Category: Artificial Intelligence

  • Innovation Without Borders: Galileo’s Networked Approach to Better Higher Education System

    Innovation Without Borders: Galileo’s Networked Approach to Better Higher Education System

    One of the biggest, but least remarked upon trends in European higher education in recent years is the growth of private for-profit, higher education. Even in countries where tuition is free, there are hundreds of thousands of students who now prefer to take courses at private for-profit institutions.

    To me, the question is, why? What sort of institutions are these anyway? Interestingly, the answer to that second question is one which might confuse my mostly North American audience. Turns out a lot of these private institutions are relatively small, bespoke institutions with very narrow academic specializations. And yet they’re owned by a few very large international conglomerate universities. That’s very different from North America, where institutions tend to be either small and bespoke, or part of a large corporation, but not both.

    Today my guest is Nicolas Badré. He’s the Chief Operating Officer of the Galileo Group, which operates a number of universities across Europe. I met him a few months ago at an OECD event in Jakarta. When I heard about some of Galileo’s initiatives, I knew I’d have to have him on the show. 

    There are three things which I think are most important about this interview. First is the discussion about Galileo’s business model and how it achieves economies of scale across such different types of institutions. Second, there’s how the network goes about collectively learning across all its various institutions. And third, specifically how it’s choosing to experiment with AI across a number of institutions and apply the lessons more globally. 

    Overall, it’s a fascinating chat. I hope you enjoy it too. But now, let’s turn things over to Nicolas.


    The World of Higher Education Podcast
    Episode 3.27 | Innovation Without Borders: Galileo’s Networked Approach to Better Higher Education System

    Transcript

    Alex Usher (AU): Nicolas, Galileo Global Education has grown significantly over the years. I think the group is, if I’m not mistaken, 13 or 14 years old now. Some of the universities it owns might be a bit older, but can you walk us through the origins of the group? How did you grow to be as big as you are? I think you’ve got dozens of institutions in dozens of countries—how did that growth happen so quickly?

    Nicolas Badré (NB): Thank you, Alex, for the question. It’s an interesting story. And yes, to your point, the group was created 13 and a half years ago, with an investment by Providence Equity Partners into Istituto Marangoni, a fashion school in Italy. That dates back to 2011. Since then, we’ve made 30 acquisitions.

    The growth started primarily in Europe, especially in France and Germany. Then, in 2014, we took our first steps outside of Europe with the acquisition of IEU in Mexico. Significant moves followed in 2018 and 2019, particularly into the online learning space with Studi in France and AKAD in Germany.

    There’s been a very rapid acceleration over the past five years. For context, I joined the group at the end of 2019. At that time, Galileo had 67,000 students across nine countries. Today, we have 300,000 students in 20 countries.

    Back then, the group was primarily focused on arts and creative schools, as well as business and management schools. Now, we’ve expanded into tech and health, and even into some professional training areas—like truck driving, for instance.

    What does this reflect? Two things. First, very strong organic growth from our existing schools and brands. Take ESG in France as an example. It’s been around for 40 years and is a well-known entry-level business school. Over the past five years, it’s diversified considerably creating ESG Luxury, ESG Tourism, you name it. It’s also expanded its physical presence from just a few cities to now being in 15 or 16 cities across France.

    So it’s really been a combination of strong organic growth and selective acquisitions that have helped us more than quadruple our student numbers in just five years.

    AU: It’s interesting— I think a lot of our listeners and viewers might be surprised to hear about such a strong for-profit institution coming out of France. When you think of French higher education, you think of the Grandes Écoles, you think of free education. So why would so many people choose to pay for education when they don’t have to? It’s a pretty strong trend in France now. I think over 26% of all students in France are in some form of private higher education. What do you offer that makes people willing to give up “free”?

    NB: It’s a good question, and you’re right—it’s not just about France. In many places across Europe, including Germany, the Nordics, and others, you see similar dynamics.

    That said, yes, in France in particular, there’s been a growing share of private players in higher education over the past few years. That probably reflects the private sector’s greater ability to adapt to new environments.

    I’d highlight three main factors that help explain why we’ve been successful in this space.

    First, we’re obsessed with employability and skills-based education. And that’s true across all levels and backgrounds. When we worked on our group mission statement, everyone agreed that our mission is to “unleash the potential of everyone for better employability.” 

    Because of that focus, we maintain very strong ties with industry. That gives us the ability to adapt, create, and update our programs very quickly in response to emerging demands. We know competencies become obsolete faster now, so staying aligned with job market needs is critical. That’s probably the strongest unifying driver across all of Galileo.

    Beyond that, we also offer very unique programs. Take Noroff, for example—a tech school in Norway, which is even more tuition-free than France. It’s one of the very few fee-paying institutions in the country. But the program is so strong that students are willing to pay around 15,000 euros a year because they know they’ll get a top-tier, hands-on experience—something that might be slower to evolve in the public system.

    So that’s the first point: employability and unique, high-impact programs.

    Second, we put a strong emphasis on the student experience. How do we transform their education beyond just delivering content? That’s an area we continue to invest in—never enough, but always pushing. We’re focused on hybridizing disciplines, geographies, and pedagogical approaches.

    And we’ve systematized student feedback—not just asking for opinions, but making sure we translate that feedback into tangible improvements in the student experience.

