Tag: Learning

  • Building a More Inclusive, Personalized Learning Environment

    Building a More Inclusive, Personalized Learning Environment

    In today’s higher education landscape, the idea that future students will need more academic support is far from a catchphrase—it reflects a profound shift in both student needs and faculty responsibilities.

    Over the past few decades, the demands on faculty have surged due to an increasing number of accommodation requests and the diverse challenges that students bring from their varied high school experiences and personal lives. Consequently, educators are now expected to deliver a more personalized and differentiated education than ever before.

    As the student population becomes increasingly diverse and faces new external pressures, traditional support models are proving inadequate. We must move beyond reactive accommodations and embrace a comprehensive, tailored and proactive system of academic support. This transformation is essential for empowering both students and educators to thrive in an increasingly complex academic environment.

    Expanding Accommodation Needs

    One of the most noticeable changes in today’s academy is the sharp increase in the number of students requiring accommodations. As many as a quarter of my students have a registered disability, and the accommodations that I am required to provide have changed in significant ways post-pandemic.

    Previously, universal design principles were seen as adequate to ensure accessibility for all. Courses were retrofitted with extended deadlines, recorded lectures and online resources, providing a common platform without isolating individual needs.

    However, today’s reality demands a more nuanced and tailored approach. Accommodations now often involve significant modifications—such as flexible attendance policies, alternative assessment formats and even exemptions from standard class participation—that alter the very nature of the educational experience.

    These changes necessitate careful planning and ongoing communication between faculty, students and disability services to create a learning environment where every student can succeed. It also requires more training, resources and support for faculty and students—which hasn’t taken place.

    The Legacy of Uneven Educational Backgrounds

    Another key challenge arises from the uneven educational experiences that many students received in high school. Over the past several decades, the disparity in academic preparation has widened significantly. As a result, students now enter college with a much broader range of skills, background knowledge and even vocabulary than in previous generations.

    For some, high school provided a strong foundation, equipping them with the critical thinking skills and subject mastery necessary for the rigors of higher education. These students are well prepared to dive into complex course material and participate actively in academic discussions.

    In contrast, others come from educational environments where resources were limited or where the curriculum was less challenging. These students frequently struggle to meet the high standards expected at the collegiate level, finding themselves overwhelmed by the pace and depth of instruction.

    This variation in preparation places an additional burden on faculty, who must continuously adapt their teaching strategies to meet the needs of an unevenly prepared student body. In many classes, instructors face the daunting task of simultaneously engaging students who excel academically while also providing targeted support for those who are less prepared.

    This often means developing multiple instructional approaches, creating supplementary materials and offering additional feedback and tutoring sessions. Faculty must work diligently to ensure that every student has the opportunity to succeed, balancing the needs of advanced learners with those who require more foundational support.

    The challenge of uneven educational backgrounds underscores the critical need for a more flexible and individualized approach to teaching. Institutions must recognize this disparity and invest in innovative teaching methods, robust academic support services and ongoing faculty development. Only through such concerted efforts can educators ensure that all students, regardless of their starting point, are given the tools they need to thrive in college and beyond.

    Increasing Demands on Students’ Time

    Today’s students confront unprecedented pressures on their time. The demands of balancing work, extracurricular activities and family responsibilities have become an everyday reality, leaving many with significantly less time to devote to their studies. This predicament is not merely an inconvenience—it directly affects students’ academic performance and well-being.

    One of the most critical challenges is that these competing demands can hinder students’ ability to engage fully with challenging course material. I expect my students to tackle lengthy, demanding texts that demand deep concentration and sustained effort. When students are pressed for time, they often resort to skimming or incomplete reading, which can lead to gaps in understanding and ultimately a shortfall in academic achievement.

    This phenomenon not only compromises the quality of their learning but also contributes to a broader pattern of stress and burnout. The cumulative effects of these pressures can have long-lasting impacts on both academic performance and overall mental health.

    Given these realities, it is incumbent upon faculty to recognize the multiple challenges faced by today’s students. Traditional teaching methods and rigid assessment schedules may no longer be effective or equitable. Instead, educators must explore flexible teaching methods and alternative assessment strategies that allow students to manage their time more effectively.

    For example, integrating online discussion or tutoring sessions, offering modular coursework and incorporating a mix of formative assessments can provide students with the flexibility they need to engage with the material at their own pace. Such approaches not only accommodate the varied schedules of modern students but also help maintain academic integrity by ensuring that learning outcomes are met without forcing students to sacrifice quality for convenience.

    Adapting teaching strategies to reflect the realities of modern student life is not just a matter of convenience—it is a necessity for fostering academic success and reducing stress. By creating more flexible, responsive learning environments, faculty can help students overcome the challenges of time management and ensure that they have the resources needed to thrive both academically and personally.

    This rethinking of academic support is essential in an environment where the well-being of students must remain at the heart of the educational experience.

    Cultural and Socioeconomic Diversity

    Higher education’s student body is more diverse than ever, encompassing a wide range of cultural, linguistic and socioeconomic backgrounds. This diversity enriches the academic environment, infusing classrooms with a wealth of perspectives and experiences. However, it also brings significant challenges, particularly when it comes to addressing varied perspectives on identity, language and values.

    In today’s classrooms, educators are tasked not only with delivering academic content but also with navigating a complex array of social sensitivities and assertive demands for cultural responsiveness.

    One emerging trend is that many students have become increasingly sensitive about their peers’ feelings. They are cautious about expressing opinions that might inadvertently harm or offend, reflecting a heightened awareness of diversity and the impact of language on identity. They worry about appearing stupid or out of touch. This sensitivity, while rooted in a genuine desire for inclusivity, can lead to self-censorship in discussions and a reluctance to engage in the robust debates that have long been a hallmark of academic inquiry.

    In contrast, another segment of the student population is more assertive and less deferential than in the past. These students actively demand that the curriculum reflects their interests and addresses the realities of their lives. They expect academic content to be culturally responsive—incorporating diverse voices and challenging traditional perspectives. This shift in attitude is not merely about political correctness; it is about ensuring that the educational experience is relevant and reflective of the complex, diverse, globalized world in which they live.

    To meet these evolving needs, courses must be designed with a keen awareness of these differences. Faculty must create learning environments that are both safe and intellectually challenging, where discussions are inclusive yet rigorous and where students feel empowered to express themselves without fear of causing unintended harm.

