Tag: Challenging

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

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

    Key points:

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

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

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

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

    Fast forward to today.

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

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

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

    This is where visual literacy becomes a frontline defence.

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

    From photography to AI: A conversation grounded in practice

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

    A conversation that grew out of practice

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

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

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

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

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

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

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

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

    Reading images is reading

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

    When students read images carefully, they:

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

    These are the habits of skilled readers.

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

    From composition to comprehension: Mapping image reading to reading strategies

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

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

    Once students recognise these moves, teachers can say explicitly:

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

    That moment of transfer is powerful.

    Making AI image generation teachable (and safe)

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

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

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

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

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

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

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

    When classroom talk begins to change

    Over time, classroom conversations shift.

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

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

    These are reading sentences.

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

    Visual literacy as a bridge, not an add-on

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

    By teaching students how to read images, schools strengthen:

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

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

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

    It is literacy.

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

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  • AI is challenging us to relocate our sense of educational purpose in the outward-future rather than the inward-past

    AI is challenging us to relocate our sense of educational purpose in the outward-future rather than the inward-past

    As the debates and discussions around use of AI continue to develop, I reflect that, perhaps too often, the questions we ask as educators about the impacts of AI can be too small.

    There seems to me to be a current over-preoccupation with inward-facing considerations of the impact of AI on our own practices and processes: How we can manage the risks of academic misconduct, how we make our assessments a bit more authentic, how we quality assure students’ development of “AI skills”. I don’t deny that these are important and timely questions, but I think they miss the bigger (knottier) purpose-led picture.

    As AI continues to infuse our work in a variety of means and ways we seem sometimes too focused on management and adaptation of processes, rather than working strategically and purposefully to define broader outcomes which face off into the professional and graduate futures of our students and the world they will occupy and shape over the next 50 years.

    Until we start asking the bigger questions about the more fundamental challenges to educational purposes that AI brings in its wake, we will not be in a position to understand the shifts in educator capabilities and competencies and indeed professional identities that such a paradigm shift will necessarily require.

    Recently, with Prof. Nick Jennings, I argued that we can see two “swim lanes” emerging in AI: one focused on process optimisation and efficiency; one on invention and co-creation. Both are useful, but they require very different things from educators.

    AI literacy for optimisation

    AI tools offer compelling possibilities to support students with personalised learning support, rapid retrieval of relevant information and coaching prompts for personal and career development. I don’t see these tools replacing human academic and student services professionals; instead they offer a degree of personalised insight and augmentation to human-centric services.

    Similarly, AI tools can assist with many of the functions of teaching and learning “delivery”, offering ideas for small-group activities, generating reading lists or other learning resources, offering prompts to structure discussion, rapidly processing student feedback, and so on. Again, this is an efficient, step change augmentation to the spectrum of digital tools that can support effective learning and teaching. Educators will adopt these if they find them to be useful, and according to their disciplinary culture, and their personal orientation towards technology in general.

    Just as we have adapted to email or MS Excel (other software is available) as baseline administrative tools used in organisations and businesses, over time I see that academic workflows will no doubt evolve in response to collective learning and accepted wider practices about the usefulness and effectiveness of various AI tools when applied to different elements of academic practice. Some tools might genuinely make academics’ lives easier; others may promise much and deliver very little.

    From an institutional perspective it makes sense to curate a flow of discussion about the adoption of AI tools for learning, teaching and student support. Doing so allows for the dissemination of useful practice, contributes to collective understanding about AI’s capabilities and limitations and, optimally, ensures that where AI tools are adopted they are applied ethically and in ways that do not compromise academic quality.

    AI literacy for reimagining education futures

    With the potential benefits of AI for optimisation duly noted, I don’t think that is the conversation that is going to be the most material for education leaders in the next few years. For me, AI does not represent a specific set of digital capabilities that must be mastered so much as it points to a future that is fundamentally uncertain, and subject to tectonic disruption.

    That loss of predictability speaks to a very different set of purposes and outcomes for education – less the acquisition of a body of knowledge than the development of high end human competencies exercised and mediated through a developed technological literacy, all underpinned by a disciplinary knowledge base.