    And third, I’d say there’s a values-based dimension to all of this. We focus heavily on innovation, entrepreneurship, and high standards. Those are the core values that we’re driven by. You could say they’re our obsessions—and I think that kind of vision and energy resonates with our students. Those are the three main things I’d point to.

    AU: I have a question about how you make things work across such a diverse set of institutions. I mean, you’ve got design schools, drama schools, law schools, medical schools. When people think about private education, there’s often an assumption that there’s some kind of economies of scale in terms of curriculum. The idea that you can reuse curriculum across different places. But my impression is that you can’t do that very much. It seems like you’re managing all these different institutions, each of them like their own boutique operation, with their own specific costs. How do you make it work across a system as large and diverse as yours? Where are the economies of scale?

    NB: Well, that’s also a very good point—and you’re absolutely right. We have a very diverse network of schools. We have a culinary arts school in Bordeaux, France, with maybe 400 students, and we have universities with more than 10,000 students, whether in medical or business education.

    So yes, you might wonder: why put these institutions together?

    The answer is that we really built the group’s development around the entrepreneurial DNA of our school directors. They’re responsible for their own development—for their growth, diversification, and how they respond to the job market.

    We’re not obsessed with economies of scale. What we really value is the network itself. What we focus on is shared methodology—in areas like sales and marketing, finance, HR, and student experience.

    There are also some opportunities for synergies in systems. In some cases, for instance, yes—we use a similar CRM across several countries. But I think the real value of the network lies in its ability to share experiences and experiment with innovation throughout, and then scale up those innovations appropriately across the other schools.

    So I’d say it’s more about shared practices than about forcing economies of scale across borders—because that doesn’t always make sense.

    AU: Am I correct in thinking that you don’t necessarily present yourself as a chain of institutions to students? That each institution actually has a pretty strong identity in and of itself—is that right? Is there a fair bit of autonomy and ability to adapt things locally at each of your schools?

    NB: Yes, I think that’s true. In terms of branding, we believe that each of our schools generally has a stronger brand than Galileo itself. And that’s how it should be, because each school has its own experience, its own DNA, its own momentum and development.

    So, we see ourselves more as a platform that supports the development of all these schools, rather than a chain imposing the same standards and practices across the board.

    Of course, we do have certain methodologies—for example, how to run a commercial campaign. We provide guidance, but it’s ultimately up to each school to manage that process and use the methodology in a way that works best for their own development.

    That doesn’t mean there’s no value in having the Galileo name—there is. But the value is in being a platform that supports the schools, rather than overshadowing them.

    AU: Nicolas, I know Galileo is testing a lot of AI-driven approaches across its various institutions. What I found interesting in a discussion we had offline a few weeks ago is that you’re experimenting with AI in different parts of the institution—some of it around curriculum, some around administration, and some around student services. Can you give us an overview? What exactly are you testing, and what are the goals of these experiments?

    NB: I think we first need to frame how we’re using AI, and it’s important to look at our strategy globally. We believe there are three major trends shaping higher education.

    First, student expectations are evolving quickly—they’re demanding more flexibility and personalization. Second, there’s a rapid emergence of new competencies, which challenges our ability to adapt and update programs quickly. And third, we need to go beyond boundaries and be agile in how we approach topics, address new skills, and serve diverse learners. These are the three starting points we see as opportunities for Galileo to differentiate itself. Now, we’re not trying to become a leading AI company. Our goal remains to be a recognized leader in education—improving employability and lives. That’s our benchmark.

    With that in mind, our AI vision is focused on four areas:

    1. How do we deliver a unique experience to our students?
    2. How do we connect educators globally who are trained in and comfortable with AI?
    3. How do we develop content that can be adapted, localized, translated, and personalized?
    4. And how do we improve operational productivity?

    AI is clearly a powerful tool in all four areas. Let me walk through some of the things we’re doing. 

    The first area we call AI for Content. We’re using AI to more quickly identify the competencies required by the job market. We use tools that give us a more immediate connection to the market to understand what skills are in demand. Based on that, we design programs that better align with those needs.

    Then the next step is about course and content creation. Once we’ve defined the competencies, how do we design the courses, the pedagogical materials? How do we make it easier to localize and adapt that content?

    Take Studi, an online university in France with 67,000 students and around 150 different programs. A year ago, it would take them about four months to design a bachelor’s or master’s program. Now, it takes one to two months, depending on the specifics. The cost has been cut in half, and development speed has increased by a factor of two, three, even four in some cases. This also opens up opportunities to make programs more personalized because we can update them much faster. 

    The second area is AI for Experience. How do we use AI to enhance the student experience?

    We’ve embedded AI features in our LMS to personalize quizzes, generate mind maps, and create interactive sessions during classes. We’ve also adapted assessments. For example, in Germany, for the past two years, our online university AKAD has let students choose their own exam dates. That’s based on an AI approach that generates personalized assessments while staying within the requirements of German accreditation bodies. This wouldn’t be possible without AI. The result is higher engagement, faster feedback, and a more personalized learning experience.

    Lastly, beyond content and experience, we’re seeing real gains in AI for Operations. In sales and marketing, for example, we now use bots in Italy and Latin America to re-engage “dead” leads—contacting them again, setting up meetings, and redirecting them through the admissions funnel. It’s proven quite efficient, and we’re looking to expand that approach to other schools.