    This requires a deliberate shift in curriculum design and pedagogical approaches. Educators must become facilitators of cultural dialogue, employing strategies such as structured debates, reflective exercises and collaborative projects that allow students to explore multiple perspectives. In doing so, instructors not only address academic objectives but also help students develop the critical communication skills needed to advocate for themselves and engage in meaningful discourse.

    Moreover, institutions must invest in professional development for faculty, ensuring that they are well equipped to navigate these complexities. Workshops on culturally responsive teaching and conflict resolution can provide valuable tools for managing sensitive discussions and balancing diverse viewpoints. By integrating these practices into everyday teaching, universities can foster a dynamic academic community that respects individual differences while promoting shared learning.

    The challenges posed by a more sensitive yet assertive student body underscore the need for a broader rethinking of the educational experience. True academic support must be proactive and individualized—transcending one-size-fits-all accommodations to embrace a model that is responsive to the unique needs and cultural contexts of each student. This holistic approach not only enhances academic performance but also enriches the overall learning environment, creating a space where every student can thrive.

    Rethinking Course Design

    In the past, courses were often structured around a standardized curriculum intended to serve a homogeneous student body. Universal design for learning provided a foundation for making courses accessible, yet it was designed as a one-size-fits-all solution. Today, however, students enter higher education with vastly different backgrounds, learning styles and personal challenges. These differences demand a more nuanced approach. Faculty must now consider how to build courses that not only accommodate diverse needs but actively build on each student’s unique strengths.

    This involves reimagining traditional assignments and assessments to allow for multiple avenues of expression—whether through essays, presentations, projects or creative multimedia formats—ensuring that mastery of the subject matter is measured in ways that align with individual capabilities.

    Faculty as Facilitators of Inclusive Learning

    To implement these changes effectively, educators must transition from being mere transmitters of information to becoming facilitators of a dynamic, inclusive learning environment. This shift requires faculty to develop new skills and adopt innovative teaching strategies that go beyond conventional lectures.

    For instance, incorporating collaborative learning methods, peer mentoring and structured feedback sessions can help create a classroom culture where students feel empowered to engage with the material and with one another. Such methods not only support individual learning journeys but also foster a sense of community and shared responsibility for academic success.

    Beyond Reactive Disability Accommodations

    One of the most glaring weaknesses in current disability policies at many colleges, including mine, is their failure to equip students with the practical skills and resources necessary for long-term academic success.

    While accommodations—such as extended deadlines, modified attendance requirements or alternative assessment methods—are undoubtedly important, they often function as a one-way street. Disability centers, overwhelmed by demand and constrained by limited resources, focus primarily on implementing reactive measures rather than providing proactive, skill-building support.

    This approach leaves many students without the essential tools they need to navigate the rigors of higher education independently. For instance, while accommodations may allow a student to attend class remotely or receive extra time on exams, they rarely come with training in self-advocacy. Students who struggle to articulate their needs or negotiate further modifications remain at a disadvantage, potentially compromising their academic performance.

    Similarly, critical skills such as effective study techniques, note taking and time management are often overlooked. Without guidance in these areas, students may continue to face obstacles that hinder their ability to fully engage with course material and meet academic expectations.

    The result is a support system that, while well intentioned, treats accommodations as the end point rather than the beginning of a broader educational strategy. True academic support should empower students to develop self-reliance and resilience, ensuring that they are not merely recipients of modified policies but active participants in their own learning journeys.

    This requires a fundamental shift from a model that simply reacts to student needs toward one that proactively builds the skills necessary for lifelong success.

    In order to address this critical shortfall, institutions must invest in comprehensive support programs that extend beyond traditional accommodations. Workshops on self-advocacy, time management and effective study habits should be integrated into the academic framework.

    Moreover, disability centers need to establish stronger partnerships with academic departments to create a seamless support network that bridges the gap between accommodations and skill development. Only by adopting a holistic approach can colleges ensure that students with disabilities are not just surviving within the academic system, but truly thriving.

    The Need for Ongoing Professional Development

    One of the biggest challenges is that most faculty members were neither expected to learn nor trained in these inclusive teaching practices. The rapidly evolving educational landscape demands continuous professional development. Institutions must invest in workshops, seminars and training programs that equip faculty with the latest strategies in inclusive pedagogy and collaborative teaching.

    By learning to use new digital tools and adapting to flexible teaching methods, educators can better address the wide range of learner needs. Ongoing training is crucial for fostering an environment where faculty feel supported and empowered to experiment with innovative teaching practices without compromising academic rigor.

    Faculty members face mounting pressure to adapt to new teaching methodologies, technological advancements and evolving accommodation practices. While universities routinely mandate training on issues like conflicts of interest, Title VI and IX compliance and technology risks, support in the core areas of pedagogy and assessment remains minimal. To address this gap, institutions must invest in comprehensive, ongoing in-service training for faculty. This training should cover inclusive teaching practices, innovative assessment strategies and the effective integration of digital tools into the classroom.

    Moreover, faculty should have continuous access to expert guidance and peer support. Dedicated centers for teaching excellence or mentoring programs need to offer real-time assistance, enabling instructors to navigate challenges as they arise. By fostering a culture of professional development and collaboration, universities can empower educators to experiment with new approaches and refine their methods over time—ensuring that teaching remains both rigorous and responsive to the diverse needs of modern students.

    A Call for a Comprehensive Reimagining

    The current model of academic support—with its patchwork of reactive accommodations and sporadic training sessions—is no longer sufficient to address the evolving challenges facing both faculty and students. The demands of modern higher education have shifted dramatically, requiring more than temporary fixes; they demand a radical reimagining of the educational experience that is individualized, personalized and differentiated to meet the unique needs of every member of the academic community.

    At the heart of this transformation lies a fundamental shift in institutional priorities. Universities must reallocate resources toward continuous professional development for educators and establish robust support systems for students. This means creating structured, ongoing training programs that equip faculty with the latest inclusive teaching strategies and digital tools, enabling them to adapt their methods to the diverse learning styles and backgrounds of today’s students.

    Such an investment not only enhances academic performance but also cultivates the critical skills and self-advocacy that are essential for lifelong success.

    Moreover, we must move beyond the reactive, one-size-fits-all accommodations that have characterized the past. Instead, academic support should be integrated into every aspect of teaching and learning, forming the backbone of a dynamic and responsive educational ecosystem.