    Every new technology, from writing to print to the internet to large language models has prompted a reconsideration of the relationship between educational purposes and disciplinary knowledge. Over time, instead of a student “coming to the discipline” as an apprentice and an assumed future practitioner, disciplinary knowledge is increasingly deployed in the service of a broader range of student outcomes – the discipline “comes to the student.” This is also increasingly reflected in portfolio careers in which core knowledge is rehashed, redeployed, recontextualised and directed towards the challenges of the world and of the workplace, none of which are solved by a single discipline. The difference between previous shifts and the paradigm shift being ushered in by AI is the speed, volatility and unpredictability of what it will do. We are in uncharted waters and, if we are honest, we are not really sure where we are headed or how best to help shape those future outcomes and destinations.

    Despite these shifts, or perhaps in part because of them, the idea of the professor still defaults to the guardian and steward of disciplinary knowledge. Recognising that the strength of UK HE in particular comes from a tradition of being organised around somewhat compartmentalised deep disciplinary knowledge, this conceptualisation has remained remarkably consistent even as higher education has become more widely available and serving purposes beyond the passing on of knowledge.

    In this sense AI can never (and should never) “replace” academics as stewards of disciplinary knowledge, but it should prompt a deep examination of what that reconfiguration of the relationship between knowledge and education purpose looks like for the different disciplines – and the moments when students need to cross disciplinary boundaries in service of their potential futures, rather than the futures we imagined when in their shoes.

    The questions and discussion I am interested in curating asks academics about the potential shape of their discipline and its associated professions in 50 years: What does it mean to think, and “do” your discipline with and alongside AI? What does AI do to the professional practices and identities of the professions allied to your disciplines? The answers to such questions are more readily imagined through contemporary cutting edge research agendas than by established approaches to engaging students with existing bodies of knowledge.

    It is only in light of our imagination of the possible futures that await our students that we can start asking what kind of educational environments and approaches we need to build to create the conditions for the development of the skills sets, attitudes and competencies they will need.

    My hunch is that we will collectively need to “unwire” ourselves from “standard” PG Cert and PG Dip teaching development tracks and be prepared to look outside the classics of higher education pedagogy and literature, including to primary education, and innovative workplace CPD to find the approaches that work best. While we might retain a foundational basket of knowledge and skills required for entry to the academic profession, I think these will resonate more strongly with a broader set of high end human competencies than with the traditional skills associated with teaching development.

    It is likely we’ll need to take a more experimental, co-creative approach to the higher education pedagogy, which engages in the outward facing futurology of graduate paths across the next 50 years as a fundamental starting point for considering our own purpose-led practices. In this we might then retain concepts and theories that serve those purposes while discarding those that have outlived their usefulness.

    Sam Grogan will be among the speakers at Kortext LIVE education leaders event on 11 February in London, as part of a panel discussing the Wonkhe/Kortext project Educating the AI Generation. Find out more and book your free spot here.

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  • This math platform leverages AI coaching to help students tackle tough concepts

    This math platform leverages AI coaching to help students tackle tough concepts

    eSchool News is counting down the 10 most-read stories of 2025. Story #5 focuses on a math platform that offers AI coaching for maximum impact.

    Math is a fundamental part of K-12 education, but students often face significant challenges in mastering increasingly challenging math concepts.

    Many students suffer from math anxiety, which can lead to a lack of confidence and motivation. Gaps in foundational knowledge, especially in early grades and exacerbated by continued pandemic-related learning loss, can make advanced topics more difficult to grasp later on. Some students may feel disengaged if the curriculum does not connect to their interests or learning styles.

    Teachers, on the other hand, face challenges in addressing diverse student needs within a single classroom. Differentiated instruction is essential, but time constraints, large class sizes, and varying skill levels make personalized learning difficult.

    To overcome these challenges, schools must emphasize early intervention, interactive teaching strategies, and the use of engaging digital tools.

    Last year in New York City Public Schools, Franklin Delano Roosevelt High School (FDR) teachers started using a real-time AI math coaching platform from Edia to give students instant access to math support.

    Edia aligns with Illustrative Mathematics’ IM Math, which New York City Public Schools adopted in 2024 as part of its “NYC Solves” initiative–a program aiming to help students develop the problem-solving, critical thinking, and math skills necessary for lifetime success. Because Edia has the same lessons and activities built into its system, learning concepts are reinforced for students.

    FDR started using Edia in September of 2024, first as a teacher-facing tool until all data protection measures were in place, and now as an instructional tool for students in the classroom and at home.

    The math platform’s AI coaching helps motivate students to persevere through tough-to-learn topics, particularly when they’re completing work at home.

