Category: Teaching & Learning

  • How can students’ module feedback help prepare for success in NSS?

    How can students’ module feedback help prepare for success in NSS?

    Since the dawn of student feedback there’s been a debate about the link between module feedback and the National Student Survey (NSS).

    Some institutions have historically doubled down on the idea that there is a read-across from the module learning experience to the student experience as captured by NSS and treated one as a kind of “dress rehearsal” for the other by asking the NSS questions in module feedback surveys.

    This approach arguably has some merits in that it sears the NSS questions into students’ minds to the point that when they show up in the actual NSS it doesn’t make their brains explode. It also has the benefit of simplicity – there’s no institutional debate about what module feedback should include or who should have control of it. If there isn’t a deep bench of skills in survey design in an institution there could be a case for adopting NSS questions on the grounds they have been carefully developed and exhaustively tested with students. Some NSS questions have sufficient relevance in the module context to do the job, even if there isn’t much nuance there – a generic question about teaching quality or assessment might resonate at both levels, but it can’t tell you much about specific pedagogic innovations or challenges in a particular module.

    However, there are good reasons not to take this “dress rehearsal” approach. NSS endeavours to capture the breadth of the student experience at a very high level, not the specific module experience. It’s debatable whether module feedback should even be trying to measure “experience” – there are other possible approaches, such as focusing on learning gains, or skills development, especially if the goal is to generate actionable feedback data about specific module elements. For both students and academics seeing the same set of questions repeated ad nauseam is really rather boring, and is as likely to create disengagement and alienation from the “experience” construct NSS proposes than a comforting sense of familiarity and predictability.

    But separating out the two feedback mechanisms entirely doesn’t make total sense either. Though the totemic status of NSS has been tempered in recent years it remains strategically important as an annual temperature check, as a nationally comparable dataset, as an indicator of quality for the Teaching Excellence Framework and, unfortunately, as a driver of league table position. Securing consistently good NSS scores, alongside student continuation and employability, will feature in most institutions’ key performance indicators and, while vice chancellors and boards will frequently exercise their critical judgement about what the data is actually telling them, when it comes to the crunch no head of institution or board wants to see their institution slip.

    Module feedback, therefore, offers an important “lead indicator” that can help institutions maximise the likelihood that students have the kind of experience that will prompt them to give positive NSS feedback – indeed, the ability to continually respond and adapt in light of feedback can often be a condition of simply sustaining existing performance. But if simply replicating the NSS questions at module level is not the answer, how can these links best be drawn? Wonkhe and evasys recently convened an exploratory Chatham House discussion with senior managers and leaders from across the sector to gather a range of perspectives on this complex issue. While success in NSS remains part of the picture for assigning value and meaning to module feedback in particular institutional contexts there is a lot else going on as well.

    A question of purpose

    Module feedback can serve multiple purposes, and it’s an open question whether some of those purposes are considered to be legitimate for different institutions. To give some examples, module feedback can:

    • Offer institutional leaders an institution-wide “snapshot” of comparable data that can indicate where there is a need for external intervention to tackle emerging problems in a course, module or department.
    • Test and evaluate the impact of education enhancement initiatives at module, subject or even institution level, or capture progress with implementing systems, policies or strategies
    • Give professional service teams feedback on patterns of student engagement with and opinions on specific provision such as estates, IT, careers or library services
    • Give insight to module leaders about specific pedagogic and curriculum choices and how these were received by students to inform future module design
    • Give students the opportunity to reflect on their own learning journey and engagement
    • Generate evidence of teaching quality that academic staff can use to support promotion or inform fellowship applications
    • Depending on the timing, capture student sentiment and engagement and indicate where students may need additional support or whether something needs to be changed mid-module

    Needless to say, all of these purposes can be legitimate and worthwhile but not all of them can comfortably coexist. Leaders may prioritise comparability of data ie asking the same question across all modules to generate comparable data and generate priorities. Similarly, those operating across an institution may be keen to map patterns and capture differences across subjects – one example offered at the round table was whether students had met with their personal tutor. Such questions may be experienced at department or module level as intrusive and irrelevant to more immediately purposeful questions around students’ learning experience on the module. Module leaders may want to design their own student evaluation questions tailored to inform their pedagogic practice and future iterations of the module.

    There are also a lot of pragmatic and cultural considerations to navigate. Everyone is mindful that students get asked to feed back on their experiences A LOT – sometimes even before they have had much of a chance to actually have an experience. As students’ lives become more complicated, institutions are increasingly wary of the potential for cognitive overload that comes with being constantly asked for feedback. Additionally, institutions need to make their processes of gathering and acting on feedback visible to students so that students can see there is an impact to sharing their views – and will confirm this when asked in the NSS. Some institutions are even building questions that test whether students can see the feedback loop being closed into their student surveys.

    Similarly, there is also a strong appreciation of the need to adopt survey approaches that support and enable staff to take action and adapt their practice in response to feedback, affecting the design of the questions, the timing of the survey, how quickly staff can see the results and the degree to which data is presented in a way that is accessible and digestible. For some, trusting staff to evaluate their modules in the way they see fit is a key tenet of recognising their professionalism and competence – but there is a trade-off in terms of visibility of data institution-wide or even at department or subject level.

    Frameworks and ecosystems

    There are some examples in the sector of mature approaches to linking module evaluation data to NSS – it is possible to take a data-led approach that tests the correlation between particular module evaluation question responses and corresponding NSS question outcomes within particular thematic areas or categories, and builds a data model that proposes informed hypotheses about areas of priority for development or approaches that are most likely to drive NSS improvement. This approach does require strong data analysis capability, which not every institution has access to, but it certainly warrants further exploration where the skills are there. The use of a survey platform like evasys allows for the creation of large module evaluation datasets that could be mapped on to NSS results through business intelligence tools to look for trends and correlations that could indicate areas for further investigation.

    Others take the view that maximising NSS performance is something of a red herring as a goal in and of itself – if the wider student feedback system is working well, then the result should be solid NSS performance, assuming that NSS is basically measuring the right things at a high level. Some go even further and express concern that over-focus on NSS as an indicator of quality can be to the detriment of designing more authentic student voice ecosystems.

    But while thinking in terms of the whole system is clearly going to be more effective than a fragmented approach, given the various considerations and trade-offs discussed it is genuinely challenging for institutions to design such effective ecosystems. There is no “right way” to do it but there is an appetite to move module feedback beyond the simple assessment of what students like or don’t like, or the checking of straightforward hygiene factors, to become a meaningful tool for quality enhancement and pedagogic innovation. There is a sense that rather than drawing direct links between module feedback and NSS outcomes, institutions would value a framework-style approach that is able to accommodate the multiple actors and forms of value that are realised through student voice and feedback systems.

    In the coming academic year Wonkhe and evasys are planning to work with institutional partners on co-developing a framework or toolkit to integrate module feedback systems into wider student success and academic quality strategies – contact us to express interest in being involved.

    This article is published in association with evasys.

    Source link

  • Machine learning technology is transforming how institutions make sense of student feedback

    Machine learning technology is transforming how institutions make sense of student feedback

    Institutions spend a lot of time surveying students for their feedback on their learning experience, but once you have crunched the numbers the hard bit is working out the “why.”

    The qualitative information institutions collect is a goldmine of insight about the sentiments and specific experiences that are driving the headline feedback numbers. When students are especially positive, it helps to know why, to spread that good practice and apply it in different learning contexts. When students score some aspect of their experience negatively, it’s critical to know the exact nature of the perceived gap, omission or injustice so that it can be fixed.

    Any conscientious module leader will run their eye down the student comments in a module feedback survey – but once you start looking across modules to programme or cohort level, or to large-scale surveys like NSS, PRES or PTES, the scale of the qualitative data becomes overwhelming for the naked eye. Even the most conscientious reader will find that bias sets in, as comments that are interesting or unexpected tend to be foregrounded as having greater explanatory power over those that seem run of the mill.

    Traditional coding methods for qualitative data require someone – or ideally more than one person – to manually break down comments into clauses or statements that can be coded for theme and sentiment. It’s robust, but incredibly laborious. For student survey work, where the goal might be to respond to feedback and make improvements at pace, institutions are open that this kind of robust analysis is rarely, if ever, the standard practice. Especially as resources become more constrained, devoting hours to this kind of detailed methodological work is rarely a priority.

    Let me blow your mind

    That is where machine learning technology can genuinely change the game. Student Voice AI was founded by Stuart Grey, an academic at the University of Strathclyde (now working at the University of Glasgow), initially to help analyse student comments for large engineering courses. Working with Advance HE he was able to train the machine learning model on national PTES and PRES datasets. Now, further training the algorithm on NSS data, Student Voice AI offers literally same-day analysis of student comments for NSS results for subscribing institutions.