    For example, early intervention strategies, such as formative assessments and iterative feedback, ensure that learning gaps are addressed before they widen and personalized learning plans can be developed to build on each student’s unique strengths.

    The benefits of such a comprehensive approach are twofold. First, it supports academic success by creating an inclusive learning environment that is adaptable to the individual needs of each student. Second, it alleviates the burden on faculty, who currently face the daunting task of juggling research, administrative duties and the increasing diversity of student needs.

    By establishing a framework of proactive support, institutions can empower both educators and learners to thrive in a challenging, rapidly shifting academic landscape.

    As higher education continues to evolve, so too must our strategies for academic support. The traditional model of reactive accommodations and ad hoc training is no longer adequate in the face of growing student diversity, uneven preparation and heightened external pressures on students’ time.

    Only by embracing a comprehensive, proactive and flexible approach can we ensure that every student—and every educator—is equipped to navigate the complexities of modern academic life.

    This reimagined support system will not only boost academic performance but also enrich the overall educational experience, fostering a vibrant, inclusive and resilient community that is prepared to meet the challenges of the future.

    In an era of tightening institutional finances and overburdened faculty, the shift toward a more individualized approach to education may seem like an overwhelming challenge. However, this shift is not optional—it is both a legal requirement and an essential strategy for improving student retention, graduation rates and postgraduation outcomes.

    As student populations become increasingly diverse and face complex external pressures, campuses must prioritize academic and faculty support to create a learning environment where every student can thrive.

    The Legal Mandate for Individualized Support

    Legislation such as the Americans with Disabilities Act and Section 504 of the Rehabilitation Act mandate that institutions provide equal access to education for all students. These legal frameworks require not only reactive accommodations but also proactive, individualized support that anticipates and addresses the diverse needs of the student body.

    In practice, this means that colleges and universities must design courses, develop teaching methods and implement support systems that are flexible and tailored to individual learning styles. Ignoring this mandate not only risks legal repercussions but also undermines the institution’s commitment to inclusivity and equal opportunity.

    Enhancing Academic Success and Student Outcomes

    In addition, the current challenges faced by students—ranging from increased accommodation needs and uneven educational backgrounds to intense time pressures and cultural diversity—demand more than a one-size-fits-all solution.

    When students receive personalized academic support, retention and graduation rates improve significantly. Tailored support enables students to engage deeply with course material, develop critical skills and ultimately achieve better postgraduation outcomes. By creating a comprehensive support system, institutions can help bridge the gap between diverse student needs and the rigorous demands of higher education, ensuring that every student has the opportunity to succeed.

    The Burden on Faculty and the Need to Rethink Institutional Priorities

    For faculty, the shift to an individualized educational model requires a significant rethinking of traditional teaching methods.

    Instructors must balance the needs of advanced learners with those requiring additional support, all while managing other academic responsibilities such as research and grant writing. This challenge is compounded by the lack of sufficient training and resources currently available to help educators implement inclusive teaching practices. Institutions must respond by reallocating resources and prioritizing continuous professional development.

    Only by providing faculty with the necessary tools and support can universities foster a dynamic, responsive learning environment that benefits both teachers and students.

    The move toward a more individualized, personalized and differentiated approach to education is no longer a luxury—it is a legal and institutional imperative. As student needs evolve in a rapidly changing world, institutions must reframe academic support as a core element of the educational experience.

    By prioritizing continuous faculty training, investing in robust support systems and rethinking course design, colleges and universities can enhance academic performance, improve student retention and graduation rates and ensure better outcomes after graduation.

    There is no way around this transformation: If we are to equip every student and educator to thrive in an increasingly complex academic environment, the shift to a comprehensive, proactive and flexible support model must become the cornerstone of higher education.

    Steven Mintz is professor of history at the University of Texas at Austin and recipient of the AAC&U’s 2025 President’s Award for Outstanding Contributions to Liberal Education.

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  • 5 online resources to beat the summer slide

    5 online resources to beat the summer slide

    Key points:

    As the final school bells ring and students head into summer vacation, educators and parents alike are turning their attention to the phenomenon known as the summer slide–the learning loss that can occur when children take a long break from structured academic activity.

    NWEA research notes that students can lose up to two months of math skills over the summer, and reading abilities can also decline, particularly for students from underserved communities.

    But the summer slide isn’t inevitable. With the growing availability of engaging, high-quality online learning tools, students have more opportunities than ever to keep their skills sharp. These tools offer interactive lessons, personalized learning paths, and fun activities that reinforce what students learned during the school year–without making summer feel like school.

    Here are five standout online resources designed to help K-12 students stay on track over the summer months:

    1. Khan Academy: Khan Academy’s free online platform offers comprehensive lessons in math, science, history, and more. Its summer learning programs provide structured plans for students in grades K-12, including daily activities tailored by grade level. Each lesson includes short instructional videos, interactive quizzes, and mastery challenges. For students who want to get ahead or reinforce tricky concepts from the previous school year, Khan Academy is an ideal, self-paced resource.

    Khan Kids, a separate app for younger learners (ages 2-8), combines educational videos, stories, and games that focus on early literacy, math, and social-emotional development.

    2. PBS LearningMedia: PBS LearningMedia curates thousands of free videos, lesson plans, and interactive activities aligned to state and national standards. The content is engaging and age-appropriate, drawing from trusted PBS programs like Wild Kratts, NOVA, and Peg + Cat. During the summer, PBS typically offers special themed weeks–like “Summer of Reading” or “Science Week”–featuring playlists and activity bundles to help children stay curious and engaged.

    For younger children, PBS Kids also provides games and shows that reinforce foundational skills in reading, math, and critical thinking.

    3. ReadWorks: Reading skills are among the most vulnerable to decline during the summer, especially for students who do not have regular access to books or structured reading activities. ReadWorks is a nonprofit platform offering free, research-based reading comprehension materials for grades K-12. Teachers and parents can assign grade-level texts, paired with vocabulary lessons and comprehension questions. The platform also features an Article-A-Day challenge that encourages students to build background knowledge and reading stamina with just 10 minutes a day. ReadWorks is especially helpful for English Language Learners, offering audio versions and question supports to aid comprehension.

