Learning and Education

Personalized Learning in the Age of AI

In this article:
AI has the potential to transform education. But connecting people and content needs a clear strategy. 

Last year, Thad Lurie, senior vice president of digital and technology at the American Geophysical Union (AGU), began looking into ways to use AI to deliver personalized information, education, and connection recommendations to members. “We have literally hundreds of thousands of peer-reviewed articles and scientific abstracts,” he says. “People were saying, ‘We know the information is there, we just can’t find it.’” 

Through a technology partner, AGU developed a process that uses a machine-learning technique called vectorization, which identities the unique “fingerprint” of a piece of content, and finds matches along other pieces of content, as well as members working in those areas. It created a pilot where it vectorized a year’s worth of content 35,000 items   and shared its findings with a select group of members. “We said we’re building a recommendations engine that’s AI based on natural language processing, and here’s what it would recommend for you,” Lurie says. “Are these pieces of content and these connections relevant to you and your research?’” 

Overwhelmingly, the answer was yes. 

AGU’s experience speaks to one of a number of ways that associations are looking to streamline and personalize their education pathways. Though a fully personalized credentialing and certification learning path hasn’t yet emerged, education professionals in the association world are finding places to bring a personal touch to their processes. 

Jeff Cobb, cofounder and managing director of Tagoras, an educational consulting firm, points to an acronym in the instructional design world: ADDIE, which stands for analysis, design, development, implementation, and evaluation. He’s already seen associations make strides in the development arena, because AI delivers efficiencies for the subject-matter experts who are responsible for developing and vetting educational content. 

“A lot of associations are sitting on vast libraries of subject matter expertise, so it’s really about how they want to leverage that.” —Gary Lamach III, SVP of strategy and growth, ELB

“Associations are typically dependent on volunteer or low-paid subject matter experts to help with the development of the content,” he says. “You’re very dependent upon that SME and what their availability is, what their work ethic is. What AI is doing is giving staff the tools to generate an outline to give to them based on the content that we already have as an organization, or that we’re able to get through public sources, to generate an outline for what we’re looking for. So, the subject matter expert is not working from a blank slate.” 

AI has also proved valuable in the evaluation portion of instructional design, he says. “What AI does now is enable associations to do a much deeper dive and understanding of the evaluations that they’re getting back from their learning experiences,” he says. “That doesn’t take you down to the individual learner level yet, but it does give you the ability to much better shape it going forward, to actually meet the issues that are coming up for your audience.” 

First Steps 

Gary Lamach II, SVP of strategy and growth at ELB, an education consultancy, says associations have an opportunity to use AI to identify and develop new educational pathways that can be monetized. But he first recommends that associations determine their educational goals. “A lot of associations are sitting on vast libraries of subject matter expertise, so it’s really about how they want to leverage that,” he says. “Do they want to leverage it commercially, to access subject matter expertise? Do they want to use it as a member benefit? Are they looking to monetize it in a different way, underpinning their education?” 

Regardless of how it’s used, time-saving opportunities are abundant. Lamach points to one association adapting knowledge-checks, which require explanations for incorrect answers. “If I’m asking a subject matter expert to generate those questions, it’s taking them 15 to 20 minutes to generate each question, because they have to provide a rationale to each incorrect answer as well,” he says. “With the tool that I created, we were able to have subject matter experts vet and edit questions rather than create — so rather than paying a subject matter expert an hour to generate three questions, we’re having them edit and review 10 to 20 questions in that hour. So, there’s an immediate cost savings there.” 

When the information is clear, users seem eager to engage with it. AGU’s Lurie says that because its tool is using only publicly available information and making recommendations around it, it raises no data security or ethical concerns. AGU did inform members about the use of AI and offered them an opportunity to opt out; Lurie says nobody has.  

Beyond looking at how members are using your association’s AI tools, Cobb recommends considering how they’re using them outside of the association. It may be that people are sidestepping the association’s walled gardens, which could eat into certification plans but also allow an association to promote its higher quality, more bespoke, more personalized offerings. 

“Understanding how your learners are actually using AI and what that means for more traditional learning experiences is important, because I think it could be a significant threat — a challenge to what organizations are doing with their education,” he says. “At the same time, it can be a significant opportunity.” 

Mark Athitakis

Mark Athitakis, a contributing editor for Associations Now, has written on nonprofits, the arts, and leadership for a variety of publications. He is a coauthor of The Dumbest Moments in Business History and hopes you never qualify for the sequel.