    “I was looking for something to have a back-and-forth for students, so that when they need help, they’d be able to ask for it, at any time of the day,” said Salvatore Catalano, assistant principal of math and technology at FDR.

    On Edia’s platform, an AI coach reads students’ work and gives them personalized feedback based on their mistakes so they can think about their answers, try again, and master concepts.

    Some FDR classes use Edia several days a week for specific math supports, while others use it for homework assignments. As students work through assignments on the platform, they must answer all questions in a given problem set correctly before proceeding.

    Jeff Carney, a math teacher at FDR, primarily uses the Edia platform for homework assignments, and said it helps students with academic discovery.

    “With the shift toward more constructivist modes of teaching, we can build really strong conceptual knowledge, but students need time to build out procedural fluency,” he said. “That’s hard to do in one class session, and hard to do when students are on their own. Edia supports the constructivist model of discovery, which at times can be slower, but leads to deeper conceptual understanding–it lets us have that class time, and students can build up procedural fluency at home with Edia.”

    On Edia, teachers can see every question a student asks the AI coach as they try to complete a problem set.

    “It’s a nice interface–I can see if a student made multiple attempts on a problem and finally got the correct answer, but I also can see all the different questions they’re asking,” Carney said. “That gives me a better understanding of what they’re thinking as they try to solve the problem. It’s hugely helpful to see how they’re processing the information piece by piece and where their misconceptions might be.”

    As students ask questions, they also build independent research skills as they learn to identify where they struggle and, in turn, ask the AI coach the right questions to target areas where they need to improve.

    “We can’t have 30 kids saying, ‘I don’t get it’–there has to be a self-sufficient aspect to this, and I believe students can figure out what they’re trying to do,” Carney said.

    “I think having this platform as our main homework tool has allowed students to build up that self-efficacy more, which has been great–that’s been a huge help in enabling the constructivist model and building up those self-efficacy skills students need,” he added.

    Because FDR has a large ELL population, the platform’s language translation feature is particularly helpful.

    “We set up students with an Illustrative Math-aligned activity on Edia and let them engage with that AI coaching tool,” Carney said. “Kids who have just arrived or who are just learning their first English words can use their home languages, and that’s helpful.”

    Edia’s platform also serves as a self-reflection tool of sorts for students.

    “If you’re able to keep track of the questions you’re asking, you know for yourself where you need improvement. You only learn when you’re asking the good questions,” Catalano noted.

    The results? Sixty-five percent of students using Edia improved their scores on the state’s Regents exam in algebra, with some demonstrating as much as a 40-point increase, Catalano said, noting that while increased scores don’t necessarily mean students earned passing grades, they do demonstrate growth.

    “Of the students in a class using it regularly with fidelity, about 80 percent improved,” he said.

    For more spotlights on innovative edtech, visit eSN’s Profiles in Innovation hub.

    Laura Ascione
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  • How Superior Public Schools united curriculum and data

    How Superior Public Schools united curriculum and data

    Key points:

    Creating consistency between classrooms and ensuring curriculum alignment school-wide can be challenging, even in the smallest of districts. Every educator teaches–and grades–differently based on their experience and preferences, and too often, they’re forced into a solution that no longer respects their autonomy or acknowledges their strengths.

    When Superior Public Schools (SPS), a district of 450 students in rural Nebraska, defined standards-referenced curriculum as a priority of our continuous improvement plan, bringing teachers in as partners on the transition was essential to our success. Through their support, strategic relationships with outside partners, and meaningful data and reporting, the pathway from curriculum design to classroom action was a smooth one for teachers, school leaders, and students alike.

    Facing the challenge of a new curriculum

    For years, teachers in SPS were working autonomously in the classroom. Without a district-wide curriculum in place, they used textbooks to guide their instruction and designed lesson plans around what they valued as important. In addition, grading was performed on a normative curve that compared a student’s performance against the performance of their peers rather than in relation to a mastery of content.

    As other educators have discovered, the traditional approach to teaching may be effective for some students, but is inequitable overall when preparing all students for their next step, whether moving on to more complex material or preparing for the grade ahead. Kids were falling through the cracks, and existing opportunity gaps only began to grow.

    SPS set out to help our students by instituting standards-referenced instruction at both the elementary and secondary levels, allowing us to better identify each child’s progress toward set learning standards and deliver immediate feedback and intervention services to keep them on the path toward success.

    Take it slow and start with collaboration

    From day one, school leaders understood the transition to the new curriculum needed to be intentional and collaborative. 