    4. Prodigy: For students who struggle to stay motivated during math practice, Prodigy turns learning into a role-playing adventure game. Students solve math problems to earn rewards and level up characters, making the experience both educational and fun. Aligned with state standards and suitable for grades 1-8, Prodigy adapts to each learner’s skill level, offering targeted practice without the pressure of grades or tests. Parents can access dashboards to track progress and set goals over the summer. Prodigy also offers a version for English Language Arts, expanding the platform’s reach beyond numbers.

    5. Smithsonian Learning Lab: For families looking to incorporate cross-curricular learning, the Smithsonian Learning Lab provides a treasure trove of multimedia collections that blend history, science, art, and culture. Students can explore virtual exhibits, complete inquiry-based lessons, and create their own digital portfolios. The platform is well-suited for middle and high school students, especially those interested in project-based learning and critical thinking. Whether studying the Civil Rights Movement or learning about ecosystems, students can explore real artifacts, images, and primary sources from the Smithsonian’s vast collection.

    Keeping minds active and curious

    Experts emphasize that summer learning doesn’t need to mirror the structure of the traditional classroom–keeping students intellectually engaged as they explore their personal interests reinforces academic skills in an low-stress environment.

    Families can also incorporate daily routines that promote learning–reading together before bed, practicing math while cooking, or exploring nature to spark scientific curiosity.

    As the digital learning landscape expands, there are more tools than ever to support students year-round. With just 20-30 minutes of meaningful academic engagement each day, students can maintain their momentum and return to the classroom in the fall ready to learn.

    Laura Ascione
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  • For Learning, Focus on the Essence and the Experiences

    For Learning, Focus on the Essence and the Experiences

    When I was teaching, I always thought of this time on the calendar as the “postexhale” period.

    The end of the semester is a headlong sprint to the finish, which, unlike a race where you get to break the tape and coast to a stop, is more like hitting a wall and collapsing on the spot. At least that’s how it always felt to me, at least until I started ending the semester at week 13 (of 15) and using the last two weeks for wind-down and reflection on what we’d all learned.

    In the immediate aftermath of the semester, particularly spring semester, I couldn’t be bothered with any thinking or planning for the next semester. The next scheduled activity, usually something I started around the first week of August, would be the specific planning for the forthcoming semester, but there is also this postexhale period where no work needs to be done, conditions that are fertile for thinking and dreaming before the planning.

    The postexhale period is the spot where you’re likely to gestate your best ideas, because at least for the next month or so, you don’t have to do anything with them.

    I want to plant a seed of thought for anyone who is confronting having to or wanting to make changes to their course in order to accommodate the reality of generative AI technology being in the world.

    Here it is: Next semester, do less that means more.

    As I’ve been traveling around talking to people about how we can (and should) adjust how we think about teaching writing, one of the persistent worries is that introducing some AI-related content or experiences around ethics or safe use or whatever requires layering something new on what’s already happening. For many instructors, it’s an uninvited and therefore unwelcome burden.

    I get it. We can never cover everything to begin with. Here’s one more thing to cover.

    But what if we can use this as an opportunity to rethink what learning looks like? As we move through this period where we can reflect and reconsider, we can think about how to boil the experiences in the classroom down to an essence that can be reflected in learning experiences.

    Consider the learning that has proved most enduring from the full trajectory of your education and I think you’ll find that it clusters around essential, deep lessons. What has mattered are the moments where we have learned how to learn and think and act inside a particular domain. It is this learning that allows us to go forth and continue to learn eagerly, ceaselessly.

    Even as a decidedly and well-documented overall mediocre student, there are numerous learning experiences (in and out of class) that I can point to as inflection points that made a significant difference in the overall trajectory of my life because they provided something essential to my journey forward.

    One moment I invoke frequently is when my third-grade teacher asked us to write instructions for making a peanut butter and jelly sandwich and then had us try to make the sandwiches following the instructions to the letter. Because I forgot to say that you should use a knife to spread the peanut butter on the bread, I ended up sticking my hand in the jar of peanut butter to fulfill my own directive. I have a picture memorializing the occasion.

    That moment introduced me to the rhetorical situation and the fact that writing has a purpose and an audience—and careless writing has consequences. I’m sure I learned all kinds of other things in third grade and maybe some of them were important, but only one moment was indelible, and that’s all I needed.

    In high school, excited about the subject matter for my junior-year English term paper (the New Journalism of Tom Wolfe), while being not enthused about the parameters of what I was supposed to do with that subject matter, I decided to write my term paper in the style of Tom Wolfe, earning a not-so-great grade from my teacher, but a meaningful lesson in how to keep myself interested with a task. (I wrote in more detail about this previously.)

    Some reflection unearths other moments. A college nonfiction writing class had us pretending we were writing for specific publications and producing columns that could fit under the editorial banner. I chose Esquire, imagining myself a sophisticated male, I guess. We were required to understand how to write for very specific audiences with very specific aims, excellent practice for all kinds of different futures. At the end of the semester, we had a competition where we voted for the “best” columns across a number of different categories. I was a finalist in several but won zero, losing out to one specific classmate’s work every time.

    In a conference with the instructor, I must’ve expressed some kind of disappointment, and he said something that stuck with me: “X’s stuff sounds like themselves writing for a publication. You sound like someone doing an imitation of someone writing for a publication.” I walked away believing that authenticity was ultimately the differentiator in connecting with readers.

    I could name more moments. My first semester of grad school, my professor, Robert Olen Butler, had us do an in-class writing exercise based in sense memory (which can be found in his book From Where You Dream), and I experienced what it was like to tap into my artistic subconscious for an extended, focused period. Bob was not the most engaged of mentors, but I’m not sure I’d still be writing if I hadn’t had that experience.

    When I started teaching, the indelible lessons delivered by my students came even more often, possibly because I recognized my responsibility over the work in ways I hadn’t achieved as a student.

    All these moments are rooted in very specific and specifically designed experiences. These kinds of experiences are not threatened by the existence of large language models, because it was clear to me that the point of the exercise is to have the experience.

    Of course, generative AI tools could be present as part of an important learning experience, but when generative AI is used by students as a substitute for the experience, the learning is obviously deformed. Injecting LLMs into our courses simply because it seems like something we have to be doing is not a great recipe for learning.

    There are some, perhaps many, places where it is not and should not be welcome because it is not conducive to the experience of learning we’re trying to instantiate.

    As I think about these experiences, what I learned was really contained in a crystallizing moment made possible by the earlier experience of that class, or even before that class. This is not necessarily predicated on the amount of material covered or the volume of what students are exposed to.