    We’re also seeing strong results in tutoring. Take Corndel, a large UK-based school focused on apprenticeships. They’re using AI tools extensively to improve student tracking, tutoring, and weekly progress monitoring.

    So, we’re seeing a lot of momentum across all these dimensions—and it’s really picked up speed over the last 18 months.

    AU: So, you’ve got a network of institutions, which gives you a lot of little laboratories to experiment with—to try different things. How do you identify best practices? And then how do you scale them across your network?

    NB: Well, first of all, we have lots of different pilots. As you’ve understood, we’re quite decentralized, so we don’t have a central innovation team of 50 people imposing innovations across all our schools.

    It’s more about scouting and sharing experiences from one school to another. It’s a combination of networks where people share what they’re learning.

    Just to name a few, we have a Digital Learning Community—that’s made up of all the people involved in LMS design across our schools. They exchange a lot of insights and experiences.

    We also hold regular touchpoints to present what’s happening in AI for content, AI for experience, and AI for operations. We’ve created some shared training paths for schools as well. So there are a lot of initiatives aimed at maximizing sharing, rather than imposing anything top-down. Again, as you pointed out, the schools are extremely diverse—in terms of regulations, size, content, and disciplines. So there’s no universal recipe.

    That said, in some cases it’s more about developing a methodology. For example, how do you design and implement a pedagogical chatbot? The experiments we’re running now are very promising for future scale-up, because we’re learning a lot from these developments.

    AU: I know that, in a sense, you’ve institutionalized the notion of innovation within the system. I think you’ve recently launched a new master’s program specifically focused on this question—on how to innovate in education systems. Can you tell us a little bit about that?

    NB: Yeah, I’m super excited to talk about this, because it’s where I’m focusing most of my energy these days.

    We’ve been working on this project for a year with four Galileo institutions. It’s called Copernia, and the name, like Galileo, is intentional—these are people who changed perspectives. That’s exactly what we want to do: change the perspective on education and truly put the student at the center.

    Copernia started the initiative, Galileo confirmed it, and it’s no coincidence we’re focusing on this.

    The first program we’re launching under Copernia is a Master of Innovation and Technology for Education. The idea is to bring together and leverage expertise from several fields: neurocognitive science, tech, AI and data, educational sciences, innovation, design, and management. The goal is to offer students a unique experience where they not only learn about innovation—but also learn to develop and apply it.

    One of the major assets we want to leverage is the Galileo network. With over 120 campuses, we can offer students real, hands-on opportunities to experiment and innovate. So the value proposition is: if you want to design and test educational innovation, we’ll give you the tools, the foundational knowledge, and, most importantly, the chance to apply that in practice—within our network, with our partners, and with other institutions.

    The goal is to help the whole ecosystem benefit—not just from Galileo’s environment, but also from the contributions of tech partners, academic collaborators, and business partners around the world. I’m convinced this will be a major tool to develop, share, and scale practical, applied innovation.

    And importantly, this isn’t meant to be just an internal initiative for Galileo. It’s designed to be open. We want to train people who can help transform education—not only in higher education, but also in K–12 and lifelong learning. Because we believe this kind of cross-disciplinary expertise and hands-on innovation experience is valuable across the entire education sector.

    AU: I’m really impressed with the scale and speed at which you’re able to experiment. But it did make me wonder—why can’t public higher education systems do the same? I mean, if I think about French universities, there are 70 or 80 in the public system—though it’s hard to keep track because they keep merging. But theoretically, they could do this too, couldn’t they? It’s a moderately centralized system, and there’s no reason institutions couldn’t collaborate in ways that let them identify useful innovations—rolling them out at different speeds in different areas, depending on what works. Why can’t the public sector innovate like that?

    NB: First of all, I wouldn’t make a sweeping judgment on this. I think there is innovation happening everywhere—including within public institutions. So I wouldn’t describe it in black-and-white terms.

    That said, it’s true that as a private organization, we face a certain kind of pressure. We need to prove that we operate a sustainable model—and we need to prove that every month. In other words, we rely on ourselves to develop, to test, and to optimize how we grow. 

    The second is that we have an asset in being able to test and learn in very different environments. Take the example I mentioned earlier, about Germany and the anytime online assessments. We were able to implement that model there because it was online and because the regulatory environment allowed it.

    Now, when we approach accreditation bodies in other countries, we can say: “Look, it works. It’s already accepted elsewhere. Why not consider it here?” That ability to move between different contexts—academic and professional, vocational and executive—is really valuable. It allows us to promote solutions that cross traditional boundaries.

    That’s not something all public universities can do—and frankly, not something all universities can do, period. But it’s an advantage we’ve built over the past several years by creating this large field for experimentation.

    AU: Nicolas, thank you so much for being with us today.

    NB: Alex, thank you very much. It’s been a pleasure.

    AU: It just remains for me to thank our excellent producers, Tiffany MacLennan and Sam Pufek, and to thank you—our viewers, listeners, and readers—for joining us. If you have any questions about today’s podcast, please don’t hesitate to get in touch at [email protected]. And don’t forget—never miss an episode of The World of Higher Education Podcast. Head over to YouTube and subscribe to our channel. Join us next week when our guest will be Noel Baldwin, CEO of the Future Skills Centre here in Canada. He’ll be joining us to talk about the Programme for the International Assessment of Adult Competencies. See you then.