    Put the words “AI” and “student feedback” in the same sentence and some people’s hackles will immediately rise. So Stuart spends quite a lot of time explaining how the analysis works. The word he uses to describe the version of machine learning Student Voice AI deploys is “supervised learning” – humans manually label categories in datasets and “teach” the machine about sentiment and topic. The larger the available dataset the more examples the machine is exposed to and the more sophisticated it becomes. Through this process Student Voice AI has landed on a discreet number of comment themes and categories for taught students and the same for postgraduate research students that the majority of student comments consistently fall into – trained on and distinctive to UK higher education student data. Stuart adds that the categories can and do evolve:

    “The categories are based on what students are saying, not what we think they might be talking about – or what we’d like them to be talking about. There could be more categories if we wanted them, but it’s about what’s digestible for a normal person.”

    In practice that means that institutions can see a quantitative representation of their student comments, sorted by category and sentiment. You can look at student views of feedback, for example, and see the balance of positive, neutral and negative sentiment, overall, segment it into departments or subject areas, or years of study, then click through to see the relevant comments to see what’s driving that feedback. That’s significantly different from, say, dumping your student comments into a third party generative AI platform (sharing confidential data with a third party while you’re at it) and asking it to summarise. There’s value in the time and effort saved, but also in the removal of individual personal bias, and the potential for aggregation and segmentation for different stakeholders in the system. And it also becomes possible to compare student qualitative feedback across institutions.

    Now, Student Voice AI is partnering with student insight platform evasys to bring machine learning technology to qualitative data collected via the evasys platform. And evasys and Student Voice AI have been commissioned by Advance HE to code and analyse open comments from the 2025 PRES and PTES surveys – creating opportunities to drill down into a national dataset that can be segmented by subject discipline and theme as well as by institution.

    Bruce Johnson, managing director at evasys is enthused about the potential for the technology to drive culture change both in how student feedback is used to inform insight and action across institutions:

    “When you’re thinking about how to create actionable insight from survey data the key question is, to whom? Is it to a module leader? Is it to a programme director of a collection of modules? Is it to a head of department or a pro vice chancellor or the planning or quality teams? All of these are completely different stakeholders who need different ways of looking at the data. And it’s also about how the data is presented – most of my customers want, not only quality of insight, but the ability to harvest that in a visually engaging way.”

    “Coming from higher education it seems obvious to me that different stakeholders have very different uses for student feedback data,” says Stuart Grey. “Those teaching at the coalface are interested in student engagement; at the strategic level the interest is in strategic level interest in trends and sentiment analysis and there are also various stakeholder groups in professional services who never get to see this stuff normally, but we can generate the reports that show them what students are saying about their area. Frequently the data tells them something they knew anyway but it gives them the ammunition to be able to make change.”

    The results are in

    Duncan Berryman, student surveys officer at Queens University Belfast, sums up the value of AI analysis for his small team: “It makes our life a lot easier, and the schools get the data and trends quicker.” Previously schools had been supplied with Excel spreadsheets – and his team were spending a lot of time explaining and working through with colleagues how to make sense of the data on those spreadsheets. Being able to see a straightforward visualisation of student sentiment on the various themes means that, as Duncan observes rather wryly, “if change isn’t happening it’s not just because people don’t know what student surveys are saying.”

    Parama Chaudhury, professor of economics and pro vice provost education (student academic experience) at University College London explains where qualitative data analysis sits in the wider ecosystem for quality enhancement of teaching and learning. In her view, for enhancement purposes, comparing your quantitative student feedback scores to those of another department is not particularly useful – essentially it’s comparing apples with oranges. Yet the apparent ease of comparability of quantitative data, compared with the sense of overwhelm at the volume and complexity of student comments, can mean that people spend time trying to explain the numerical differences, rather than mining the qualitative data for more robust and actionable explanations that can give context to your own scores.

    It’s not that people weren’t working hard on enhancement, in other words, but they didn’t always have the best possible information to guide that work. “When I came into this role quite a lot of people were saying ‘we don’t understand why the qualitative data is telling us this, we’ve done all these things,’” says Parama. “I’ve been in the sector a long time and have received my share of summaries of module evaluations and have always questioned those summaries because it’s just someone’s ‘read.’ Having that really objective view, from a well-trained algorithm makes a difference.”

    UCL has tested two-page summaries of student comments to specific departments this academic year, and plans to roll out a version for every department this summer. The data is not assessed in a vacuum; it forms part of the wider institutional quality assurance and enhancement processes which includes data on a range of different perspectives on areas for development. Encouragingly, so far the data from students is consistent with what has emerged from internal reviews, giving the departments that have had the opportunity to engage with it greater confidence in their processes and action plans.

    None of this stops anyone from going and looking at specific student comments, sense-checking the algorithm’s analysis and/or triangulating against other data. At the University of Edinburgh, head of academic planning Marianne Brown says that the value of the AI analysis is in the speed of turnaround – the institutionl carries out a manual reviewing process to be sure that any unexpected comments are picked up. But being able to share the headline insight at pace (in this case via a PowerBI interface) means that leaders receive the feedback while the information is still fresh, and the lead time to effect change is longer than if time had been lost to manual coding.

    The University of Edinburgh is known for its cutting edge AI research, and boasts the Edinburgh (access to) Language Models (ELM) a platform that gives staff and students access to generative AI tools without sharing data with third parties, keeping all user data onsite and secured. Marianne is clear that even a closed system like ELM is not appropriate for unfettered student comment analysis. Generative AI platforms offer the illusion of a thematic analysis but it is far from robust because generative AI operates through sophisticated guesswork rather than analysis of the implications of actual data. “Being able to put responses from NSS or our internal student survey into ELM to give summaries was great, until you started to interrogate those summaries. Robust validation of any output is still required,” says Marianne. Similarly Duncan Berryman observes: “If you asked a gen-AI tool to show you the comments related to the themes it had picked out, it would not refer back to actual comments. Or it would have pulled this supposed common theme from just one comment.”

    The holy grail of student survey practice is creating a virtuous circle: student engagement in feedback creates actionable data, which leads to education enhancement, and students gain confidence that the process is authentic and are further motivated to share their feedback. In that quest, AI, deployed appropriately, can be an institutional ally and resource-multiplier, giving fast and robust access to aggregated student views and opinions. “The end result should be to make teaching and learning better,” says Stuart Grey. “And hopefully what we’re doing is saving time on the manual boring part, and freeing up time to make real change.”

    Source link

  • In defence of university halls of residence

    In defence of university halls of residence

    During my five years living alongside 340 undergraduate students as a hall warden, I have become a firm believer that residential halls are powerful civic learning environments.

    This realisation did not come immediately; if anything, I saw my role as strictly pastoral rather than having any connections to learning and teaching.

    At first glance, the role of a warden has little to do with learning. The term, warden, is an outdated and often confusing title (we are in the process of changing it) to describe a staff member responsible for responding to high-level mental health and disciplinary matters and occasional residential life events.

    I initially approached my role with misplaced enthusiasm, intervening in all manner of student conflicts, leaving little room for their own responsibility. Finding a middle ground between complete non-intervention and excessive control proved a real challenge.

    Over time, I came to understand that effective support meant creating space for disagreement and face-to-face conflict resolution rather than solving problems on students’ behalf.

    Too shy shy

    When I first started, the complaints I received usually came because a student came to my front of house colleagues to alert them of their problem. Whereas now they arrive electronically through e-mail.

    It makes sense. It’s easier, quicker and also means students who may not be around during my formal working hours can make me aware of any issues.

    But sometimes the multiple reports I receive overnight detail seemingly minor problems like a roommate not turning off lights or leaving a window open.

    I think the ease with which students can complain, especially virtually, prevents students from developing crucial conflict resolution skills. Part of living amongst other people is learning to address disagreements. It’s not easy and it’s certainly not comfortable, but it does help you grow as a person.

    It forces you to connect with others you may not agree with – either because of various socio-economic backgrounds, religious views or with those who have different ideas of cleanliness from you.

    I have witnessed meaningful connections form across religious and gender identities, and social classes within student halls. For example, the son of a billionaire bonding with a flatmate who had spent summers as an agricultural labourer in fields in Lincolnshire. Two people who likely would not have crossed paths if they had not chosen to study at the same university.

    I’ve seen interfaith events attended by those with differing faiths or none at all leading to genuine friendships.