    As you enjoy this exhale period, maybe spend some time thinking how little you could do in your course and still have students walk away with something that will be meaningful years down the road. That may be the core of your course when you come back and start thinking about it for real in a month.

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  • 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.”

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  • Flexible Learning and Policy Challenges

    Flexible Learning and Policy Challenges

    What impact is flexible learning having on learners from K-12 through to professional development?

    New Zealand has remarkably high levels of digital access across the population. Why aren’t we out performing other countries in educational measurements?

    This piece serves to introduce a series of six challenges faced by policy makers around flexible learning.

    These six challenges are:

    1. Unequal Access to Technology and Connectivity
    2. Socioeconomic Disparities
    3. Digital Literacy and Skills Gaps
    4. Quality Assurance and Consistent Experience
    5. Teacher Preparedness and Support
    6. Policy and Funding Models

    In this first piece I want to establish what I mean by ‘flexible learning’.

    Like many I struggle to have a single, concise, and consistent “definition” of flexible learning. I would say that flexible learning is a model of delivery that offers learners agency and control over various aspects of their learning experience. Flexible learning is a spectrum. Formal learning courses exist on a continuum between “rigid” and “flexible” delivery. The more control and choice given to the learner, the more flexible the learning experience.

    Flexible learning aims to “empower the student to choose what learning should be studied face-to-face and that which should be studied online, and how to go about engaging with that learning” (2022). This Means empowering the learner to make choices regarding:

    • When: synchronous or asynchronous learning, pace-mandated or self-paced progression.
    • Where: Learning in different locations (home, campus, workplace, etc.).
    • How: Different modes of engagement (online, in-person, blended, hybrid, hyflex).
    • What: Some degree of choice over content or learning pathways, though this is often more associated with “open learning.” Indeed in a world where students are overwhelmed with choices, there are strong arguments that having a prescriptive programme serves students well.

    In my article “Definitions of the Terms Open, Distance, and Flexible in the Context of Formal and Non-Formal Learning,” (2023) I argued that flexible learning is a model of delivery, rather than a fundamental mode of learning. I posit that there are only two core modes of learning: in-person (or face-to-face) and distance learning. Flexible learning then emerges from various combinations and approaches to curriculum design that empower learners to choose amongst these two modes

    As education has a habit of inventing new terms for marginally different practices it might be worth just pointing out the relationship I think exists between flexible learning and forms of Blended, Hybrid, and HyFlex learning. I perceive blended, hybrid, and HyFlex learning as specific models of delivery that fall under the umbrella of flexible learning. They all aim to give agency to the learner regarding how they engage with the material, combining elements of in-person and distance learning.

    I believe that designing for flexible learning means considering the learner’s context and perspective, and creating learning experiences that are relevant, meaningful, motivating, realistic, and feasible within an agreed timeframe. This also involves careful consideration of learning outcomes and assessment in diverse delivery contexts. This means course creators need clarity about learning design principles in relation to flexible approaches, such as working with Notional Study Hours (2020a) and the importance of Learning Outcomes (2020b).

    Based on my broad definition thatFlexible Learning refers to educational approaches and models of delivery that provide learners with a significant degree of choice and control over the time, place, pace, and mode of their learning, leveraging combinations of in-person and distance learning to enhance accessibility and cater to diverse learner needs, how do we face those six policy challenges?

    Watch this space…

    Atkinson, S. P. (2020a, April 14). Working with Notional Study Hours (NSH) or “How much is enough?” Simon Paul Atkinson. https://sijen.com/2020/04/14/working-with-notional-study-hours-nsh-or-how-much-is-enough/

    Atkinson, S. P. (2020b, April 4). Designing Courses: Importance of Learning Outcomes. Simon Paul Atkinson. https://sijen.com/2020/04/04/designing-courses-importance-of-learning-outcomes/

    Atkinson, S. P. (2022a, July 15). How do you define hybrid, or hyflex, learning?. Simon Paul Atkinson. Retrieved from https://sijen.com/2022/07/15/how-do-you-define-hybrid-or-hyflex-learning/

    Atkinson, S. P. (2023). Definitions of the Terms Open, Distance, and Flexible in the Context of Formal and Non-Formal Learning. Journal of Open, Flexible, and Distance Learning, 26(2).3 Retrieved from https://jofdl.nz/index.php/JOFDL/article/view/521

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  • 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.

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  • Transforming Higher Ed With Virtual-Hybrid Learning

    Transforming Higher Ed With Virtual-Hybrid Learning

    Reading Time: 3 minutes

    Higher education is evolving and, as someone deeply involved in curriculum development, I have witnessed firsthand how virtual-hybrid delivery models can transform learning experiences. When the COVID-19 pandemic necessitated a sudden shift in instructional methods, I had to reconsider how to deliver my senior-level undergraduate Entrepreneurial Thinking and Innovation course, which was traditionally taught face-to-face (F2F). What started as a necessary adaptation quickly became an opportunity to enhance student engagement, flexibility, and real-world preparedness. I now recognize that virtual-hybrid delivery is not merely a temporary fix, but a sustainable and highly effective model for the future of education across disciplines.

    From face-to-face to virtual-hybrid learning

    My Entrepreneurial Thinking and Innovation course was originally designed around a hands-on, project-based learning (PBL) approach. At the course’s core was a semester-long, stage-gated Business Case, or BizCase Project. Student teams tackled real-world business challenges by developing comprehensive business cases for community organizations. Traditionally, this involved in-person collaboration, real-time feedback, and instructor-led sessions.

    When we shifted to online learning, my primary challenge was to preserve the course’s interactive and applied nature, while using digital tools to maintain engagement. Rather than attempting to replicate the in-person experience, I completely reimagined the learning process.

    The revamped course focused on three key elements:

    1. Synchronous Milestone Meetings: Structured biweekly sessions replaced traditional lectures, enabling real-time, small-group discussions that fostered deeper engagement and tailored feedback.
    2. High-Quality Asynchronous Instructional Videos: Professionally produced and concise video lessons allowed students to learn independently, enhancing accessibility and comprehension.
    3. Customized Screencast Feedback: Instead of written comments, students received comprehensive, personalized video feedback, enhancing the evaluation process to be more interactive and engaging.