    Rather than demand immediate buy-in from teachers, administrators and the curriculum team dedicated the time to help them understand the value of a new learning process. Together, we took a deep dive into traditional education practices, identifying which set students up for success and which actually detoured their progress. Recognizing that everyone–teachers included–learns in different ways, administrators also provided educators with a wide range of resources, such as book studies, podcasts, and articles, to help them grow professionally.

    In addition, SPS partnered with the Curriculum Leadership Institute (CLI) to align curriculum, instruction, and assessment practices across all content areas, schools, and grade levels. On-site CLI coaches worked directly with teachers to interpret standards and incorporate their unique teaching styles into new instructional strategies, helping to ensure the new curriculum translated seamlessly into daily classroom practice.

    To bring standards-referenced curriculum to life with meaningful insights and reporting, SPS integrated the Otus platform into our Student Information System. By collecting and analyzing data in a concise manner, teachers could measure student performance against specific learning targets, determining if content needed to be re-taught to the whole class or if specific students required one-on-one guidance.

    With the support of our teachers, SPS was able to launch the new curriculum and assessment writing process district-wide, reaching students in pre-K through 12th grade. However, standards-reference grading was a slower process, starting with one subject area at a time at the elementary level. Teachers who were initially uncomfortable with the new grading system were able to see the benefits firsthand, allowing them to ease into the transition rather than jump in headfirst. 

    Empowering educators, inspiring students

    By uniting curriculum and data, SPS has set a stronger foundation of success for every student. Progress is no longer measured by compliance but by a true mastery of classroom concepts.

    Teachers have become intentional with their lesson plans, ensuring that classroom content is directly linked to the curriculum. The framework also gives them actionable insights to better identify the skills students have mastered and the content areas where they need extra support. Teachers can adjust instruction as needed, better communicate with parents on their students’ progress, and connect struggling students to intervention services.

    Principals also look at student progress from a building level, identifying commonalities across multiple grades. For instance, if different grade levels struggle with geometry concepts, we can revisit the curriculum to see where improvements should be made. Conversely, we can better determine if SPS needs to increase the rigor in one grade to better prepare students for the next grade level.

    While the road toward standards-referenced curriculum had its challenges, the destination was worth the journey for everyone at SPS. By the end of the 2024-2025 school year, 84 percent of K-5 students were at or above the 41st percentile in math, and 79 percent were at or above the 41st percentile in reading based on NWEA MAP results. In addition, teachers now have a complete picture of every student to track individual progress toward academic standards, and students receive the feedback, support, and insights that inspire them to become active participants in their learning.

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  • Innovation, Collaboration During Challenging Times

    Innovation, Collaboration During Challenging Times

    I just returned from the UPCEA annual conference held in Denver. A record attendance of some 1,300 administrators, faculty and staff from member institutions gathered to share policies, practices, innovations and knowledge in advancing the mission of higher education in 2025. It was a thriving and exciting environment of energy and enthusiasm in seeking solutions to challenges that confront us today and into the future.

    Recent policy shifts regarding the federal funding of grants provided by the institutes and foundations that support university research were on the minds of most who attended. These topics provided the undercurrent of discussions in many of the sessions. The spirit was one of supporting each other in advancing their initiatives despite the prospect of cuts in federal support. The confluence of the demographic enrollment cliff of college-bound students due to the drop in births during the previous recession of 2007–09 and additional promised cuts in funding from federal and many state sources created an environment for collaboration on solving shared challenges rivaled only by that of the COVID-19 pandemic.

    A number of the sessions addressed innovations with cost savings, efficiencies and effectiveness gains that can be realized by thoughtfully introducing artificial intelligence into supporting many aspects of the higher education mission. The potential savings are significant if AI can take over duties of positions that become vacant or instances where staff are better utilized by shifting their efforts elsewhere.