    These interactions lack formal learning objectives or assessment metrics, yet provide education that our lecture halls struggle to deliver. Providing the literal space for students to meet helps them develop social capital they cannot necessarily get in a classroom.

    Learning from home

    As a sector, we could do more to analyse and report on the civic benefits offered by halls of residence, and we are beginning to do this work at LSE.

    Most UK university halls operate under an outdated property management model, functioning more like luxury hotels than educational spaces. Some private accommodation companies have introduced luxury facilities where students from wealthy families isolate themselves in environments featuring swimming pools and designer furnishings. While aesthetically impressive, these spaces lack genuine community or learning opportunities.

    These approaches miss a crucial opportunity. Residence halls are sites of learning graduate skills, just as much as the formal classroom. Future employers want complex problem-solving and collaboration skill but the added value of being able to resolve conflict well lies beyond career preparation.

    Holding space

    In my view, modern universities have moved away from an integrated educational vision, focusing primarily on specialised knowledge instead. This fragmentation leaves students ill-equipped to interrogate complex questions and self-discovery.

    Part of this includes being able to navigate conflict constructively and understanding how to create community across differences.

    Residence halls provide spaces where intellectual, ethical, social, and practical dimensions of education can be reintegrated. Abstract concepts from seminars become concrete realities when negotiating shared living. Moral and civic education requires practical engagement with substantive questions about the common good.

    Living amongst peers is a way of acknowledging higher education as a collective endeavour rather than a timetable of classes and lectures.

    Is this overthinking spaces that should prioritise fun and exploration? I don’t think so. Our halls of residence aren’t peripheral to education. Properly reconceived, they could become central to what makes university education distinctive and valuable as higher education confronts an uncertain future.

    Source link

  • The identity crisis of teaching and learning innovation

    The identity crisis of teaching and learning innovation

    Universities love to talk about innovation. Pedagogical innovation is framed as a necessity in an era of rapid change, yet those expected to enact it – academics – are caught in an identity crisis.

    In our research on post-pandemic pedagogical innovation, we found that the decision to engage with or resist innovation is not just about workload, resources, or institutional strategy. It’s about identity – who academics see themselves as, how they are valued within their institutions, and what risks they perceive in stepping beyond the status quo.

    Academics are asked to be both risk-taking pedagogical entrepreneurs and compliant employees within increasingly bureaucratic, metric-driven institutions. This paradox creates what we call the moral wiggle room of innovation – a space where educators justify disengagement, not necessarily because they oppose change, but because their institutional environment does not meaningfully reward it.

    The paradox of pedagogical innovation

    During the pandemic, universities celebrated those who embraced new digital tools, hybrid learning, and flexible teaching formats. “Necessity breeds innovation” became the dominant narrative. Yet, as the crisis has subsided, many of these same institutions have reverted to rigid processes, managerial oversight, and bureaucratic hurdles, making innovation feel like an uphill battle.

    On paper, universities support innovation. Education strategies abound with commitments to “transformative learning experiences” and “sector-leading digital education.” However, in practice, academics face competing pressures – expectations to drive innovation while being weighed down by institutional inertia.

    The challenge is not just about introducing innovation but sustaining it in ways that foster long-term change. While institutions may advocate for pedagogical innovation, the reality for many educators is a system that does not provide the necessary time, support, or recognition to make such innovation a viable, sustained effort.

    The result? Many feel disillusioned. As one academic in our research put it:

    I definitely think there’s a drive to be more innovative, but it feels like a marketized approach. It’s not tangible – I can’t say, ‘Oh, they’re really supporting me to be more innovative.’ There’s no clear pathway, no structured process.
    Academic at a post-92 university

    For some, engaging in pedagogical innovation is a source of professional fulfilment. For others, it is a career gamble. Whether academics choose to innovate or resist depends largely on how their identity aligns with institutional structures, career incentives, and personal values.

    Three identity tensions shaping pedagogical innovation

    Regulated versus self-directed identity Institutions shape identity through expectations: teaching excellence frameworks, fellowship accreditations, and workload models dictate what “counts” in an academic career. Yet, many educators see their professional identity as self-driven – rooted in disciplinary expertise and a commitment to students. When institutional definitions of innovation clash with personal motivations, resistance emerges.

    As one participant put it:

    When you’re (personally) at the forefront of classroom innovation…you’re constantly looking outwards for ideas. Within the institution, there isn’t really anyone I can go to and say, ‘What are you doing differently?’ It’s more about stumbling upon people rather than having a proactive approach to being innovative. I think there’s a drive for PI, but it feels like a marketised approach.
    Academic at a post-92 university

    For some, innovation is an extension of their identity as educators; for others, it is a compliance exercise – an expectation imposed from above rather than a meaningful pursuit.

    This tension is explored in Wonkhe’s discussion of institutional silos, which highlights how universities often create structures that inadvertently restrict collaboration and cross-disciplinary innovation, making it harder for educators to engage with meaningful change.

    Risk versus reward in academic careers Engaging in pedagogical innovation takes time and effort. For those on teaching and scholarship contracts, it is often an expectation. For research and scholarship colleagues, it is rarely a career priority.

    Despite strategic commitments to pedagogical innovation, career incentives in many institutions still favour traditional research outputs over pedagogical experimentation. The opportunity cost is real – why invest in something that holds little weight in promotions or workload models?

    As one academic reflected:

    I prioritise what has immediate impact. Another teaching award isn’t a priority. Another publication directly benefits my CV.

    Senior leader at a Russell Group university

    Until pedagogical I is properly recognised in career progression, it will remain a secondary priority for many. As explored on Wonkhe here, the question is not just whether innovation happens but whether institutions create environments that allow it to spread. Without clear incentives, pedagogical innovation remains the domain of the few rather than an embedded part of academic practice.

    Autonomy versus bureaucracy Academics value autonomy. It is one of the biggest predictors of job satisfaction in higher education. Yet pedagogical innovation is often entangled in institutional bureaucracy (perceived or real) through slow approval processes, administrative hurdles, and performance monitoring.

    The pandemic showed that universities can be agile. But many educators now feel that flexibility has been replaced by managerialism, stifling creativity.

    I’ve had people in my office almost crying at the amount of paperwork just to get an innovation through. People get the message: don’t bother.

    Senior leader at a Russell Group university

    To counteract this, as one educator put it:

    It’s better to ask forgiveness afterwards than ask permission beforehand.

    Senior leader at a Russell Group university

    This kind of strategic rule-bending highlights the frustration many educators feel – a desire to innovate constrained by institutional red tape.

    Mark Andrews, in a Wonkhe article here, argues that institutions need to focus on making education work rather than simply implementing digital tools for their own sake. The same logic applies to pedagogical innovation – if the focus is solely on regulation, innovation will always struggle to take root.

    Beyond the rhetoric: what needs to change

    If universities want sustained innovation, they must address these identity tensions. Pedagogical innovation needs to be rewarded in promotions, supported through streamlined processes, and recognised as legitimate academic work – not an optional extra.

    This issue of curriculum transformation was explored on Wonkhe here, raising the critical question of how universities can move beyond rhetoric and make change a reality.

    The post-pandemic university is at a crossroads. Will pedagogical innovation be institutionalised in meaningful ways, or will it remain a talking point rather than a transformation? Academics are already navigating an identity crisis – caught between structural constraints, career incentives, and their own motivations. Universities must decide whether to ease that tension or allow it to widen.

    Source link

  • Supporting early-career academics – in all their roles

    Supporting early-career academics – in all their roles

    The conventional view of a successful career in academia is a linear pathway from academic study to post-doctoral work to, finally, academic employment. However, this traditional perspective fails to acknowledge the complexity and conditional nature of entering academia.

    Higher education has transformed rapidly into a multi-faceted environment, underpinned by teaching, research, industry experience, scholarly activity, and wider responsibilities – and early-career academics (ECAs) are critical to that academic ecosystem.

    The challenges ECAs face can be extensive: foremost among them the planning and delivering of teaching content, added to the pressure of research, publications and preparing funding applications, as well as engaging in broader activities in pursuit of career development. When coupled with the potential uncertainty surrounding contract renewal, these factors can create an environment where stress and anxiety are pervasive.

    Accessing the necessary resources, activities and support is crucial to developing a thriving career. Helping to achieve a balance between focusing on teaching, research outputs, personal wellbeing and building a strong professional network is fundamental.

    Balancing the multiplicity of roles may make this initial transition difficult for ECAs. While research output and funding success of ECAs are often closely scrutinised, there is a critical aspect of their role that tends to be overlooked and under-appreciated – their teaching responsibilities.