    Why virtual-hybrid learning works

    The impact of this redesign was immediate and profound. Not only did students stay engaged, but their learning outcomes improved significantly. The average final grades on the BizCase Project increased by 8-10% compared to previous face-to-face cohorts. Here’s why this delivery model is so effective:

    1. Enhanced Student Engagement

    One of the most significant advantages of virtual-hybrid learning is the combination of structured flexibility and active engagement. Traditional lecture formats often lead to passive learning. The virtual-hybrid approach inspires students to take charge of their educational journey, thereby enhancing learner agency.

    Synchronous milestone meetings ensured students remained accountable and on track, while asynchronous videos allowed them to review content at their own pace. Many students observed that revisiting instructional videos before project discussions greatly boosted their comprehension and confidence.

    1. Real-World Preparation

    Virtual-hybrid delivery reflects the realities of modern workplaces, where professionals are increasingly engaged in hybrid and remote work environments. By embracing this model, students acquire academic knowledge while developing essential skills in virtual collaboration, digital communication, and self-directed learning.

    The course redesign was based on industry research regarding optimal meeting structures, which indicates that smaller, focused discussions promote greater engagement and enhance problem-solving. I implemented smaller team-based milestone meetings instead of large, passive online lectures, ensuring each student actively participated. This change aligns with corporate best practices. It equips students with skills that are directly transferable to contemporary work environments.

    1. More Effective Feedback

    One of the most significant innovations in this course redesign was using screencast technology for project feedback. Rather than traditional written comments, students received comprehensive, video feedback. I guided them through their submissions, emphasizing strengths and areas for improvement. Students overwhelmingly preferred this method, with 90% indicating that video feedback was clearer and more personal than written comments. The combination of seeing and hearing the feedback, along with visual annotations, created a more interactive and engaging learning experience, making it easier for students to refine their work.

    Challenges and opportunities

    While virtual-hybrid learning offers significant benefits, it also presents challenges. Although students appreciated the flexibility of self-paced videos, some struggled with motivation and time management in effectively navigating the course requirements.

    Another challenge is ensuring equitable access to technology. Not all students have access to high-quality devices or reliable internet connections. This can affect their ability to engage fully in virtual-hybrid courses. Institutions must invest in digital infrastructure and support systems to ensure all students can participate effectively.

    Applying virtual-hybrid models across disciplines

    Although this article focuses on an entrepreneurship and innovation course, the principles of virtual-hybrid learning can be applied to various disciplines. This model can benefit any course, including experiential learning, teamwork, and applied projects.

    • Engineering courses can incorporate virtual design labs, simulation software, and milestone meetings for project-based assessments.
    • Medical and healthcare programs can integrate asynchronous case studies with live virtual discussions on clinical applications.
    • Humanities and social sciences can include digital storytelling, virtual peer feedback collaboration, and instructor-led discussions.

    A new era of learning

    The success of the virtual-hybrid delivery model in Entrepreneurial Thinking and Innovation underscores its remarkable potential. The one-size-fits-all, lecture-heavy educational approach is becoming obsolete. Today’s students thrive in dynamic, technology-enhanced environments that prepare them for hybrid workplaces and the future of work.

    As educators, we have both an opportunity and a responsibility to rethink traditional teaching methods. Virtual-hybrid delivery presents a path forward for a more adaptable and impactful education. Having experienced the transformative effects of this approach firsthand, I can confidently assert that virtual-hybrid delivery can be a game changer for the future of higher education.

    Learn more about how hybrid-virtual learning fosters engagement and critical thinking by watching Professor MacKenzie’s webinar, part of our 2025 Empowered Educator Virtual Conference.

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  • How we designed a space where our students connect, collaborate, and flourish

    How we designed a space where our students connect, collaborate, and flourish

    Key points:

    Our charter school, Westbrook Academy, has been serving middle and high school students in the South Los Angeles area for the past six years and stands as a beacon of opportunity for our community. With a student body comprising nearly 99 percent Black and Latinx individuals hailing from historically under-resourced communities, we confront the realities of poverty and the accompanying insecurities head-on.

    Despite the odds, our 400 students consistently demonstrate remarkable resilience and a profound capacity for excellence. Our institution is supported by generous donors and funding sources. Operated and managed by the education nonprofit LA Promise Fund, which provides students with academic and enrichment opportunities that support our mission to spark passion, empower leadership, and prepare them for their chosen college and career paths.

    At one point, our high school students were learning in a church because we didn’t have a traditional classroom set-up. We also lacked the equipment that a traditional high school might have. This changed when we moved into our forever home in South Gate, where an on-campus Empowerment Center serves as a modern, welcoming “student hub.”

    Designed and outfitted by MiEN and Meteor Education, the Empowerment Center is where kids go to hang out, collaborate, and/or participate in school club activities. The hub is also set up with two wellness rooms where students can go to debrief and disconnect from a long day or just the stresses of being a student. It’s there for the students’ use.

    Here are the steps we took to create a space that consistently makes jaws drop and impresses parents who never thought their children would have access to such a warm, welcoming communal space on campus:

    • Add some flexibility into the process. Our original goal was to open the Empowerment Center’s doors in time for the 2023-24 school year, but getting it done the right way would require a bit more time. Our partners were willing to listen to us in terms of what we wanted to create, but within the realistic timelines. That was really cool.
    • Acknowledge the financial limitations. We largely relied on fundraising for this project and knew that some things just weren’t going to be realistic. To other schools in similar situations, I’d recommend staying flexible enough to hit the timelines and get all of the bases covered while keeping student needs in mind. We can have all the bells and whistles, but at the end of the day, if the car runs, the car runs. We know we can always add a new paint job later.
    • Get the right partners onboard early. As we went through the steps of designing the Empowerment Center, we learned a lot about architecture, planning, and construction. Through it all, having the right partners in its corner helped the school achieve its goals within budget and on time. It was really great to have our design and furniture partners sharing their best practices and other insights with us. We knew what we wanted to do, and a lot of the ideas came from our families and students. We just needed them to show us how we could get those ideas as close to reality as possible.
    • Make it personal. Special features we wanted in our Empowerment Center included a huge, interactive flatscreen TV that students, teachers, and guest speakers use to interact and work together. There’s also a large selection of donated books, the latest technology tools, and artwork that was personally selected by an art curation team. They were able to secure artists from the LA community to create and share visuals that our students are really familiar with. For example, some of the artwork spotlights female empowerment (i.e., with photos of authors like Octavia Butler) and the importance of acknowledging indigenous people. Everything in the hub is meant to spark curiosity. 
    • Brace yourself for some jaw-dropping moments. At our ribbon-cutting ceremony last year, our parents’ jaws were on the floor. They just never thought these resources would be available to their kids. A lot of them grew with us being in the church and a co-located space, and then we asked them to trust us to deliver on our promise, and now we’re able to show that as the reward for supporting us. We feel really proud that our parents were just over the moon about it.