    Most Popular

    By fall 2025, readily available AI tools will be able to serve in course development, delivery and assessment:

    • Conceive, design, create online (even self-paced) courses
    • Adapt and update class materials with emerging concepts, societal situations and news context
    • Lead and assess class discussions—stimulate deeper thought and engagement
    • Assess course assignments with personalized recommendations to fill in the gaps in knowledge
    • Provide one-on-one counseling on academic matters and referrals for personal challenges
    • Create a summative assessment of course outcomes and initiate revisions for improvement
    • Generate a deep-thinking report for administrators and committees to consider

    By this fall, readily available AI tools will be able to serve in curriculum development, marketing and student onboarding:

    • Survey specified fields for addition or expansion of degree and certificate programs
    • Recommend detailed curriculum for new programs and suggest tuition/fees
    • Create marketing plans after developing a report on demand and competitors in the program area
    • Develop, track, implement and adapt marketing budget
    • Prepare and support student advising to optimize retention and completion
    • Prepare updated and revised plans for spring 2026

    By fall 2025, develop optimal staff allocation and review process:

    • Assess performance evaluations, recommend additional interviews as appropriate
    • Develop, refine and utilize departmental/college priority list to respond to revenue and enrollment trends for the year
    • Match staff skills with desired outcomes
    • Monitor productivity and accomplishments for each employee
    • Make recommendations for further efficiencies, having AI perform some tasks such as accounting and data analysis previously done by humans
    • Be responsive to employee aspirations and areas of greatest interest
    • Review and prepare updated and revised plans for spring 2026

    These tasks and many more can be accomplished by AI tools that can be acquired at modest costs. Of course, they must be carefully reviewed by human administrators to ensure fairness and accuracy are maintained.

    I learned from a number of those attending the UPCEA conference that, in these relatively early stages of AI implementation, many employees harbor fears of AI. Concerns center around human job security. While there are many tasks that AI can more efficiently and effectively perform than humans, most current jobs include aspects that are best performed by humans. So, in most cases, the use of AI will be in a role of augmentation of human work to make it more expedient and save time for other new tasks the human employees can best perform.

    This presents the need for upskilling to enable human staff to make the efficiencies possible by learning to work best with AI. Interestingly, in most cases experts say this will not require computer coding or other such skills. Rather, this will require personnel to understand the capabilities of AI in order to tap these skills to advance the goals of the unit and university. Positions in which humans and AI are coworkers will require excellent communication skills, organizational skills, critical thinking and creative thinking. AI performs well at analytical, synthetical, predictive and creative tasks, among others. It is adept at taking on leadership and managerial roles that recognize the unit and institutional priorities as well as employee preferences and abilities.

    How then can we best prepare our staff for optimizing their working relations with the new AI coworkers? I believe this begins with personal experience with AI tools. We all should become comfortable with conducting basic searches using a variety of chat bots. Learning to compose a proper prompt is the cornerstone of communicating with AI.

    The next step is to use a handful of the readily available deep-research tools to generate a report on a topic that is relevant to the staff member’s work. Compare and contrast those reports for quality, accuracy and the substance of cited material. Perform the research iteratively to improve or refine results. This Medium post offers a good summary of leading deep-research engines and best applications, although it was released in February and may be dated due to the Gemini version 2.5 Pro released on March 26. This new version by Google is topping many of the current ratings charts.

    In sum, we are facing changes of an unprecedented scale with the disruption of long-standing policies, funding sources and a shrinking incoming student pool. Fortunately, these changes are coming at the same time as AI is maturing into a dependable tool that can take on some of the slack that will come from not filling vacancies. However, to meet that need we must begin to provide training to our current and incoming employees to ensure that they can make the most of AI tools we will provide.

    Together, through the collaborative support of UPCEA and other associations, we in higher education will endure these challenges as we did those posed by the COVID pandemic.

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  • States File Lawsuit Challenging Education Department Cuts

    States File Lawsuit Challenging Education Department Cuts

    Twenty Democratic state attorneys general filed a lawsuit Thursday against the Trump administration for its massive job cuts at the Education Department, seeking to block what they say is “an effective dismantling” of the department. 

    The suit argues that by eliminating half the staff, the department is essentially abdicating its responsibility to deliver statutorily mandated programs, like federal student aid and civil rights investigations—many of which also affect state programs. 

    “This massive reduction in force is equivalent to incapacitating key, statutorily-mandated functions of the Department, causing immense damage to Plaintiff States and their educational systems,” the suit reads.

    The plaintiffs include Arizona, California, Colorado, Connecticut, Delaware, the District of Columbia, Hawaii, Illinois, Maine, Maryland, Massachusetts, Michigan, Minnesota, Nevada, New Jersey, New York, Oregon, Vermont, Washington and Wisconsin.

    The lawsuit is at least the eighth to be filed against the Trump administration over its education policies in the past month. Follow Inside Higher Ed’s Trump Lawsuit Tracker for updates on the case.