    Priority mismatch

    For many ECAs, the challenge lies in being assigned increasing teaching hours, often including subjects or modules that are far removed from their research or industry expertise. This can be frustrating, diverting time from research, which is typically their primary focus.

    The demands of teaching should not be underestimated. Developing module and session content, grading and providing student support all take up significant time. Combined with the need to prepare, it’s easy to see how there can be little room for research or personal development. The problem is compounded by the increased administrative burden associated with teaching, which in many universities has been on the rise in recent years.

    Moreover, teaching quality is often seen as “secondary” to research output when it comes to academic progression. This can lead to a mismatch in priorities, where ECAs are forced to choose between excelling at teaching or focusing on research to meet the expectations of the next stage of their careers.

    ECAs can be provided with research supervisors, but there can be limited opportunity to access support to discuss pedagogical methods of teaching and learning and preparation of sessions. Even when opportunities exist for ECAs to engage in collaborative networks, peer support and mentoring, engagement can be restricted by work environment such as lack of time, high workloads and isolation

    Bridging the gap

    Many ECAs receive research support, yet less focus is placed on teaching fundamentals and long-term professional development. Often, ECAs may achieve their postgraduate teaching certificate after having started teaching – and the operational guidance and pedagogical skills can often get overlooked.

    Although ECA mentorship programmes do now exist within institutions, and more accessible support is available in professional networks, few universities offer formal mentoring schemes, which would pair ECAs with more senior academics to provide guidance in navigating the complexities of academic careers, specifically on teaching and learning.

    Despite the best possible local institutional support, ECAs will often stress the hidden struggles to develop independently, stating that it is difficult to determine what is supposed to be done and how – or what they are “expected to know.” This results in ECAs finding themselves struggling to build necessary skills to assist them with future teaching commitments.

    How we put a resource together

    A formal mentoring scheme at Hartpury University led us to develop a series of infographics as a visual communication tool to assist the development and delivery of pedagogical concepts to assist teaching delivery (in the subject area of anatomy). One example can be seen here on the National Teaching Repository, with links to others below.

    This was underpinned by discussing with ECAs their needs and resources to support their own teaching journey. These resources have grown organically as an operational user-friendly guide.

    This “anatomy series” appears to have resonated with both mentors and ECAs – according to the downloads we’ve seen from the repository at key points in the academic annual cycle.

    Through a small study (n=7), we collated an illustrative selection of narratives from ECAs and mentors on their thoughts. Both ECAs and mentors reported using the majority of the infographics “somewhat” or “to a great extent,” providing positive feedback in the following areas:

    • clear, evidence-based material that is easy to digest and ready to use as a quick reference guide
    • bite-sized content for quick reference during content creation or planning
    • “user-friendly” approach with concise actionable guidance
    • visually appealing resources that enhance clarity and learning retention.

    In addition, mentors highlighted:

    • effective scaffolding and signposting for module and assessment design
    • succinct prompts as a helpful reminder of the fundamental principles to focus on with ECAs
    • accessible, shareable resource featuring clear examples for ECAs.

    Ideas for future topics provided by respondents included technology and innovation, student support and success, and lecturer wellbeing.

    For a thriving academic career

    A rewarding academic career needs the right support and balance to transfer knowledge, inspire a generation, and pursue research.

    ECAs face complex challenges – but universities can help by improving mentorship programmes, building supportive networks, and offering guidance, as well as creating user-friendly resources that assist the practicalities of teaching.

    Early-career academics are central to the academic ecosystem, yet their struggles can be overlooked, particularly within the teaching and learning environment. By establishing a more sustainable and supportive environment, we can ensure that they are able to thrive within the multiplicity of roles they are asked to take on, and contribute to the academic community for years to come.

    Source link

  • From crisis to community: engaging students in post-pandemic classrooms

    From crisis to community: engaging students in post-pandemic classrooms

    School and other learning environments are often a safe place for students who have difficult home lives.

    I know, I was one of those students. I take that knowledge into every classroom that I enter, and my understanding of student engagement and student experience are woven into my pedagogy of care and teaching to transgress.

    I cannot, (and do not wish to!) separate my lived experience from my teaching. As someone who dropped out of the university that I now work at, I do have an interesting insight into building community and belonging into the curriculum.

    As I wrote here with Lisa Anderson, we require a radical shift in how we consider the needs of students. I want every student in my classroom to experience it as a safe and welcoming space.

    These are not buzzwords or trends, it is how I ensure that students are able to learn – I want them to be in the room. Teaching is a relational activity that requires commitment, experience, honing our craft and being willing to adapt.

    The university sector is not in a good place, and as committed as I am to my research, it is teaching that brings me joy and new ideas every single time I enter the classroom. When we teach to transgress, it is for us as much as it is for the students.

    The classroom reminds me of what is possible. Engaging strongly with the literature of the UK’s leading emergency and disaster planner, Lucy Easthope, I recognise the education will be impacted forever by the pandemic, and I want to play my part in the recovery.

    Crime, justice and the sex industry

    I lead the largest optional final year module in my department, with 215 registered students, based on my 23 years’ experience of the sex industry. It was a community of care that got me here, with colleagues from around the country (and globe!) sharing material and ideas with me when I launched this module in 2020. Collaboration and teaching go hand-in-hand and we must allow time for this.

    The module is underpinned by my nonlinear pedagogy which I write about here. The design empowers students to have control over the direction and pace of their learning. All content is uploaded to our virtual learning environment Canvas in week one. There are weekly recorded lecture summaries, and 2-hour weekly workshops.

    The content also includes a comprehensive library reading list, weekly reading folders, watch folder and collaborative tools.

    This year the module is celebrating its fifth birthday and the student engagement is better than ever before. Here are some things that I have learned and that I am reflecting on.

    A welcoming classroom and learning names

    Where possible, I always enter the classroom ten minutes before class begins (this is definitely not always possible in a large and busy campus with extreme demands on estates and our time) to provide a prepared and calm setting for students to arrive. This is also helpful for me as a neurodiverse teacher.

    I like to greet students as they arrive, and learn names wherever possible (photo class lists are your friend).This sets the tone for our warm and welcoming teaching community. It demonstrates the way in which we will invite peers to contribute and talk through the content. It may seem a small thing, but it makes a huge difference to teaching and learning.

    Front-loaded prep

    As a dyslexic I need to be prepared. This is a large module, and a busy teaching load. I spend the weeks before semester begins frontloading my prep so that I am ready to go. This involved re-recording the summary E lectures, updating workshop materials, sheets, reading folders, module guides, etc.

    Visitors to my office are surprised to see a row of 12 piles along the floor- with each week’s content printed out, highlighted, and ready to go. I am always very grateful once semester starts that I took the time to do this. It creates a calm tone to classes that students explicitly comment on.

    Lesson plans

    This year I went old-school in multiple ways, including buying a hardback lesson planner, in which I mapped out the learning objectives for every workshop – mapping against learning outcomes for the module.

    Physically mapping these out, with prompts, links to the readings and case studies, was something that students positively picked up on. This also ensured adaptability and that I was reflecting upon and updating my material. Students need calm and expert guidance; experienced teachers are key.

    Workbooks

    Acting on student feedback from the previous year, I designed a workbook that students can print out or use digitally. Students always make a lot of notes on this module, and the workbook helps them with organising those thoughts. In class, I was very pleased to see rows of pink workbooks looking back at me.

    The workbook also includes space for questions, and learners can bring this to my student support hours. I have been learning a lot from school teachers, and recognising how much extra structure students need post-pandemic.

    Learning through tempo

    I made an active decision this year to experiment with the tempo of each workshop class, with differences even between some workshop groups. This was in response to student feedback who wanted some slower sessions in order to read in class, and more time to talk with their groups/peers.

    This was music to my ears (pun absolutely intended) and it made me reflect on the pace and rhythm of my classes. I am a high-energy teacher and I like to pack a lot into classes, but stripping (pun not intended!) some of this back to create quieter time (for class reading) and slower sessions with more time for groups to talk, has been a game-changer. Students actively requesting some slower workshops so they could read together in class, was amazing to witness. Students reacted overwhelmingly positively to my ability to respond and adapt.

    Learning through play

    It is interesting in this post-disaster period of the pandemic to witness students enjoying, and requesting, playful activities in class. As I argue here, we need to build community into the curriculum to boost attendance.

    Poster paper and felt tip pens might have attracted horrified faces a few years ago and a low uptake, but this year, every single “play” activity that I have offered has been taken up by almost every student. I always offer a range of engagement tools, with non-verbal options such as our collaborative google doc, padlet, and other online tools, and I offer the option for sheets, paper, pens etc.