    *This podcast transcript was generated using an AI transcription service with limited editing. Please forgive any errors made through this service. Please note, the views and opinions expressed in each episode are those of the individual contributors, and do not necessarily reflect those of the podcast host and team, or our sponsors.

    This episode is sponsored by Studiosity. Student success, at scale – with an evidence-based ROI of 4.4x return for universities and colleges. Because Studiosity is AI for Learning — not corrections – to develop critical thinking, agency, and retention — empowering educators with learning insight. For future-ready graduates — and for future-ready institutions. Learn more at studiosity.com.

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  • student-assistant-new-genai-capabilities – The Cengage Blog

    student-assistant-new-genai-capabilities – The Cengage Blog

    Reading Time: 2 minutes

    Since launching the Student Assistant in beta last year, we’ve been working with thousands of faculty and students to train it and bring a personalized learning experience to more students. So, what’s next for this GenAI-powered tool? 

    We’re taking it to the next level. Starting this fall 2025, the Student Assistant will become available to over 1 million students with new capabilities, including integration throughout the learning experience, course offerings across 100+ products and our new AI-powered insights dashboard.  

     Let’s jump in. 

    A quick refresher: Let us reintroduce you to the Student Assistant 

    Leveraging intelligent language models and Cengage-trusted content, the Student Assistant guides students through the learning process within their specific products. Currently, embedded in our online learning platform, MindTap, it provides tailored feedback to help students reach their own solutions, without giving away the answers. We want to support students to not only understand what they’re learning, but apply course concepts with confidence. That’s why this tool was purposefully trained by students and instructors, to ensure academic integrity is at the forefront.  

    Personalized support across learning activities 

    We’ve told you how the Student Assistant personalizes learning. Soon, students can experience that level of comprehensive, personalized support throughout their entire learning experience. The Student Assistant is expanding across various learning activities and can support more difficult question types. Plus, its responses will link to actual textbook chapters, images, videos and other resources. This allows students to instantly connect with their course content and understand exactly what they’re learning.  

    More course options equal more opportunities for students 

    Spanning 100+ products, the Student Assistant will be available to over 1 million students, each with their own set of unique learning needs. We’ve expanded access across our best-selling products, including “Principles of Economics” by N. Gregory Mankiw, “Anatomy & Physiology” by Dr. Liz Co, “Precalculus” by James Stewart and more. With more product offerings and platforms available, we can reach a wider range of students from a variety of key disciplines.

    Allows instructors to look beyond grades with AI-powered insights dashboard  

    The most desired AI use case for 52% of instructors we surveyed is AI that personalizes learning and instruction.  

    Built on real-time interactions from the Student Assistant, our new AI-powered insights dashboard is a tool instructors can utilize to support and meet students right where they’re at in the learning process. Instructors can track students’ learning patterns and increase engagement with personalized, actionable insights on everything from study habits to learning challenges and concept gaps – all before it impacts their grades.  

    The future of learning is looking bright 

    Overall, this expansion will help us create better learning experiences for more students and allow instructors like you to meet their individual needs — so you can support them in their academic journeys and create futures full of opportunity.   

    Want to stay posted on updates about our fall 2025 expansion and learn more about the Student Assistant for your course?  

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  • generative-ai-in-online-education – The Cengage Blog

    generative-ai-in-online-education – The Cengage Blog

    Reading Time: 3 minutes

    The rapid advancements in generative artificial intelligence (GenAI) are reshaping education, offering innovative tools for content creation, adaptive learning, and instructional strategies. GenAI models, such as ChatGPT, assist educators by generating structured lesson plans, assessments, and multimedia content, reducing workload and enhancing efficiency. These tools also support adaptive learning by personalizing content to match students’ strengths and learning gaps, increasing engagement and knowledge retention.

    However, the integration of GenAI presents ethical and legal concerns, including potential biases in AI-generated content, violation of the copyrights held by content creators and data privacy risks. Responsible use, complemented by human oversight, is essential to maintaining educational integrity. Successful applications of GenAI demonstrate its potential to expedite course development and create engaging digital learning experiences. Striking a balance between innovation and ethical considerations ensures AI enhances, rather than replaces, human-led teaching.

    Content creation and lesson planning

    GenAI streamlines lesson planning by allowing educators to input objectives and receive lesson plans tailored to learning goals. In fact, recent Cengage research cites lesson planning as a use-case for how teaching and learning can be supported by AI. While this functionality can save instructors valuable time and ensure their subject needs are met, it’s important to ensure that the use of copyrighted material falls within your license or other legal parameters.

    Additionally, AI-generated assessments support MOOCs, or Massive Open Online Courses, by facilitating adaptive and interactive course components, bridging the gap between large-scale online instruction and personalized learning. GenAI ensures lessons cater to diverse learning styles, enhancing accessibility and retention by integrating various formats, text, video and interactive activities.

    Adaptive learning and personalization

    AI can help assess and target students’ individual learning needs, enhancing student motivation and academic outcomes. Real-time feedback mechanisms allow learners to self-assess progress and focus on areas needing improvement, particularly beneficial in large-scale online courses. Additionally, GenAI can help personalize study materials, such as quizzes and practice tests, ensuring students learn at their own pace while maintaining engagement. When following copyright laws, these advancements help bridge gaps in traditional online learning, where standardized content may not meet diverse student needs.

