The Socratic Method at Scale: The Future of AI in Learning

February 6, 2024

As Bloomberg predicts in a recent article, “The generative AI market is poised to explode, growing to $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022, according to a new report by Bloomberg Intelligence (BI),” and learning is one of two sectors the article calls out as specifically likely to benefit from this growth. 

At Studion, because our goal is to deliver custom digital learning experiences that provide rich engagement to learners efficiently and at scale, advances in AI are a crucial tool in our toolbox for building and nurturing our clients’ communities of learners. We want to give learners the ability to unlock their inherent potential, and the thoughtful inclusion of AI in digital learning experiences allows this. 

We center learners in everything we do, and we know how to make technology work to serve each learner, no matter where they are in their journey. 

To effectively teach a learner, of course the first step is getting and maintaining their attention. As Studion Vice President, Learning Practice Josh Newman says, “The bar right now for engagement is extraordinarily high. If you’re choosing between going on social media or playing a video game versus watching someone read a PowerPoint presentation, the non-engaging, non-interactive PowerPoint reader is going to lose. If your choice is between reading content on a static webpage versus an interactive conversation with a ChatGPT-like educator, the ChatGPT educator will flat-out be more engaging.” 

This is why newer applications of generative AI include things like Khan Academy’s use of a ChatGPT-style digital tutor that struggling learners can talk to; this AI tutor will not only answer their questions, but direct them to other courses if they need more information. As Sal Khan says in his TED Talk “How AI Could Save (not Destroy) Education,” “AI could potentially provide a personal AI tutor for every student and an AI teaching assistant for every teacher.” This method of interaction can retain learners’ attention.  

The Past Meets the Future

Certain forms of AI have been present in learning for years. Machine learning is currently used to score free-response questions on standardized tests. The state of California, to give one example, uses machine learning in this way for over 5 million K–12 students. Multiple Studion clients use machine learning to monitor how students are doing in digital courses, where they’re getting stuck, and which areas of courses may need improvement. And many global formative assessment companies rely on machine learning to implement computerized tests that give different students different questions, based on the answers they give during the test. 

Josh predicts adaptive curricula are next, saying, “For everybody right now, it’s the same syllabus for a course. I think we’re going to start seeing AI applications that tailor the course syllabus to individual students based on a questionnaire they fill out about what their interests are or why they’re taking a class. Also, we’ll have adaptive modules based upon how well learners do in the early modules.” 

In addition, AI can assist with learning experiences in fundamental ways because it can help educators accomplish certain tasks more quickly and accurately. “It can translate to approximately fifty languages currently and help learners with different learning styles,” Josh says. Because AI can pivot in how it presents material, there’s potential for chat tools to teach math concepts, for example, by talking through them, which would benefit learners who don’t do as well when only given graphs and charts to explain a concept. This kind of option humanizes learning within a digital environment by tailoring the content and its presentation to what the learner needs in the moment. It’s one way in which we, the people behind the AI, can guide it to deliver meaningful outcomes for learners at scale. 

We’re always actively exploring ways to improve learners’ experiences and facilitators’ resources.

Our future use of AI will continue to pull together what our clients need to support their brands, their educators, and their learners.

What if we could use AI to identify problematic spots in courses, then build in interventions ahead of time to help learners get through those spots? What if we could use AI to predict which learners will need more engagement within a course, then create nudges to help them stay on task? What if we could create adaptive coursework and even draft course offerings themselves? 

“You see this happening right now at the micro level in courses where generative AI is used to make a PowerPoint or write an assignment,” Josh says, “but we know that it can be used at the entire course level, where you can take an existing offline course with its syllabus, reading list, tools and assessments, teacher lesson plans, and have a first draft of an entire online course be authored in a highly engaging way, with interactives and assessments and full inclusion.” 

Some companies are diving into these waters already. Kajabi, a tech company that provides an all-in-one business platform to help entrepreneurs create and sell their digital services and products, is experimenting with a new AI Creator Hub that can quickly develop course outlines and marketing campaigns using their generative AI tools.

Leveraging AI to Improve Digital Learning

At Studion, our goal is to make it possible for people to create digital learning platforms better, cheaper, and faster, to the benefit of both organizations and their learners—but it’s not to replace the human element of creation. “These tools should be thought of as turbo-chargers,” Josh says, “not replacements for humans.” We’re bringing in AI to be an assistant to our work, not to complete the work for us. 

Large language models are not capable of independent thought, after all; they’re only as accurate and unbiased as the data they consume. This means that they can be both incorrect and biased. Thus, the participation and guidance of humans are and will continue to be crucial to any successful use of AI in the learning space.   But these concerns shouldn’t take away from the incredible opportunities available thanks to AI. Take this example from Josh: “[AI] could be Socratic at the individualized level at scale. Say I’m the instructor for an online course and I want my students to break into small groups to discuss a topic. What if we include ChatGPT in those small groups and have students start out by asking ChatGPT a specific prompt question? Now you have ChatGPT there as a catalyst to the conversation, so not only are students bouncing ideas off of each other, they’re having ChatGPT push the conversation in new directions that they can then continue to talk about. It’s faster than awaiting an instructor response, it’s individual and interactive. It puts the learner in the center of the experience.”    Our experienced designers and engineers are guides into this future, augmenting the learner’s experience by utilizing AI to create what they need in real time. Because we’re technology agnostic, we’re free to do what we do best: integrate systems. “Our job is to have a great radar,” says Josh, “to identify things that are good, things that are working, and then incorporate those into our learning experience platforms. We’re always going to be going for best-in-breed applications.” 

We’re putting in the time and effort to get to know each organization we work with as well as their learners, which is how we can develop learner-centered content that’s richly engaging and focused on inclusion and community. We will continue to pull together the best from the available technology to deliver meaningful outcomes that benefit everyone involved.

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