The University of Sydney’s (USyd) new artificial intelligence (AI) learning and assessment policy is commonsense for both teachers and students, head of the uni’s AI group has said.
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The university arguably leading the sector in its use of artificial intelligence (AI) in assessment tasks has received criticism from some students who have complained they lost marks for not using AI in a test.
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Let’s be real — online teaching isn’t about dumping lecture notes into a learning system and calling it a day. If we want students to actually engage, grow and retain what we teach, we’ve got to meet them where they are with tools and strategies that turn passive screens into powerful learning spaces.
This is at the heart of our Spring 2025 Empowered Educator recorded webinar session, “Interactive Learning Redefined With A.I.”
During our session, we explored tools and mindsets that make all the difference, whether you’re just starting as an educator or looking to breathe new life into your virtual classroom.
We’re teaching in an era where attention spans are short, expectations are high and personalization is the norm. Students don’t just want to listen. They want to participate, problem-solve and feel seen. The combination of interactive learning and Generative AI (GenAI) makes this not only possible, but sustainable.
Forget static slides. The key is giving students something to do, not just something to watch. Some of the most effective, real-time strategies listed in the CID Quick Tip Guide were explored during our session:
This kind of learning keeps things dynamic, allows for quick feedback and, best of all, shows students you’re in it with them.
Now, here’s where we level up. AI isn’t just about automation — it’s about tailoring the learning journey to meet each student where they are. In our session, we explored ways to:
It’s like having a digital co-teacher who’s always ready to personalize.
We also dove into case studies and data from real classrooms where these approaches led to:
When students feel included and in control of their learning, outcomes naturally improve.
In the end, this isn’t just about tools or tech. It’s about creating experiences where students feel challenged, supported and seen.
Watching this session on transforming student engagement in the online classroom will more than inspire you. You’ll learn how to:
Let’s create classrooms that aren’t just digital — but dynamic.
Written by Dr. Clevester Moten, Business Instructor at Jackson College and James Bender, Adjunct Instructor at Jackson College.
Dr. Clevester Moten is a transformative educator, scholar and thought leader whose research and work focus on equity, leadership and systemic reform. With more than 20 years of leadership spanning public, private and nonprofit sectors, he specializes in fostering collaboration and addressing societal challenges. Dr. Moten holds advanced degrees in public policy and business administration.
In recent years, artificial intelligence (AI) has rapidly integrated into the world of business, with higher education being no exception. According to recent Cengage research, 92% of higher ed instructors and 83% of students say it’s important to include AI literacy in courses, partly because 84% of students believe AI skills proficiency is important for future employment.
AI tools, such as ChatGPT, Liner, Gemini and other similar platforms, are becoming influential in reinforcing student learning. They can help contribute to the generation of ideas, provide unique perspectives and facilitate deeper engagement with course resources. For example, students can use AI to enhance discussions, discover helpful images and content and improve their critical thinking skills. However, it’s necessary to consider AI integration thoughtfully and responsibly to make the most of its benefits while abating potential barriers.
One of the substantial benefits of integrating AI into the classroom is its capability to foster critical thinking. By offering students various viewpoints on a topic, AI encourages them to explore, compare and contrast different arguments. This process not only deepens their understanding but also sharpens their analytical skills. Additionally, AI can generate prompts that guide students to ask more reflective, intuitive and probing questions, further increasing scholarly interest in a topic.
Even with its benefits, the ascent of AI in academia has raised concerns about academic integrity. When it comes to the risks and ethics of AI, 82% of instructors Cengage surveyed are concerned about academic integrity (cheating, plagiarism). To tackle these concerns, educators must determine well-defined instructions on ethical AI use, emphasizing the importance of originality and proper citation of AI generated content. This methodology ensures that students explore AI responsibly, maintaining integrity in their academic efforts.
AI’s malleability makes it a valuable tool for accommodating various styles of learning. Visual learners can benefit from AI-generated illustrations and graphs, auditory learners from audio abstracts and kinesthetic learners from interactive engagement. By tailoring learning to these diverse needs, AI can create a more stimulating learning environment, enhancing intellectual capacity and student persistence.
Looking ahead, institutions should aspire to develop a viable AI-integrated curriculum that progresses with technological improvements. Continuous enhancement and innovation are essential, as is the creation of AI literacy programs for both students and faculty. Such initiatives will guarantee long-term expertise and certainty in leveraging AI effectively, preparing the academic world for a future where AI plays an integral role in education and the business world.