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  • Embracing a growth mindset when reviewing student data

    Embracing a growth mindset when reviewing student data

    Key points:

    In the words of Carol Dweck, “Becoming is better than being.” As novice sixth grade math and English teachers, we’ve learned to approach our mid-year benchmark assessments not as final judgments but as tools for reflection and growth. Many of our students entered the school year below grade level, and while achieving grade-level mastery is challenging, a growth mindset allows us to see their potential, celebrate progress, and plan for further successes amongst our students. This perspective transforms data analysis into an empowering process; data is a tool for improvement amongst our students rather than a measure of failure.

    A growth mindset is the belief that abilities grow through effort and persistence. This mindset shapes how we view data. Instead of focusing on what students can’t do, we emphasize what they can achieve. For us, this means turning gaps into opportunities for growth and modeling optimism and resilience for our students. When reviewing data, we don’t dwell on weaknesses. We set small and achievable goals to help students move forward to build confidence and momentum.

    Celebrating progress is vital. Even small wins (i.e., moving from a kindergarten grade-level to a 1st– or 2nd-grade level, significant growth in one domain, etc.) are causes for recognition. Highlighting these successes motivates students and shows them that effort leads to results.

    Involving students in the process is also advantageous. At student-led conferences, our students presented their data via slideshows that they created after they reviewed their growth, identified their strengths, and generated next steps with their teachers. This allowed them to feel and have tremendous ownership over their learning. In addition, interdisciplinary collaboration at our weekly professional learning communities (PLCs) has strengthened this process. To support our students who struggle in English and math, we work together to address overlapping challenges (i.e., teaching math vocabulary, chunking word-problems, etc.) to ensure students build skills in connected and meaningful ways.

    We also address the social-emotional side of learning. Many students come to us with fixed mindsets by believing they’re just “bad at math” or “not good readers.” We counter this by celebrating effort, by normalizing struggle, and by creating a safe and supportive environment where mistakes are part of learning. Progress is often slow, but it’s real. Students may not reach grade-level standards in one year, but gains in confidence, skills, and mindset set the stage for future success, as evidenced by our students’ mid-year benchmark results. We emphasize the concept of having a “growth mindset,” because in the words of Denzel Washington, “The road to success is always under construction.” By embracing growth and seeing potential in every student, improvement, resilience, and hope will allow for a brighter future.

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  • Challenging climate hypocrisy in higher education learning and teaching 

    Challenging climate hypocrisy in higher education learning and teaching 

    By Dr Adrian Gonzalez (@AGonzalez05) Senior Lecturer in Sustainability and Director of Learning and Teaching, Department of Environment and Geography at the University of York.

    Climate hypocrisy in Higher Education

    The climate crisis and global attempts at strengthening the sustainable and low-carbon transition is arguably the most critical issue we face and there is clear evidence to show strong Higher Education (HE) support for this twin approach. However, HE, particularly in the Global North, faces increasing scrutiny and critique over its implementation of the sustainability agenda. This has led to accusations of greenwashing, in which universities (willingly or perhaps erroneously) overmarket and/or underdeliver their sustainability policies, and climate hypocrisy, where an internationalist agenda frames student recruitment (the drive towards overseas markets), research activities and partnerships. For example, in UK tertiary education (further education and higher education), the largest sources of travel emissions are student flights, but there has been limited focus on the emissions stemming from learning and teaching, particularly fieldtrips, which this post is keen to reflect on.

    Destination long haul; Higher Education residential undergraduate student fieldtrips

    Outdoor education, particularly fieldtrips, offer a wide array of learner benefits and can be integral to different undergraduate programmes such as Geography, Earth and Environmental Sciences (GEES), archaeology, history and classics. However, the competitive UK higher education market has helped generate an internationalisation of undergraduate fieldtrips which are now used as a critical marketing tool to attract prospective students, who as ‘consumers’, are increasingly keen on knowing where these trips go to inform applications. For example, a brief internet search of UK GEES departments shows undergraduate trips heading to exotic locations such as the Amazonia region, Colombia (BSc Environmental Science), Bahamas (BSc Ocean Science and Marine Conservation) and Malawi (BA Human Geography). 

    Climate hypocrisy is evident here; students are studying programmes that acknowledge and grapple with the climate crisis and the need for transformational structural changes, yet at the same time will be enrolled on degrees that facilitate long-haul international learning opportunities without significant acknowledgement or reflection of the environmental impacts. Whilst there is no reliable publicly available data on the level of carbon emissions generated by GEES and other subject fieldtrips in UK higher education, I can give an indication by drawing on a case study of the department I work in.

