, L. and Watson, E. AAC&U and Elon University.

    Report from a survey of 337 college and university leaders that provides a status report on the fast-moving changes taking place on US campuses. Key data takeaways include the fact faculty use of AI tools trails significantly behind student use, more than a third of leaders surveyed perceive their institution to be below average or behind others in using GenAI tools, 59% say that cheating has increased on their campus since GenAI tools have become widely available, and 45% think the impact of GenAI on their institutions in the next five years will be more positive than negative.

    Four objectives to guide artificial intelligence’s impact on higher education

    Aldridge, S. Times Higher Education. January 27th, 2025

    The four objectives are: 1) ensure that curricula prepare students to use AI in their careers and to add human skills value to help them success in parallel of expanded use of AI; 2) employ AI-based capacities to enhance the effectiveness and value of the education delivered; 3) leverage AI to address specific pedagogical and administrative challenges; and 4) address pitfalls and shortcomings of using AI in higher ed, and develop mechanisms to anticipate and respond to emerging challenges.

    Global perspectives

    DeepSeek harnesses links with Chinese universities in talent war

    Packer, H. Times Higher Education. January 31st, 2025

    The success of artificial intelligence platform DeepSeek, which was developed by a relatively young team including graduates and current students from leading Chinese universities, could encourage more students to pursue opportunities at home amid a global race for talent, experts have predicted.

    Teaching and learning

    Trends in AI for student assessment – A roller coaster ride

    MacGregor, K. University World News. January 25th, 2025

    Insights from (and recording of) the University World News webinar “Trends in AI for student assessment”, held on January 21st. 6% of audience members said that they did not face significant challenges in using GenAI for assessment, 53% identified “verifying the accuracy and validity of AI-generated results” as a challenge, 49% said they lacked training or expertise in using GenAI tools, 45% identified “difficulty integrating AI tools within current assessment systems”, 41% were challenged in addressing ethical concerns, 30% found “ensuring fairness and reducing bias in AI-based assessments” challenging, 25% identified “protecting student data privacy and security” as a challenge, and 19% said “resistance to adopting AI-driven assessment” was challenging.

    Open access

    Charting a course for open education resources in an AI era

    Wang, T. and Mishra, S. University World News. January 24th, 2025

    The digital transformation of higher education has positioned open educational resources (OER) as essential digital public goods for the global knowledge commons. As emerging technologies, particularly artificial intelligence (AI), reshape how educational content is created, adapted and distributed, the OER movement faces both unprecedented opportunities and significant challenges in fulfilling its mission of democratising knowledge access.

    The Dubai Declaration on OER, released after the 3rd UNESCO World OER Congress held in November 2024, addresses pressing questions about AI’s role in open education.

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