    The future of AI in online education

    The use of AI in asynchronous learning is revolutionizing how educators develop content. With AI-driven tools, instructors can create high-quality, interactive, and accessible video lectures without the steep learning curve of traditional production methods. As technology continues to advance, AI will play an increasingly pivotal role in shaping the future of online education.

    For educators looking to simplify their lecture creation process, adopting AI tools is a game-changer. Instructors can focus more on teaching and less on technical production, ultimately providing students with a more engaging and effective learning experience.

    Ethical considerations and challenges

    While GenAI enhances education, ethical matters must be addressed. AI systems often rely on extensive data collection, raising privacy concerns that necessitate stringent safeguards. Moreover, biases in training data can result in skewed educational content, underscoring the need for careful dataset curation.

    Another challenge is the risk of over-reliance on AI-generated materials. While AI can assist in lesson planning and content development, human oversight remains critical to ensure contextual understanding and engagement. AI-based assessment tools, though efficient, may fail to interpret nuanced student responses accurately, necessitating human intervention to maintain fairness in evaluations.

    Conclusion

    Collaboration between educators, policymakers, and AI developers is crucial in establishing best practices that optimize AI’s benefits while mitigating risks. A balanced approach — leveraging AI’s efficiency while preserving human oversight — can foster an equitable, innovative, and effective learning environment.

    Follow Matt Larcin, subscribe to the Age of AI in Higher Education newsletter and visit www.mattlarcin.com.

    Written by Matt Larcin, Senior Instructional Designer, University of California, Los Angeles 

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  • AI-Powered Teaching: Practical Tools for Community College Faculty – Faculty Focus

    AI-Powered Teaching: Practical Tools for Community College Faculty – Faculty Focus

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  • AI-Powered Teaching: Practical Tools for Community College Faculty – Faculty Focus

    AI-Powered Teaching: Practical Tools for Community College Faculty – Faculty Focus

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  • The Student Assistant: Through the Student Lens

    The Student Assistant: Through the Student Lens

    Reading Time: 4 minutes

    You first met our game-changing GenAI-powered Student Assistant in August 2024, and we’ve been keeping you up to date on all of the exciting developments ever since. We’ve told you how it helps personalize your students’ learning experience on a whole new level with content that’s specific to your course textbook — but now we want to show you how. 

    Let’s dive in and explore some visual examples of student interactions that demonstrate its full capabilities.

    Points students in the right direction  

    Do your students ever get stuck on how to begin working on a question or topic? Using the Student Assistant, students can ask for a solid jumping-off point to get the ball rolling in the right direction. They can also ask it to clarify points of confusion, so they can successfully progress through an assignment.  

    Student Assistant tells student where to start by making sure they understand the key terms in the question.

    Student Assistant I'm lost prompt

    Promotes critical thinking and academic integrity 

    The Student Assistant guides students to help them identify the correct answer, without giving it away, promoting the development of critical thinking skills and putting emphasis on self-reliance. Students are also discouraged from simply guessing a correct answer and are asked to explain their logic behind a selection.

    Student asks the Student Assistant to just give them the answer, and the Student Assistant tells them they cannot provide answers directly. The Student Assistant Is it the first answer prompt.

    Simplifies complex topics 

    If students are struggling to comprehend what they’re learning, they can ask for topics to be elaborated on, rephrased or broken down. They can also ask for brief definitions of key terms. 

    Student asks the Student Assistant to make the topic simpler. Student Assistant provides simpler explanation. Student asks Student Assistant to explain topic in a different way. Student Assistant responds with a different explanation.

    Student asks Student Assistant to give a short definition. Student Assistant provides a concise definition for each term.

    Makes real-world connections 

    With the Student Assistant, students can ask for explanations of how topics they’re studying connect to real-world scenarios. It can generate discipline- and career-specific use-cases, helping students understand the relevancy of course content within the framework of their future careers.  

    Student asks the Student Assistant to give them a real-world example of topic. Student Assistant provides an example. Student asks the Student Assistant how topic applies to nursing? Student Assistant provides explanation.

    Student asks the Student Assistant when they'll use this topic after college. Student Assistant provides a detailed explanation.

    Keeps students on track 

    Getting distracted during a task is something that can happen to the best of us, and students are no exception. If students ask to be shown external or entertaining web content, the Student Assistant will redirect and keep them focused on the assignment at hand. This tool will never provide or rely on external content.  

    Student asks the Student Assistant for a cat video. The Student Assistant redirects student back to assignment.

    Motivates and encourages

    The Student Assistant lets students know that it’s okay to struggle through an assignment by encouraging them with a positive, motivational tone. With positive reassurance from the Student Assistant, students can complete assignments with confidence.  

    Student tells the Student Assistant, this is so hard. The Student Assistant replies with encouragement and motivation.

    Reframes course content  

    When students aren’t making personal connections with course content, it can be easy for them to lose interest in the topic altogether. Students can ask for their course topics to be turned into an engaging story, helping them key into critical themes and ideas that they may have initially overlooked.  

    Student asks Student Assistant to turn topic into a story. The Student Assistant provides a story.

    Can’t wait to begin using the Student Assistant in your courses? 

    The Student Assistant is currently available in beta with select titles, including “Anatomy & Physiology”, “CompTIA Network+ Guide to Networks” and “Economics.”  To get started, create a course with any of the titles available with the Student Assistant and start using it today. 