    A welcoming, hospitable classroom where students know they are being considered, pays dividends in engagement and mutual respect. Once students feel safe and able to take risks, no matter how low-stakes, they open up, and engage in difficult and complex debates.

    One group activity looked at sexual entertainment venue closures using five different pieces of coloured card to map out key findings from two different journal articles, identify and apply concepts from earlier weeks in the module, examples of venue closures, and examples of campaign group discourse.

    A “fun” activity that involves deep critical thinking and the ability to successfully weave together multiple forms of evidence to formulate a convincing argument. I then took a photo of the giant map we all created across the module. Every single student wanted to take part; students are actively seeking community and togetherness within the classroom.

    As Treasa Kearney and I argue here, campus should be a treasured space that offers valuable connections to students.

    The activity with foam stickers, which I thought students would resist, was the most popular activity of the semester (after the guided walk, below). Through the mechanism of light-hearted play, students successfully navigated a tricky and sensitive topic examining the harms, dangers and exploitation associated with online sex work. We ended up with students stickering their laptops, phones, their workbooks, and themselves! We cannot forget that these are all students of the pandemic, they missed out on so many opportunities to interact with peers. They are embracing every opportunity to connect with each other within timetabled sessions.

    Guided walk

    Another activity on the module (and the one that students most favourably comment on) is our guided walk of sexual entertainment venues in Liverpool city centre. I provide online material for accessibility purposes recognising that not all students can walk around the city, or may not wish to.

    For students who attend, we map out the city in terms of gendered harm and risk, and I give a lecture inside of a sexual entertainment venue that opens exclusively for our class. This brings the Policing and Crime Act 2009 to life, and gives students a unique insight into what the key texts are discussing. It is also very much a community building exercise, with a large proportion of our module cohort in attendance. Learning outside of the classroom is very important for student engagement.

    Scaffolding learning

    I intentionally choose to layer texts: curating texts of various complexity, using tools such as padlet. Students choose what texts to access based on their own areas of interests and confidence, as they progressively build up skill and academic knowledge of the area. This ensures that the module is accessible to all students, with learners challenged at a point which feels appropriate for them.

    It also means that students always have supported content to work with. In week ten, we looked at the media, and we returned to a key text from week eight, to apply three media myths from a journal article to three documentary clips. Using worksheets, the students demonstrated a sophisticated ability to apply a criminological concept to media sources.

    Responding to ongoing feedback

    Building a rapport with students through modelling a pedagogy of care and inclusion, equips students with the ability to provide feedback throughout the semester. Students appreciate the wealth of resources available from the beginning of semester, but others may feel overwhelmed with choice.

    In rapid response to student feedback, I started to provide recommended readings in addition to the large selection. Students appreciated this speedy closing of the feedback loop, and being valued co-producers of the module approach. The student feedback for the module was the best yet.

    Accessible assessment as the default position

    With growing numbers of students experiencing health issues, it is good practice to think of accessibility as the default position, not an additional bolt-on. I am in favour of different modes of assessment that students can choose from, or developing an assessment that can be approached in different ways. I have written here about my letter assessment, inspired by the work of Katie Tonkiss. Students often feel worried about “academic writing”, and this assessment allows students to use the first person, and to use a more colloquial writing tone if desired. The students develop a nuanced, convincing and influential writing style, with the ability to hold conflicting and competing harms in tension.

    Ultimately, it is about remembering that teaching is a huge privilege and blessing. We get to have an impact on so many people and play a part in shaping ideas and innovations of the future. I will never lose the gratitude for getting to do this job and remembering where I come from.

    Source link

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

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

    Highlight from a Canadian PSI

    New AI Research Assistant available in library search

    April 25th, 2025. University of Manitoba. 

    UManitoba recently announced the launch of their new AI Research Assistant (beta), a GenAI tool to help with library searches and to help gather initial insights on research topics. Functions include providing summarized responses to research questions, recommending relevant publications from the libraries’ collections, and suggesting additional question prompts to expand the research topic.

    AI Policy

    Encadrement de l’IA en enseignement supérieur: des syndicats d’enseignants déplorent la lenteur de Québec à agir

    Dion-Viens, Daphnée. Le Journal de Montréal. April 24th, 2025.  

    “Québec a annoncé l’automne dernier la création d’une instance de concertation sur l’intelligence artificielle en enseignement supérieur, dont les travaux ont débuté en octobre. Le bilan des travaux devait être présenté en avril, mais cet échéancier a été repoussé à la fin de l’été. Un cadre de référence pour l’intégration de l’IA dans les cégeps et les universités devrait être présenté à la rentrée. La Fédération nationale des enseignantes et enseignants du Québec (FNEEQ-CSN) déplore ce report. Le temps presse puisque plusieurs établissements attendent ces lignes directrices pour agir. »

    Universities have a chance to lead in shaping AI’s future

    Kaya-Kasikci, S. et al. University World News. April 23th, 2025.

    The authors of a recent academic analysis of national AI policies share their thoughts about how the diverse AI policy approaches and perspectives around the world might impact the future of post-secondary education.   

    Transformation of Education

    Are You Ready for the AI University?

    Latham, S. The Chronicle of Higher Education. April 8th. 2025. 

    “What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.“

    AI is unable to outpace higher education

    Lumina Foundation. April 29th, 2025. 

    “Leaders from academia, economic development, and industry discuss how universities and colleges are advancing research and equipping students with the skills to lead in an AI-powered future. From addressing social inequities to preparing cities for the economy of the future, the conversation highlights the transformative potential of AI when nurtured within higher education, and the tradeoffs that must be made in an education system wired for the past.“

    Gen Z says AI has made their college degrees irrelevant

    Torres, R. April 29th, 2025. Higher Ed Dive.

    “The ongoing push to deemphasize college degree requirements in job postings has led half of Gen Z job seekers to view their degrees as a waste of time and money”, according to a recent Indeed report that surveyed 772 US adulted workers and job seekers with an associate’s degree or higher.

    Workforce readiness

    Labor Market Disruption and Policy Readiness in the AI Era

    McGrath, E. and Burris, M. The Century Foundation. April 29th, 2025.

    Policy recommendations to prepare current and future workforce for AI.

    Teaching and Learning

    Here is how experiential learning can save colleges from AI

    McKeen, S. University Business. April 30th, 2025.

    “If knowledge is now universally accessible, what remains of higher education’s value? (…) The traditional college lecture is obsolete. Why should students pay thousands in tuition to sit in a lecture hall when AI can summarize complex theories in seconds? The world no longer rewards passive knowledge absorption. Employers want graduates who can think critically, collaborate effectively, and apply knowledge in complex, unpredictable environments. Experiential learning isn’t just an educational trend— it’s a survival strategy.“

    Is AI Enhancing Education or Replacing It?

    Shirky, C. The Chronicle of Higher Education. April 29th, 2025.

    “The fact that AI might help students learn is no guarantee it will help them learn. […] The teacher can advance learning only by influencing the student to learn.Faced with generative AI in our classrooms, the obvious response for us is to influence students to adopt the helpful uses of AI while persuading them to avoid the harmful ones. Our problem is that we don’t know how to do that.“

    Teaching Writing in the Age of AI

    Mintz, S. Inside Higher Ed. May 2nd, 2025. 

    « As artificial intelligence becomes increasingly capable of generating polished, grammatically correct text that meets academic standards, educators face a critical challenge: How can we teach students to write authentically and effectively? » This author talks about the challenges of teaching writing in the AI era, and provide tips on how to move beyond these challenges.

    3 Laws for Curriculum Design in an AI Age

    Chaudhuri, A. and Trainor, J. Inside Higher Ed. April 30th, 2025.

    The authors share « a framework for thinking about how to address AI technology in the curriculum at all levels, from the individual classroom to degree-level road maps, from general education through graduate courses. »

    When GenAI resets the assessment baseline

    Jones, C. Times Higher Education. April 29th, 2025. 

    A visiting lecturer at Regent’s University London, Kingston University and more shares how he reassessed his assignment to mitigate students using AI to do all the work for them. His initial plan was to have ChatGPT create a « baseline » output against which he could mark his students assignments, but he was surprised to realize that the ouptut was better than most undergraduate students would have delivered. He had to review his approach, and shares his strategy in this article.

    Research

    AI Summary ‘trashed author’s work’ and took weeks to be corrected

    Ross, J. Times Higher Education. April 24th, 2025.