    Department of Environment and Geography, University of York

    The department runs a wide variety of one-day and residential fieldtrips across its undergraduate and postgraduate programmes. It is the undergraduate residential trips that, owing to their design, have particularly significant carbon emissions and were made the focus of the subsequent investigation. Until 2022-2023, the department ran several residential fieldtrips that encompassed both UK and overseas destinations for its four undergraduate programmes (BSc Environmental Science; BSc Physical Geography and Environment; BSc Environment, Economics and Ecology; BA Human Geography and Environment). 

    I used the University of York’s carbon calculator, which draws upon the UK government’s Department for Environment, Food and Rural Affairs greenhouse conversion factors to calculate the carbon emissions stemming from travel and accommodation and the offsetting requirements. The table below shows the residential fieldtrips and carbon emissions from travel (including coach and flights where relevant) and accommodation on a per-person and 50-person basis. For four 50-person trips, this generated 108,521.85 kg CO2e (or 109 metric tonnes rounded up), equating to a carbon offsetting cost of £3,437.97 for the Department on an annual basis.

    Table 1: Department of Environment and Geography, University of York fieldtrips up to 2022-2023

    What does this total figure equate to? A good comparison is the Stockholm Environment Institute (SEI), an international non-profit that focuses on environment and development challenges and employs 170 staff working across several international regional centres. At the time of these fieldtrips operating, SEI’s 2020 annual report indicated that its air travel emissions were almost 550 metric tonnes CO2e (in 2019). So these department fieldtrips made up the equivalent of almost 20% of the total air travel emissions of a major international research organisation.

    Conclusion: a call to action

    These figures indicate the scale of the socio-environmental impacts caused and the urgent need for UK higher education learning and teaching operations, particularly in GEES given the subject areas, to be seen as ‘walking the talk.’ There have been recent efforts to address this issue through the work of the RGS-IBG who have developed a list of voluntary principles to guide geography fieldwork, including the adoption of ‘sustainable fieldtrips’ which acknowledge the need to recognise and justify the resulting carbon impacts. Whilst it is positive to see 31 institutions signed up, this is less than half of the UK GEES departments and does not incorporate any wider disciplinary commitments. 

    This article raises a call to action for all learned institutions and UK HE departments operating residential fieldtrips to adopt sustainable fieldtrip principles and operations. Without system-wide change, climate hypocrisy remains unchallenged in UK higher education learning and teaching. 

    To support academic staff and departments, several steps towards sustainable fieldtrips can be taken:

    • Conduct a carbon audit of fieldtrips to ascertain the impacts as undertaken at the Department of Environment of Environment and Geography, University of York; 
    • Using this data, consider revising long-haul fieldtrip locations to relevant localised destinations that can be reached through low carbon (i.e. no flights) transport; 
    • Publish the carbon costs on the department or university website to support wider debate and discussion of sustainable fieldtrips;
    • Implementing sustainable fieldtrips can lead to multiple Equity, Diversity and Inclusion (EDI) benefits, particularly around accessibility and inclusivity. Use this opportunity to review and seek to strengthen the EDI agenda. 
    • Disseminate best practice guidance through research and conference outputs;
    • Lobby learned institutions to adopt sustainable fieldtrip principles that align with those adopted by the RGS-IBG;

    Through these steps, UK higher education can begin to create a more holistic, robust and transparent sustainability and decarbonisation agenda. 

    However, these actions cannot happen in isolation or nullify wider critical discussions around the UK HE sustainability agenda. One of the most significant discussion points is the impact of international students studying in the UK, a country which is the second most popular study destination in the world. Whilst these students provide significant economic benefits to the UK economy (£41.9 billion between 2021/22) and are vital to the UK higher education business model (one in six universities get over a third of their total income from overseas students), the carbon footprint far surpasses the UK higher education fieldtrip contribution. A 2023 report from 21 UK further education and higher education providers concluded that student flights accounted for 2.2 metric tonnes of CO2e or 12% of total emissions, whilst globally, student mobility is estimated to generate at least 14 megatones of Co2e per year (14 million metric tonnes). It is clear therefore that in the UK context, there is an urgent need for a robust policy debate on UK higher education funding and student mobility, otherwise the sector’s decarbonisation agenda will remain only partially addressed through sustainable fieldtrips. 

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