    We’re gearing up for more titles to feature the Student Assistant this fall. In the meantime, you can currently explore this tool’s capabilities, its current list of titles where it’s featured and AI at Cengage.   

     

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

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

    International Frameworks

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

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

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

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

    Industry Collaborations

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

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

    AI Literacy

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

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

    Teaching and Learning

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

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

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

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

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

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

    Accessibility & Digital Divide

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

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

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  • How AI is Changing the Way I Teach Business Law

    How AI is Changing the Way I Teach Business Law

    Reading Time: 5 minutes

    AI has taken the world by storm, and the education field is no exception. After over two decades teaching at The Paul Merage School of Business at the University of California, Irvine, I have seen lots of changes related to curriculum, teaching resources and students. However, I’ve seen nothing quite like the wave of AI tools popping up in classrooms. It’s exciting, a little daunting and definitely something we all need to talk about.

    So, here’s the deal: I’m not an AI expert. But I have spent a lot of time experimenting with AI, learning from my mistakes and figuring out what works and what doesn’t. I’d like to share some of these experiences with you.

    AI in education: What’s the big deal?

    AI is already here, whether we’re ready for it or not. According to Cengage research, use of AI has nearly doubled among instructors, from 24% in 2023, to 45% in 2024. Many of us are using AI to create lectures, craft assignments and even grade assessments. The challenge is not whether we adopt AI. Rather, it’s doing so in a way that enhances our students’ learning outcomes, while maintaining academic integrity in our courses.

    In my online undergraduate business law course, I have always required my students to take written assessments, where they analyze a set of facts to reach a legal conclusion. Not only am I trying to teach them the principles of law, but I want them to improve their writing skills.

    A shift in focus

    A few years ago, I noticed a subtle increase in the overall scores for these written assessments. I have taught this course for over 20 years, so I knew what the historical scores were. Looking into it further, I started hearing about how some students were using ChatGPT in their courses. This got me wondering whether some of my students had already been using it to take my written assessments. Quick answer: yes, they were. This now presented a problem: what do I do about it? In an online course, how can I prohibit the use of AI tools on a written assessment while effectively enforcing that ban?  I shifted my focus from policing and enforcing a ban on the use of AI in my courses to teaching my students how to use AI responsibly.

    Teaching students to use AI responsibly

    In my course, I developed assignments called “Written ApprAIsals.” These three-part writing assignments combine traditional learning with AI-assisted refinement. These teach students how to use AI responsibly while improving their critical thinking and writing skills. Here’s how it works:

    Step 1: Write a first draft without AI

    Students are given a law and related news article about a current legal issue. They must write a memo which analyzes the constitutionality of this law. I also provide them with guidance on utilizing the standard legal memo format, known as IRAC (Issue, Rule, Analysis, Conclusion), to help organize their thoughts and writing.

    Students are permitted to use whatever materials they have, including eBooks, my lecture videos and outlines, Cengage’s online learning platform, MindTap and its resources, and any other information they ethically obtain online. But, they’re not permitted to use AI.

    The purpose of this first draft is for them to demonstrate the foundational knowledge they should have already learned. Students must attest to completing this first draft without using AI, and it’s worth 30% of the total “Written ApprAIsal” grade.

    Step 3: Integrate AI to resolve deficiencies

    Once I have given them feedback on their first drafts, students are required to use AI to improve their first draft. Students must submit the URL to their AI queries and responses (“AI log”). Or less ideally, they can submit a PDF or screenshot of them. I can assess the effort they put in, evaluate their queries, and provide guidance on how to more effectively use AI. This part is worth 40% of the total “Written ApprAIsal” grade.

    Step 3: Use AI to help write a final draft

    Using what they’ve obtained from AI, along with my feedback, students must transform their first draft into an improved final draft. Students are permitted to continue using AI as well.  They must turn on track changes in their document so I can see what changes they’ve made to the first draft.

    Why has this approach worked in my course?

    1. It makes students aware of my familiarity with AI and how it’s used. Students now know I am on the lookout for improper usage of AI in our course.
    2. It encourages their acquisition of foundational knowledge. Students quickly figure out that they must know the basic legal principles. Without them, they will have no idea if AI is providing them with inaccurate information, which can happen sometimes, especially when it comes to legal cases
    3. This approach promotes academic integrity. Students recognize their first drafts must reflect their genuine understanding. There is no benefit to using AI for the first draft. Because the remaining parts are based on their use of AI to improve the first draft, there will not be much room for improvement if the first draft is too good. And because students must submit their AI logs, I can easily ascertain if they actually did the work.
    4. Students build necessary skills for their future careers. They can improve their writing and analysis skills in a low stakes’ way, while receiving useful feedback.
    5. It helps me focus my efforts on helping them understand the law, rather than having to enforce a ban on the use of AI.

    Issues related to this approach

    It takes a lot of effort to find the right law and related news article to use. Not only does the law have to be current, but it also must be interesting and relevant to the students. Legal issues must be presented in a way which are factually neutral to avoid bias. And, the news articles must be factual and not cluttered with distracting commentary or opinions.

    Additionally, rapid feedback is required. With up to 150 students in my course, I only have a little more than 24 hours to turn around written feedback and comments on their first drafts and AI logs. Frankly, it can be overwhelming.