    AI research summaries ‘exaggerate findings’, study warns

    Ross, J. Times Higher Education. April 16th, 2025.

    « Dutch and British researchers have found that AI summaries of scientific papers are much more likely than the original authors or expert reviewers to ‘overgeneralise’ he results. (…) AI summaries – purportedly designed to help spread scientific knowledge by rephrasing it in ‘easily understandable language’ – tend to ignore ‘uncertainties, limitations and nuances’ in the research by ‘omitting qualifiers’ and ‘oversimplifying’ the text. Read the academic paper here. 

    AI Literacy

    Using peer networks to integrate AI literacy into liberal arts

    McMurtrie, B. The Chronicle of Higher Education. April 24th, 2025.

    Read how an associate professor of anthropology at the University of Texas at San Antonio is teaching students about effective AI use.

    Urgent Need for AI Literacy

    Schroeder, R. April 30th, 2025. Inside Higher Ed. 

    « As we approach May, alarm bells are ringing for all colleges and universities to ensure that AI literacy programs have been completed by learners who plan to enter the job market this year and in the future. »

    Source link

  • Rethinking our approach to maths anxiety

    Rethinking our approach to maths anxiety

    As higher education professionals, we encounter a wide spectrum of emotional responses to mathematics and statistics.

    This could vary from mild apprehension to teary outbursts, and often, it can also lead to complete avoidance of the subjects, despite their value in achieving success both in university and after.

    Behaviours such as procrastination can hinder student learning, and as such, it is imperative that students are taught to challenge these feelings.

    An analogy that we have used is fear of spiders – we may be likely to avoid places that house spiders, and in the same way, students may procrastinate or completely avoid maths-related tasks due to their “discomfort”.

    Additionally, cultural attitudes, gender, and past educational experiences can all influence how someone responds to mathematics.

    The term “maths anxiety” is commonly used to describe any negative emotion related to mathematics. However, when viewing it from a psychological viewpoint, we argue that there needs to be a distinction made between clinical anxiety and general apprehension.

    Most of us would feel worried if we were taking an exam that included mathematics or statistics – it is normal to feel some level of worry about being tested, and we can learn to manage this.

    Clinical anxiety, on the other hand, is more extreme, and significantly impairs the ability to manage daily tasks – it requires psychological support. By conflating these experiences, we run the risk of over-medicalising a typical reaction to potentially challenging material, and we might miss opportunities to provide appropriate support, or to help students to self-regulate their emotions.

    Various approaches have proven successful in our practices for dealing with worries.

    What works

    We’ve found that opening up the conversation about anxiety early on – creating a safe space where students can explore what it is, when it shows up, and how it affects them. With each new group, we try to start this discussion as soon as possible, framing it in broad terms to keep it inclusive and non-threatening. Students often respond well when asked to think about situations that make them feel nervous – things like sitting an exam, taking a driving test, or speaking in public.

    From there, we invite them to notice the physical and emotional effects anxiety has on them. Common responses include sweating, shortness of breath, feeling jittery or nauseous, difficulty concentrating, or an urge to get away. These are usually sensations they’ve experienced before, even if they haven’t named them. When we approach it this way – shared, grounded in real life, and without judgement—it tends to normalise the conversation. We’re always conscious of the potential for some students to feel overwhelmed by the topic, so we stay attuned and pause when needed, signposting to further support if things get too heavy.

    Asking students what they already do when they feel anxious helps too. Giving everyone a chance to reflect and share helps surface the small strategies – breathing deeply, taking a walk, positive self-talk – that they may not realise they’re using. It affirms that they do have tools, and that managing nerves is something within their control.

    Simply asking students how they feel about using maths or statistics in their studies can also help. More often than not, a few will admit to feeling nervous – or even anxious – which opens the door to normalising those feelings. From there, we can connect the strategies they already use in other situations to the challenges they face with maths, helping them build a toolkit they can draw on when the pressure mounts.

    Some strategies that students find helpful include mindful breathing, visualising a calming place, or even splashing cold water on the face to reset. Others involve filtering out negative messages that chip away at confidence, re-framing self-talk to be specific and encouraging – like swapping “I can’t do maths” for “I’ve learned before, I can learn again” – and, crucially, building skills and confidence through steady learning and practice.

    There may, however, be cases where a student’s anxiety is not assuaged by employing these techniques, and a level of clinical anxiety may be suspected, requiring further support from counsellors or other professionals. In these cases, ensuring the students are guided, even taken, to access the relevant support services is key. This may lead to requests for reasonable adjustments as well as prescribed treatments, thus enabling the student to face the challenge and hopefully emerge successfully on the other side.

    Prizes for all

    Of course, these are all interventions that are useful for students who are struggling with worries about maths – but there are also things we can do to support all of our students. Some students will be struggling quietly; some will have other learning differences that might impact on their ability to learn maths, such as ADHD.

    One approach we might consider is Universal Design for Learning, where we make learning accessible for all our diverse students, regardless of the specific issues that they might experience, or whether they tell us about those issues. Giving students choice in how they complete their assessments, allowing them access to resources or notes (open book) during test situations, and not imposing tight timescales on assessments can be one way to support students to achieve their best. Taking this approach also removes some of the administrative work involved in working out reasonable adjustments!

    Sometimes there are professional requirements that mean that such adjustments are not possible (for example, calculating doses in nursing where achieving 100% is a requirement), but often it can be helpful to consider what we are assessing. Do we need to assess a student’s ability to solve a maths problem from memory and under time pressure, or do we want to know that they can solve a problem they may encounter in a typical graduate role when they might be able to search how to approach it?

    Authentic assessment can be a useful tool for making maths learning and assessment less scary and more accessible.

    Differentiating between a regular level of apprehension and clinical anxiety will help us to be better placed to implement strategies to support students and staff in succeeding on their mathematical or statistical journey. This can begin at the curriculum design and development stage, extending beyond our work with individual students.

    Supportive relationships between learning development tutors, students and teaching staff enable us to implement tailored strategies for minimising maths anxiety. By working together, we can reframe maths learning to be seen as an opportunity for growth, and not something to fear.

    Source link

  • Extracurricular activities have big benefits for students

    Extracurricular activities have big benefits for students

    Extracurricular activities have big benefits for both students and the university – but we could do more to get students involved.

    University life for students is busy these days, not just with lectures and assessments but for many students, also the need to work to fund their studies.

    Extracurricular activities can not only add value to the student experience and are a key offering of universities which have some surprising benefits for both.

    They have a demonstrative effect in reducing depression, boosting employability skills, giving students an opportunity to try new things without pressure of assessment – and participation in extracurricular activities is closely related to increasing alumni donations to the university, a clear sign of happy and successful graduates.

    However, in order for us to get the most out of them we need both the benefits, and the activities themselves, to be signposted better within the university as well as ensuring that some groups that would benefit most despite lower engagement are encouraged to get involved.

    Competition for student’s time is fierce, with coursework, exams, and projects, but also for those students who need to work in paid employment to fund their studies and living costs. But extracurricular activities have several benefits for the students, and whilst a small number of students find it harder than others to balance activities and academic work, outcomes are generally positive.

    The vast majority of studies around the world have found a general correlation between taking part in extracurricular activities and improved academic performance. There are a large range of activities that students could do – activities that complement the curriculum such as the MBA programme having a pitching competition or a weekend hackathon (often called cocurricular activities), whilst there are also activities from outside these boundaries such as sports which are unrelated to the student’s core subject.

    Regardless of the actual activity that they do, there are a range of positives. They improve employability skills and leadership skills – giving the student CV-worthy examples, and they are a way to show an employer that you are interested in a specific career.

    Employers have suggested extracurricular activities can help determine your cultural fit, and show examples of commitment and interpersonal skills. Involvement in social enterprise or charitable projects are looked upon favourably. Improving students’ employment prospects, especially with extracurricular activities having a “levelling up” effect for those from minority groups and those from lower socio-economic groups – this reflects well on the university and its mission.

    Extracurricular activities allow students the opportunity to try more hands-on and experiential activities without the risk and pressure of needing a good grade, or being creative using spaces such as makerspaces. It might also be a rare opportunity to work in a cross disciplinary manner and diversifies your group of friends.

    Residential courses and field trips are also valuable, with research showing that they stimulate a sense of togetherness with those on their courses, and with a chance to see their subject in action which helps them put it in context, encourages more enjoyment of it, and allows them to form career plans based on that subject, with those in late adolescence and early adulthood especially attuned for developing career self-efficacy in this way.