The integration of AI into higher education proposes a transformative opportunity to enrich synchronous and asynchronous discussions, while cultivating critical thinking. By embracing AI responsibly and ethically, educators can equip students with the skills and strategies to engage more meaningfully with course content, ensuring they are well prepared in an increasingly digital environment.
Written by Dr. Neisa Jenkins, Professor at DeVry University
We recently shared three ways faculty are using generative AI (GenAI) to help them handle the more administrative aspects of their roles — gleaned from ongoing research that culminates in our annual Faces of Faculty report. This comprehensive report explores the professional landscape, challenges, and opportunities facing today’s higher education faculty. Over the past few years, we’ve learned that GenAI has enjoyed popularity among early adopting educators as: a tool for jumpstarting ideas and conversations with students; to help with differentiation of instruction for different learning levels and styles; and a tool for automating feedback. We’ve also learned that around half of instructors now hold a positive view of GenAI, up from just 28% in 2023, and we expect that the number is continuing to rise as more educators experiment with the tech.
What are some other ways in which higher education faculty are using AI to lighten their professional loads? Here are two more use-cases we learned about:
Since GenAI arrived on the higher education scene in a meaningful way, faculty have been understandably frustrated by the ways in which students can use it to cheat and plagiarize the work of others. In fact, 82% of faculty in a recent report expressed concern about academic integrity and AI. An adjunct in Washington told us, “When students rely on AI instead of learning to write and study, they learn less. This is like giving kids a calculator before they know what it even means to add and subtract…”
Yet, we’re hearing from educators that a “fight fire with fire” approach can be really effective at combating plagiarism and cheating. Importantly, this involves having honest conversations with students about academic integrity and the value of original work and critical thinking. Many faculty are spending time explaining to students that while GenAI tools are often appealing as a quick fix, using them to cheat and plagiarize will only harm their chances of academic success. Others are going beyond theory and integrating AI tools into their lessons; effectively asking students to use AI in an integral way, without sacrificing originality.
Some are taking it a step further, though, and are using AI to stay a step ahead of the cheaters by thinking as they do. Faculty are often cued into the possibility of plagiarism by virtue of essays and responses that contain verbatim key terms from prompt phrases, or by stilted and inauthentic word choice and syntax. Running a page of text through an AI detection tool can quickly flag which sentences, concepts or phrases have been “lifted” straight out of ChatGPT or other GenAI platforms. One article suggests that educators subtly obtain a baseline sample of each student’s authentic writing style and capabilities at the start of the term, so that any potential plagiarism becomes far more obvious.
A faculty member at Purdue summarized the nature of the plagiarism challenge in a blog post. “I realized that 80-90% of the assignment I had created for my courses could now be readily answered by AI…We are now thinking about how we can make our courses both AI-amplified and AI-resilient.”
“Judicious use of AI tools will make many tasks less burdensome. Good AI results depend on detailed and well-crafted prompts.” – Instructor, North Carolina
In 2023, over half (58%) of instructors reported wanting to use AI for administrative tasks. As the overall popularity of GenAI has risen among educators, we expect that more and more are also now using GenAI tools to lessen their admin burden. What does this look like, and how can faculty use AI to make professional life easier on the administrative side of things?
A few AI-powered tasks we heard about from survey respondents include:
AI calendar features can help educators optimize their workday by scheduling time blocks that are based on patterns and urgency. It can also deploy automated responses to routine student queries based on certain words and phrases. This simple use-case allows educators to find better work-life balance, avoid scheduling conflicts, and divide their time and attention fairly among the students and situations that most require it.
Asking AI to write a recommendation, resume or cover letter borders on the unethical, but using AI to review these documents and suggest enhancements seems like a smart use of time and technology, and one that can benefit students while saving educators time.
While its results aren’t always perfect, GenAI pulls from a virtually infinite pool of resources to generate lists and recommendations for users. So, no matter how seasoned or well-read an educator may be, AI can offer a helpful starting point for suggesting comprehensive resources and reading material that can benefit students.
Check out our part 1 article: “Three Ways Faculty Are Using AI to Lighten Their Professional Load.“ It highlights three practical ways instructors are putting AI to work — helping them save time, streamline tasks and refocus on what matters most.
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
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:
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 podcast@higheredstrategy.com. 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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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Written by Matt Larcin, Senior Instructional Designer, University of California, Los Angeles