    Hitting it out of the park

    Reflecting on the process we put in place to get our modern student hub designed, built, and open for business, I can say that the end result is an engaging, collaborative space that can be used for hanging out, structured learning, or a little of both. I think we really hit the ball out of the park with this innovative space.

    Student, teacher, and family feedback on the Empowerment Center has been extremely positive. Everyone loves it, and students are always excited to come and spend time in the modern, comfortable space that’s equipped with the technology and tools they need to be able to learn and engage.

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  • If memory is the residue of thought, what are we learning from AI?

    If memory is the residue of thought, what are we learning from AI?

    • This is an edited version of a speech given by Josh Freeman, HEPI Policy Manager, to the Cardiff University Biochemical Society Sponsored Seminar Series on AI.

    I want to start with a thought experiment – one that will be on familiar ground for many of us. A lecturer sets an assignment and receives two student essays which are very similar in argument, structure, originality and so on. The difference is that one student used AI and the other didn’t.

    The student who used AI used it, as more than half of students (51%) do, to save time. They knew what they wanted to say, wrote a bullet-pointed list, fed this into ChatGPT and asked it to generate an essay ‘in the style of a 2nd year Biosciences student’ – which is what we know that students are doing. Perhaps they added some finishing touches, like a bit of their own language.

    The second student wrote their essay the old-fashioned way – they wrote a plan, then turned that into a draft, redrafted it, tweaked it and manually wrote their references.

    The question is: Which essay should we value more? They are functionally the same essay – surely we should value them equally?

    I don’t mean which essay should get the higher mark, or whether the student who used AI was cheating. Let’s assume for the moment that what they did was within the rules for this particular course. What I mean is, which essay better shows the fulfilment of the core purposes of a university – instilling intellectual curiosity, critical thinking, personal development in our students?

    I think most of us would instinctively say that something has been lost for the student who used AI. We don’t value students as content creators. We don’t see the value in the essay for its own sake – after all, many of us have seen hundreds or thousands of similar essays in our time in academia. What we value is the process that got the student to that point. There is something fundamental about the writing process, that in the act of writing, you are forced to confront your own thoughts, express them, sit with them. You have to consider how far you really agree with them, or if there is something missing. Though the student who used AI produced the same end result, they didn’t have that same cognitive experience.

    AI is, for the first time, divorcing the output from much of the cognitive process required to get that output. Before AI, if a student submitted an essay, you could be relatively confident – barring the use of essay mills or plagiarism – that they had thought deeply, or at least substantially, about the output they submitted. The content was a good proxy for the process. But with AI, it’s remarkably easy to generate the content without engaging in the process.

    I was a teacher previously, and the mantra we were told again and again was ‘Memory is the residue of thought.’ (With credit to Daniel Willingham.) We remember what we think about. When you have to sit with an essay, or a difficult academic text, it fosters more learning because your brain is working harder. If you can fast-track the essay or just read a summary of the important bits of the text, you skip the work, but you also skip the learning.

    This is a problem for all kinds of reasons, some of which I’ll go into. But in another way, it may also be a good thing. For a long time, the focus has been on the content that students produce, as the best marker for a students’ skills and knowledge. But I hope that AI will force us to think deeply about what process we want students to go through.

    In the time I have left, I want to touch on a few issues raised by our recent survey, showing that the vast majority of students use generative AI, including to help with their assessments.

    The first is that the rabbit is out of the hat. Almost all students are using AI, for a rich variety of purposes, and almost certainly whether or not we tell them they can. That will be obvious to anyone who has received a coursework submission in the last 18 months, but it is so key that it is worth emphasising. Barring the withdrawal of large language models like ChatGPT from the internet (unlikely) or the mass socialisation of our students away from GenAI use (also unlikely, but less so), AI is here to stay.

    The second is that the system of academic assessment developed over decades or more is suddenly and catastrophically not fit for purpose. Again, this will be known to many but I am not sure the sector has fully grappled with the implications of it. All assessments had some level of insecurity, insofar as essay mills and contract cheating existed, but we have always felt these methods were used by relatively few students; we were also able to pass national legislation to crack down on these methods.

    AI is different for two reasons. The first is ease of use – the barriers of seeking out an essay mill and coughing up the money are gone (though it remains true that the most powerful AI models still have a cost). The second is how students reckon with the moral implications. It is clear to almost everyone, I think, that using an essay mill is breaking the rules, so students would usually only use these when they are truly desperate. But AI is different. We saw in the report that there great uncertainty when it comes to using AI – lots of disagreement about what is acceptable or not. When it’s cloudy in this way, it’s easier to justify to yourself that what you’re doing is okay. Most people won’t overtly ‘cheat’ but they might push on hazy boundaries if they can tell a story about why it is acceptable to do so.

    So all of our assessments need to be reviewed. I recently read an essay from UCL Law School, talking about how they will be using 50-100% ‘secure’ assessment, meaning in-person written or oral exams. This is a good start, though it may not even be enough if 50% of your assessments are ‘hackable’ by students with little or no subject knowledge or with no grasp of the skills you are meant to be teaching them. And I am not convinced that ‘secure’ exams are always such. If essay questions are predictable, you can easily use AI to generate some mock essays for you and memorise them, for example.

    This is also why the claims that AI will generate huge efficiency gains for the sector are misplaced, at least in the short term. In the coming years, AI will put huge strain on the sector. Essentially, we are asking all of our staff to be experts in AI tools, even as the tools themselves constantly update. For example, AI tools hallucinate a lot less than they used to and they also produce fake references much less often – and there are now specific tools designed to produce accurate references (such as ChatGPT’s Deep Research or Perplexity.AI). It is an open question as to whether this radical redrawing of assessment is a reasonable ask of the sector at a time when budgets are tight and cuts to staffing are widespread – up to 10,000 jobs lost by the end of the academic year, by some estimates.