    Tips on integrating AI into your course

    I have learned a few things along the way about integrating AI into my courses.

    Establish clear rules: Be upfront and clear about when, and how, AI can be used. Stick to those rules and enforce them.

    Consider accessibility: Not every student has easy or affordable access to AI tools. Make sure you have alternatives available for these students.

    Teach foundational knowledge first: Students need to know the core concepts so they can critically evaluate any AI-generated content.

    Require transparency: Students must show how they used AI. It is a great way to keep them honest.

    Be flexible and open to experimentation, most importantly: Mistakes are inevitable. There will be times where something you thought would work just doesn’t. That’s ok. Adjust and keep innovating.

    Final Thoughts

    AI is here to stay, and that’s not necessarily a bad thing. AI is a tool that can help students learn. But, it’s up to us to show our students how to use AI responsibly. Whether it’s helping them improve their writing skills, gain foundational knowledge or develop critical thinking skills, AI has so much potential in our courses. Let’s embrace it and figure out how to make it work for each of us.

    Got ideas or experiences with AI in your courses? Let’s connect. I would love to hear how you are using it!

    Machiavelli (Max) Chao is a full-time Senior Continuing Lecturer at the Paul Merage School of Business at the University of California, Irvine and Cengage Faculty Partner. 

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  • Three Ways Faculty Are Using AI to Lighten Their Professional Load

    Three Ways Faculty Are Using AI to Lighten Their Professional Load

    Reading Time: 4 minutes

    Our most recent research into the working lives of faculty gave us some interesting takeaways about higher education’s relationship with AI. While every faculty member’s thoughts about AI differ and no two experiences are the same, the general trend we’ve seen is that faculty have moved from fear to acceptance. A good deal of faculty were initially concerned about AI’s arrival on campus. This concern was amplified by a perceived rise in AI-enabled cheating and plagiarism among students. Despite that, many faculty have come to accept that AI is here to stay. Some have developed working strategies to ensure that they and their students know the boundaries of AI usage in the classroom.

    Early-adopting educators aren’t just navigating around AI. They have embraced and integrated it into their working lives. Some have learned to use AI tools to save time and make their working lives easier. In fact, over half of instructors reported that they wanted to use AI for administrative tasks and 10% were already doing so. (Find the highlights here.) As more faculty are seeing the potential in AI, that number has likely risen. So, in what ways are faculty already using AI to lighten the load of professional life? Here are three use-cases we learned about from education professionals:

    1. AI to jumpstart ideas and conversations

    “Give me a list of 10 German pop songs that contain irregular verbs.”

    “Summarize the five most contentious legal battles happening in U.S. media law today.”

    “Create a set of flashcards that review the diagnostic procedure and standard treatment protocol for asthma.”

    The possibilities (and the prompts!) are endless. AI is well-placed to assist with idea generation, conversation-starters and lesson materials for educators on any topic. It’s worth noting that AI tends to prove most helpful as a starting point for teaching and learning fodder, rather than for providing fully-baked responses and ideas. Those who expect the latter may be disappointed, as the quality of AI results can vary widely depending on the topic. Educators can and should, of course, always be the final determinants and reviewers of the accuracy of anything shared in class.

    1. AI to differentiate instruction

    Faculty have told us that they spend a hefty proportion (around 28%) of their time on course preparation. Differentiating instruction for the various learning styles and levels in any given class constitutes a big part of that prep work. A particular lesson may land well with a struggling student, but might feel monotonous for an advanced student who has already mastered the material. To that end, some faculty are using AI to readily differentiate lesson plans. For example, an English literature instructor might enter a prompt like, “I need two versions of a lesson plan about ‘The Canterbury Tales;’ one for fluent English speakers and one for emergent English speakers.” This simple step can save faculty hours of manual lesson plan differentiation.

    An instructor in Kansas shared with Cengage their plans to let AI help in this area, “I plan to use AI to evaluate students’ knowledge levels and learning abilities and create personalized training content. For example, AI will assess all the students at the beginning of the semester and divide them into ‘math-strong’ and ‘math-weak’ groups based on their mathematical aptitude, and then automatically assign math-related materials, readings and lecture notes to help the ‘math-weak’ students.”

    When used in this way, AI can be a powerful tool that gives students of all backgrounds an equal edge in understanding and retaining difficult information.

    1. AI to provide feedback

    Reviewing the work of dozens or hundreds of students and finding common threads and weak spots is tedious work, and seems an obvious area for a little algorithmic assistance.

    Again, faculty should remain in control of the feedback they provide to students. After all, students fully expect faculty members to review and critique their work authentically. However, using AI to more deeply understand areas where a student’s logic may be consistently flawed, or types of work on which they repeatedly make mistakes, can be a game-changer, both for educators and students.

    An instructor in Iowa told Cengage, “I don’t want to automate my feedback completely, but having AI suggest areas of exigence in students’ work, or supply me with feedback options based on my own past feedback, could be useful.”

    Some faculty may even choose to have students ask AI for feedback themselves as part of a critical thinking or review exercise. Ethan and Lilach Mollick of the Wharton School of the University of Pennsylvania share in an Harvard Business Publishing Education article, “Though AI-generated feedback cannot replicate the grounded knowledge that teachers have about their students, it can be given quickly and at scale and it can help students consider their work from an outside perspective. Students can then evaluate the feedback, decide what they want to incorporate, and continue to iterate on their drafts.”