    These residential activities seem to disproportionally benefit poorer students and those from minority groups, resulting in higher marks, thus making them ideal activities for universities to support. With the Sutton Trust suggesting the number of students in the UK now living at home due to the cost of living to be 34 per cent, rising to 65 per cent from those in poorer socio-economic groups, it is a rare opportunity for some students to escape from living with parents.

    Extracurricular activities are seen as adding value by students, especially those overseas students who readily sign up for activities, as we have found with off campus opportunities we offer in entrepreneurship quickly booked up by enthusiastic overseas students, such as our “Enterprise School” in the Lake District with postgraduate groups from mixed subject areas working together late into the night (putting the staff to shame) – and keeping in touch when they return to Manchester and beyond, building a network they would never have otherwise met.

    What can we do to improve them?

    We can try to engage older and ethnic minorities more as these groups tend to spend less time on extracurricular activities at the university, and make them more friendly for those who may have carer commitments, for example not always having events in the evening.

    This might help other groups of students – I have also found as an academic adviser that many students in Manchester live with parents and commute from nearby cities such as Liverpool and Sheffield, with their notoriously bad rail lines – and these students are less likely to take part in extracurricular activities as they prioritise when they travel to university.

    Those from lower socio-economic groups also spend less time on extracurricular activities due to the pressure of paid employment, so encouraging them to consider at least some extracurricular activity would be beneficial.

    First year males could also be a target for engagement – whilst suicide rates for students overall are considerably lower than that of the general population, for first year males the rate was found to be 7.8 per 100,000 people, significantly higher than males of other years and female students as a whole, which has been attributed to social isolation, alcohol consumption and the general life change of moving to university.

    Involvement in extracurricular activities reduces suicidal tendencies by increasing the sense of belonging and lessening the sense of burden a student might feel, and are a relatively low cost option as part of the universities commitment to its duty of care. It has been suggested by the Office for Students that those students who are in several minority categories concurrently are particularly vulnerable from a mental health perspective, so being aware of these students is especially important.

    Students partaking in extracurricular activities reported having a depressive mood less often and report the development of a long-lasting social support network – which may well identify problems and help students before the university even becomes aware of anything wrong.

    Unfortunately, many that will benefit most from them won’t take part – so we need to encourage them to do so – especially students’ academic advisers who might have a broader picture on how well the student is getting on. Studies have found that female students are more likely than males to undervalue the skills they have gained from extracurricular activities – again academic advisers could reinforce this for all, especially when preparing for job applications.

    Alumni speakers could also reference what extracurricular activities they did to focus on how this helped them while at university, and examples of how it helped them find employment and fit into the workplace.

    Programme directors might also recommend what co-curricular activities might be useful for the student’s degree, and students themselves such as at the student’s union could communicate more on the benefits of extracurricular activities, especially to engage first years, throughout the year as well as during the whirlwind of welcome week – some students might need time to settle down before they can see how much spare time they can allocate to extracurricular activities.

    Ask students when they want activities to run – this might be different for city centre or out of town campuses – but we have found in Manchester a surprising number of students who are prepared to commit to a whole Saturday working on a hackathon, for example.

    Interestingly, there is a correlation between the number of extracurricular activities that a student partakes in and alumni donations, with a Wonkhe study suggesting that participation in extracurricular activities was a much stronger indicator of donation to their alma mater even than degree class obtained, showing extracurricular activities strengthen the relationship between students and their university.

    There is every reason for universities to provide a full range of opportunities – and to encourage students to get involved.

    Source link

  • With the power of knowledge – for the world

    With the power of knowledge – for the world

    I went along to AHUA conference on Tuesday, and saw a fascinating presentation from Esa Hämäläinen, who’s the Dir­ector of Ad­min­is­tra­tion at the University of Helsinki.

    The university has easily one of my favourite origin stories – it was established by a 13-year-old girl who the world came to know as Queen Christina of Sweden.

    It also has a cracking set of values, some of which appear now to be the sort of thing that’s banned by the Office for Students in England.

    In 2015, under Prime Minister Juha Sipilä’s administration, the government announced a €500 million cut to higher education budgets in Finland.

    That followed a previous €200 million reduction and included freezing the university index, which had adjusted funding based on inflation.

    As a result, universities like the University of Helsinki had to lay off hundreds of staff – about 400 in the case of Helsinki.

    There’s a lot of different ways of calculating staff-student ratios that often make comparisons problematic – but one of the things I was pondering on the train was how they are doing what they’re doing on an academic SSR of 22.2:1 – significantly higher than in the past, and significantly higher than the UK.

    For the avoidance of doubt, I’m not searching for a blueprint on how to shed academic staff. But if cuts are going to rain down anyway, understanding how other systems work beyond “Oh look they have ECTS too” I think (hope) can help.

    I say this partly because a lot of people I talk to are experiencing or implementing plain and simple “reduce the number of optional modules” strategies based on the efficiency of more/large/core – which most research suggests students don’t like, and I suspect is a probable cause of during and post-degree regret.

    What’s fascinating is that rather than just accept the inevitability of a thinner student academic experience as a result of those cuts, the university evolved its Bildung philosophy to make a whole range of scaffolding changes to cope on fewer staff. And I’ve spent a long train journey trying to work out how.

    They call a Twix a Raider

    First some Twix/Raider basics. There’s 180 ECTS for a Bachelor’s degree, designed to be taken over 3 years. No difference to the UK there (unless we count Scotland) other than students can take longer to obtain those 180, supported via the maintenance system to do so – although universities across Europe are variously under government pressure/incentives to speed that up a bit.

    It’s also worth noting that for various reasons, the average entry age for bachelor’s degree programmes in Finland is 24, compared to an OECD average of 22. We have (along with Belgium) the youngest freshers and the fastest completion times in the OECD. That we then beat Belgium on completion rates often causes me to reflect on whether that’s a sign of success or a signal of conveyor-belt trapping, a cause of mental health problems and a driver of lower of academic standards – but I digress.

    What we’d typically call “modules” in the UK are referred to as “courses” in Finland. As for what we’d call a “programme” or “subject pathway”, it varies – but at Helsinki, undergraduate students complete two core “modules”, each comprising a collection of courses, one for “Basic” studies (what we’d think of as a UG first year), and one for “Intermediate” studies (what we’d think of as a second and third year).

    These two modules are each awarded a single grade on a 1–5 scale, and it’s these two grades that appear on the student’s degree transcript.

    So, instead of the UK-style baffling algorithm of final grades weighted in different ways across multiple modules, students in Finland receive just two key grades on their transcript – simple, succinct, and arguably more transparent, along with the pathways taken within them. Additionally, students can receive a separate distinction mark for their dissertation. A nice touch.

    The University of Helsinki is Finland’s flagship institution – huge in size, high in status, and widely seen as the country’s de facto elite public university. And yet, intriguingly, there are only 32 undergraduate degree programmes on offer across its 11 faculties. Within each of these programmes, students have considerable freedom to create their own study path, but the structure is strikingly straightforward – 11 faculties, 32 programmes, no sub-departments, and no sprawling web of hundreds of “course” leaders.

    That also means 32 academic communities, with 32 academic societies that students join to get support from eachother and engage in things – a nice size that avoids having to find 1500 course reps or trying to sustain a meaningful single student community from 40,000 students – all supported by 32 sets of student tutors, of course.

    The mother of all science

    Let’s take Philosophy as an example. To complete the degree, students have to earn 90 ECTS credits in Philosophy-specific study, 75 elective credits, and 15 from general studies. That structure encourages both specialisation and breadth.

    Oh, and a quick technical note – the standard assumption in Finland is that 1 ECTS credit represents 27 hours of student effort. In the UK, by contrast, it’s 20. The reasons are dull and bureaucratic (that didn’t stop me working out why) but worth bearing in mind when comparing intensity.

    First it’s worth digging into the 90 credits earned in Philosophy. These are split into two main “modules” – Basic Studies (30 credits) and Intermediate Studies (60 credits). As I said earlier, the former corresponds to first-year study, and the latter covers second and third year.

    The 15 credits of general studies are interesting. 2 credits are awarded for a reflective planning exercise where students work with an academic to design their personalised study plan – a kind of “choose your own adventure” approach that signals a departure from spoon-feeding from day one. That’s assessed on a pass/fail basis.

    There are also three credits for digital skills training, delivered via self-study – two credits within the Basic Studies and one within Intermediate. Again, this is assessed pass/fail and serves both to build capability and to ensure students are confident in using the university’s largely self-service systems.

    Then there are 10 credits dedicated to communication and language skills. These span both written and oral communication, include components in both Finnish and Swedish, and feature academic writing training – often completed in groups. All of this is, again, pass/fail.