    The third issue returns to the thought experiment I presented you with at the start. We will now be forced to think deeply about what skills we want our students to have in an age where AI tools are widely accessible, and then again about how we give our students those skills.

    Think again of those two essays, one of which used AI and one didn’t. There is an argument in favour of the AI-assisted essay if you particularly value teaching AI skills and you think getting AI to help with essays is one way to enhance those skills. But like developing AI-proof assessments, this is a moving target. Some people will remember the obsession with ‘prompt engineering’ in the early days of GenAI – carefully crafting prompts to manufacture very specific answers from chatbots, only for them to update and all that work becoming entirely useless? By virtue of being natural language models, they are frequently very intuitive to use and will only become more so. So it is not at all clear that even the best AI courses available now will be very useful a few years into students’ long and varied careers.

    The same problem applies to courses designed to teach students the limits of AI – such as bias, the use of data without permission, hallucinations, environmental degradation and other challenges which we are hearing lots about. Small innovations could mean, for example, that the environmental cost of AI falls dramatically. There is already some research saying a typical ChatGPT prompt may now use no more energy than a Google search. In a few years’ time, we may be dealing with a very different set of problems and students’ knowledge will be out of date.

    I can’t pretend HEPI has all the answers – though we do have many, and we require all of our publications to include policy solutions, which you are welcome to investigate yourselves on our website. But my view is that the skills students will receive from a university education – critical thinking, problem solving, working as a team, effective communication, resilience – are as critical as ever. In particular, we will probably need to hone in on those skills that AI cannot easily replicate – soft skills of motivating others or building trust, emotional intelligence, critical thinking, which will endure in importance even as AI automates other tasks.

    But the methods we use will need to change. We hear a lot from academics about the enormous administrative burden academics face, for example. In my view, the best case is that AI automates the boring bits of all our jobs – paperwork, producing lesson materials, generating data – and freeing us up to do what matters, which is producing innovative research and spending more time with students. That will make sure AI enhances, rather than threatens, the enormous benefits our degrees impart to students in the coming years.

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  • Learning Designer, Learning Technologist, Brown

    Learning Designer, Learning Technologist, Brown

    If there is anyone in higher education that you want to work with, that person is Melissa Kane. As director of online program development at Brown University, Melissa leads a talented team doing incredible work at the intersection of learning, technology and institutional change. You can learn more about Melissa and her professional and educational journey here. When I saw on LinkedIn that Melissa is recruiting for a learning designer and a learning technologist, I thought that these roles would be perfect to highlight in this “Featured Gig” series. 

    If you are also recruiting for an opportunity at the place where learning, technology and organizational change meet, please get in touch.

    Q: What is the mandate behind these roles? How do the roles align with and advance the university’s strategic priorities?

    A: Both the learning designer and the learning technologist positions are directly tied to Brown University’s strategic priority to diversify the master’s degree portfolio and significantly increase global impact through the expansion of online graduate degree programs. As higher education continues to evolve toward more flexible, human-centered and accessible learning modalities, Brown delivers on its mission by providing a uniquely Brown learning experience to a new demographic of working professionals and international learners who may require more geographical flexibility.

    Since this strategic initiative began in 2021, Brown has remained invested in its internal staff resources to partake in constructing and delivering its online master’s programs. Because of this, the learning designer and learning technologist positions are essential infrastructure investments that will enable us to continue delivering the same rigorous and innovative education that defines Brown through the online modality.

    The learning designer role advances our mission by ensuring that courses in our online master’s programs maintain Brown’s hallmark of academic excellence while leveraging evidence-based practices in fully asynchronous online learning experience design. Similarly, the learning technologist role has the opportunity to position us at the forefront of educational innovation by pioneering new approaches to implement existing and emerging learning technologies that can influence the ways we advance graduate student education.

    Both of these roles will be integral in helping Brown with its goal of enrolling and retaining new markets of graduate students while still maintaining our mission-driven commitment to deliver transformative, high-quality education in this evolving landscape.

    Q: Where do the roles sit within the university structure? How will the people in these roles engage with other units and leaders across campus?

    A: The learning designer and the learning technologist roles are strategically positioned within the Sheridan Center for Teaching and Learning, reporting through the Office of the Provost, which again reflects the university’s commitment to placing pedagogical excellence at the center of its online master’s degree expansion efforts. The Sheridan Center’s integrated approach makes it an ideal location for individuals in these positions to collaborate with other members of the university’s community, including the School of Professional Studies, the library and academic departments and schools. Because of our cross-campus partnerships to help deliver courses within the online graduate degree portfolio, we have the unique opportunity to enable consistent quality and pedagogical coherence across all online programs as we work with academic departments to draw on their unique disciplinary strengths and identities.

    Q: What would success look like in one year? Three years? Beyond?

    A: Our team’s success stems from deep human connections and the intellectual capital created through collaboration, trust and empathy with each other and our campus partners. In the first year, success is measured by the individual’s openness to creative thinking, empathetic cross-functional collaboration and inclusive practice in both their projects and interpersonal interactions. The learning designer will demonstrate fluency in digital pedagogies that are inclusive of global audiences at scale, while the learning technologist will continue to grow their technical knowledge and skills to meet diverse student learning needs through innovative, ethical and accessible educational technologies as the AI landscape changes.

    By year three and beyond, individuals in these roles will have evolved into thought leaders in learning experience innovation that is responsive and relevant to our ever-changing world. They will have established themselves as trusted collaborators with our campus partners, and their work will demonstrate measurable impact on student success and engagement in the graduate degree environment. Ultimately, I see individuals in these roles continuing to forge bridges between academic departments and inclusive online learning environments that reflect Brown’s commitment to academic excellence, innovation and accessibility.

    Q: What kinds of future roles would someone who took these positions be prepared for?

    A: As members of the integrated Sheridan Center for Teaching and Learning, both positions have clearly defined advancement pathways based on the university’s evolving needs, with opportunities to progress to senior learning designer, senior learning technologist or even assistant director roles.

    While that’s the formal pathway, what’s exciting to me is that we’ve deliberately designed these positions to foster professional growth, which means an individual’s potential future impact at Brown is really only limited by their own ambitions of expanding their expertise in the field of learning design and technology. This has been my experience at Brown, and between the university’s deep commitment to staff development and remaining responsive to emerging trends in higher education, I imagine the possibilities for future roles extend beyond what I can envision at this moment.

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