    AI is not a “fix-all” for the administrative side of higher education. However, many faculty members are gaining an advantage and getting some time back by using it as something of a virtual assistant.

     

    Are you using AI in the classroom?

    In a future piece, we’ll share 3 more ways in which faculty are using AI to make their working lives easier. In the meantime, you can fully explore our research here:

     

     

     

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  • Simulations and AI: Critical Thinking Improvement

    Simulations and AI: Critical Thinking Improvement

    Reading Time: 4 minutes

    As an educator teaching undergraduates and graduates, both online and face-to-face, it’s always a challenge to find meaningful ways to engage students. Now that artificial intelligence has come into play, that challenge has become even greater. This has resulted in a need to address ways to create “AI-proof” assignments and content.

    Simulations in different types of courses

    According to Boston College, simulations are designed to engage students “directly with the information or the skills being learned in a simulated authentic challenge.” In my teaching over the past decade plus, I have gone from using simulations in one primary operations management course to using them in almost every course I teach. And I don’t necessarily use them in a stand-alone assignment, although they can be used as such. How I use a simulation is course dependent.

    Face-to-face

    In some face-to-face courses, I will run the simulation in class with everyone participating. Sometimes I will have teams work in a “department,” or have true, open discussions. Sometimes I will run the room, ensuring every single student is paying attention and contributing. Using simulations in this fashion gives flexibility in the classroom. It shows me who truly gets the concepts and who is going through the motions. The dynamic of the class itself can dictate how I run the simulation.

    Online

    In online courses, I typically assign simulation work. This can be one simulation assignment or a progressive unit of simulations. It’s a great way to see students improve as they move through various concepts, ideas, and applications of the topics covered. Creating assignments which are both relative to the simulation and comparative to the work environment make assignments AI-proof. Students must think about what they have actually done in class and relate it to their workplace environment and/or position.

    Why simulations work for all levels

    There are many simulations that can be used and incorporated in both undergraduate and graduate level courses. As much as we don’t think of graduate students relying on AI to complete work, I have seen this happen multiple times. The results aren’t always ideal. Using simulations at the graduate level, and ensuring your assignments reflect both the simulation and real-world comparisons, can help your students use AI to gather thoughts, but not rely on it for the answers.

    Student benefits

    Using simulations will have many benefits for your students. I have gotten feedback from many students over the years regarding their ability to make decisions and see the results that simulations give. My capstone students often want to continue running the simulation, just to see how well they can do with their “business.” I have had students in lower-level management courses ask me how they can get full access to run these when I have them as “in-class only” options. The majority of feedback includes:

    1. Anything is better than lecture!
    2. Being able to see how students’ decisions impact other areas can be very helpful for them. They actually remember it, enforcing more than reading or watching can do.
    3. Students want more simulations throughout their courses, rather than just one or two. They will have the ability to make those decisions and see those impacts. And they feel it will prepare them even more for the workforce.

    As a retention and engagement tool, simulations seem to be one of the best I have found. Are there students that don’t like them? Yes, there always are. Even so, they’re forced to think through solutions and determine a best course of action to get that optimal result. From an instructor’s perspective, there’s nothing better than seeing those wheels turn. Students are guided on how to recover from an issue, and are advised on what may happen if different solutions were attempted. The questions gained are often better than the results.

    Instructor benefits

    For instructors, there are many benefits. As I stated earlier, you can see improvements in student behavior. They ask questions and have a defined interest in the results of their actions. In classes when you have teams, it can become friendly competition. If they are individual assignments, you get more questions, which is something we always want to see. More questions show interest.

    Ease of use

    Although I usually include recorded instructions and tips for simulations in my online courses, I prefer my personal recordings, since I also give examples relevant to student majors and interests. For example, in an entrepreneurial class, I would go through a simulation piece and include how this might affect the new business in the market vs. how it might impact an established business.

    Auto-grading

    When assigning simulations, they are usually auto-graded. This can drastically lighten our workload. I personally have around 150-200 students each term, so being able to streamline the grading function is a huge benefit. However, with this, there are trade-offs. Since I also create simulation-based questions and assignments, there are no textbook answers to refer to. You must know the simulations and be the content expert, so you can effectively guide your students.

    Thoughtful responses

    AI can be a great tool when used productively. But seeing overuse of the tool is what led me to learn more simulations. This adjustment on my end has resulted in students presenting me with more thoughtful, accurate, and relevant responses. Feedback from students has been positive.

    Sims for all industries

    An additional benefit of simulations is that there are basically sims for all industries. Pilot and healthcare sims have existed for a very long time. But even if you only have access to one or two, you have the ability to make it relatable to any field. If you’re like me and teach a variety of classes, you can use one simulation for almost any class.

    Overall success

    I was using simulations before AI became so influential. The extensive and current use of AI has driven me to use more simulations in all of my courses. By adjusting what tools I use, I have been able to encourage more thorough problem solving, active listening and reasoning. Plus, I get strategic and effective questions from my students. The overall results include intense engagement, better critical thinking skills, and content retention.

     

    Written by Therese Gedemer, Adjunct Instructor and Workforce Development Trainer, Marian University, Moraine Park Tech College and Bryant & Stratton College

     

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