    What I find interesting about these is a recognition that designing a bespoke study programme (that can change over time), along with IT and communication skills, are really about becoming a student – here they are recognised as taking actual time.

    In the Basic Studies module, students take six standard “intro to…” courses worth 5 credits each. These are relatively straightforward in design, delivery, and assessment. Each course is normally assessed via a single exam, although in most cases students can opt to complete coursework instead.

    In each degree programme, 60 subject-based credits – what we’d call second and third year content – then form the Intermediate “module”. Of these, five are allocated to the thesis (dissertation), while the remainder is typically made up of 5-credit courses, offering students considerable choice and customisation.

    To move into intermediate, there’s a 0 credit “maturity” assessment so students aren’t moving there until they’re ready. Then of the 60 Intermediate credits, 30 are structured as follows. 5 credits are awarded for a proseminar, which functions like a structured, small-group academic workshop:

    At the beginning of the course, students are given a review of the basics of academic writing and how to critically review and oppose an academic work. How to formulate a research question is discussed and advice is given on how to obtain source material. The student is then expected to formulate a research question in the form of a short abstract which is then reviewed and discussed by the teacher and other students. Then a period of research and essay writing takes place where the opportunity for supervision is given. At the end of the course, the student must present an essay for review by an opponent and oppose another student’s essay.

    5 credits are for a Candidate intuition seminar, and that looks like this:

    At the beginning of the course, students receive a refresher course in the basics of academic writing and how to critically review and oppose an academic paper. At the beginning of the course, there is also a discussion on how to formulate a research question and participants are given advice on how to obtain source material. The student is then expected to formulate a research question in the form of a short abstract which is then reviewed and discussed by the teacher and other students. This is followed by a period of research and essay writing where opportunities for supervision are provided. At the end of the course, the student must present an essay for review by an opponent and act as an opponent in the processing of another student essay.

    Then as well as the dissertation (thesis) itself there’s 5 credits for a compulsory internship (pass/fail) and 5 credits for preparing to apply what you did on your degree to the world, and that looks like this (also pass/fail):

    This gives the student the opportunity to independently explore the individual, growing competence that the degree provides and the importance of competence in a changing society and working life. The aim is for the student to become familiar with and reflect on the ways in which the unique competence provided by studies in philosophy, in collaboration also with studies in other subjects, which the student has chosen, can be relevant to our lives, to working life, society and the world.

    It can be completed in various different ways, in consultation with the responsible teacher – collaboration, independent studies and observation and reflection tasks related to other modules. An e-portfolio or course diary can also be included.

    And then finally there’s a 5 credit compulsory, and in Philosophy that’s a classic module on History of Philosophy.

    For the other 30 credits of Intermediate there’s then a collection of “classic” academic modules again, often in pathway clusters.

    So via the 60 “subject” ECTS points and the 15 “general studies” ECTS points, that’s 105 ECTS accounted for. And here’s the thing. The 75 left are acquired by picking the sort of stuff I’ve talked about above, but they must be from other degree programmes!

    That means that a Philosophy student that wants to do the basics in statistics or whatever can access what might be regarded as another course’s core modules. That obviously means a large amount of interdisciplinary stuff happening, with quite a lot of interesting student mixing happening too. It also means that the “courses” are highly efficient.

    Oh, and also if you do Erasmus, or learn skills at work, or as a volunteer, or whatever…

    You can receive credit for studies you have completed at higher education institutions either in Finland (universities, the National Defence University, and universities of applied sciences) or abroad. The studies must have been successfully completed.

    You can also get credit for skills you have acquired in working life, positions of trust or hobbies, for example. In this case, we are talking about skills acquired in a way other than formal education.

    A time for reflection

    At this point down the rabbit hole I see small, simple-to-design and simple-to-assess academic modules (without having to cram in 100 agendas), plenty of pass/fail credit (less grading means less pressure for everyone), and lots of focus on choice and independent study. And an actual recognition that skills development matters without it always having to be crammed into optional activity students don’t have time for, or academic modules.

    Just a note on grading. One of the things happening here is that grading itself is less complex (5 is Excellent, 4 is Very good, 3 is Good, 2 is Satisfactory, 1 is Passable and 0 is Fail), there’s less of it to do in general, and the ability to re-take assessments in a funding system that allows for setbacks reduces the need for extenuating circumstances and extensions and so on – so the stakes are less high, less often.

    So broadly what I take from it all is:

    1. The hidden curriculum is less hidden
    2. Academic staff have a simpler life
    3. The credit system overall creates rounded graduates
    4. The design reduces unnecessary pressure on students
    5. Some of the credit prepares students for graded credit instead of it all being graded
    6. There are lots of personalisation options
    7. There’s a much more meaningful degree transcript
    8. There’s more assessment choice
    9. There’s less pressure to get students through at top speed
    10. There’s less high-stakes assessment in general
    11. There are “millions” of potential (what we would call) “programmes” without the coordination overhead, walled gardens and spoonfeeding of (what we would call) programmes
    12. There’s less traditional academic “teaching” going on here, but what there is is more efficient and more straightfoward

    Crucially, lots of the modules I’ve seen are from research-active academics – whose research area probably wouldn’t sustain a whole “programme” in our systems – but whose little chunk of credit sits neatly and sustainably in this system.

    So what could my little GWR trip down that a Finnish rabbit hole all mean?

    First of all, if I was the higher education minister (haha) I’d require there to be no more than the number and titles of QAA’s subjects in its benchmark statements as the degrees on offer as a condition of access to the loan book.

    On the emerging unit of resource, it’s going to end up impossible to innovate if not – getting new programmes approved will always be based on what marketeers think will “sell” – and doing simplifying in this way would force more “choose your own adventure” without the overhead of running and marketing a “programme”. I also take the view that saying to a student on an Open Day that there will be quite a bit of elective choice – when everyone internally knows that a lot of the choice will have gone by the time the VR round is done and that student is in their third year – is pretty immoral (and almost certainly unlawful).

    In addition, I also suspect the “choose your own adventure within some parameters” approach would reduce some of the regret we see in the UK. Even if students enrol with a strong disciplinary orientation (partly because of the ridiculous specialisation we force onto students at Level 1-3), a topline reading of the Bristol “regret” research is that either during or after the degree, students clock how unhelpful the UK’s obsession with narrowing is. (There’s no equivalent “regret” question in the Finnish NSS, but lots of interesting stuff that suggests less regret nonetheless.)

    You’ll have seen that much of the credit is about what we might generically call study skills – via our Belong project, we have unpublished national polling evidence (that will be on the site soon) that suggests that in general, students often regard what is on offer in the UK as too generic, and when it’s optional and non-credit bearing, other demands on their time tend to win out. This appears to be a system that has solved some of that.

    The rattle through above, by the way, was me diving into a Philosophy degree – but even in subjects where we might usually expect to see a more programmatic approach via more compulsory modules, structures and weighting aren’t hugely dissimilar – here’s the generic Bachelor’s in Science, for example.

    Plenty of the “choice” on offer is about both a dissertation and extra credit in the run-up to said dissertation – where there isn’t teaching on the thing the student wants to study per se but students can access academics who might be research-active in that. And some of the other choice options are doubtless constrained by timetable – but that’s eased somewhat by some of the credit being acquired “centrally”, some in self-directed mode, and a maintenance system that allows the average duration to be over 3.5 years. Clash? Take it next semester.

    Ultimately what I’m struck by, though, is the simplicity of the whole thing – which is not obvious on first look. I’m not saying that it’s simple to design the study plan or to even visualise the whole degree (either by diving into the website or reading this account), but I am saying that a lot of the tasks carried out by students or academics are simpler – where the focus is on academic learning and development (with quite sophisticated pedagogical research, innovation and support) rather than endless assessment, complex degree algorithms and multiple agendas.

    To the extent to which you can see a graduate attributes framework here, it’s delivered via multiple types of credit acquisition, rather than every attribute being loaded into every fat module.

    What is, though, absolutely undeniable is that a Chemistry graduate in this system has done less… Chemistry. Maybe the Royal Society of Chemistry (and all of the other PSRBs) would have things to say about that. But they’re nonetheless demonstrably rounded graduates (without a lot of the rounding depending on inaccessible extracurriculars) – and in a mass system, how many Bachelors graduates all need as much Chemistry individually anyway?

    Put another way, if a dwindling number of students want to study just Chemistry, and this system sustains a large number of Chemistry modules that are available both to those who do and those and don’t, isn’t that better for society overall?

    Source link