Throughout 2023, the education market appears to be steadily shifting from a position of apprehension toward AI’s role toward embracing the it’s potential. It was only last year that instructors lamented ChatGPT and its ability to promote plagiarism in the classroom. Anecdotally, however, we believe we’re seeing fewer instructors who view artificial intelligence as an adversary and more who view it as an ally.
Instead, they now see it as a useful solution to support (not replace) processes within their job description. The instructors who reject AI are much like those who forbade their students from using the internet in the 90s. Instead of sending students to the library, they’re much better served exploring how it can support better learning outcomes.
The warming attitude towards AI means the time is ripe for EdTech companies to integrate these technologies into their products. In fact, plenty of EdTech companies have already done so, with varying degrees of success.
If you’re feeling behind in the race to add AI to your EdTech, you’re certainly not alone. The question is no longer “Should you integrate AI into your EdTech product?” It’s how you should integrate them, and how soon. But rather than adding multiple integrations to your product to keep up with competitors, adopt a more strategic approach.
Strategic Areas Where Your EdTech Product Can Benefit From AI
Companies are feeling immense pressure to add similar AI technologies to their products. And there are many meticulously-built AI innovations out there that create value for their users.
But if you aren’t strategic about your implementation, you won’t create that value. Take Adobe Photoshop beta, for instance.
It feels to us that their recent addition of generative AI features to their flagship product feels rushed and vastly underwhelming when compared to other platforms such as Midjourney. But the flip-side is that they are in the game and learning from their users with live features.
For EdTech product teams, it’ll be important to balance the pressure of releasing AI features and the desire to wait until they are sure they truly add value to their users. Instead of rushing ahead, take a step back and consider where AI can have the most impact. Here’s where AI features can best serve your UX.
Personalization and Adaptive Learning
The truth is: generative AI technology is the thing everyone’s thinking about right now. But machine learning is nothing new in EdTech. The thing that’s changing the conversation so quickly is the sudden impact the new generation of these technologies have brought. In a way, you’ve just been working with the beta version.
Take personalization and adaptive learning experiences, for example. These are two fundamental features of EdTech products. One of the goals of EdTech has always been to personalize the learning experience for students. Personalized EdTech products might track a student’s progress, identify their individual learning needs, and tailor the content and activities to their specific interests and abilities, thereby creating adaptive learning experiences. EdTech products with adaptive learning experiences adjust in difficulty based on students’ performance. This ensures that students are challenged but not overwhelmed, and not wasting time on material they already know.
Before the acceleration of AI, your product could perhaps offer three or four different adaptive learning experiences. Not only are large language models (LLMs) drawing upon vastly larger databases than ever, they are paired with powerful cognitive models that can drive action in the proper context of what each user is trying to accomplish. That’s opening up opportunities to deliver highly personalized experiences.
Real-time feedback
With a larger data set to draw from, AI can also provide constructive user guidance the moment your user needs it. During a learning activity when a student is struggling to master a concept, for instance, AI features can intervene to guide the student toward the correct solution in a way that makes more sense to the user.
With great data comes great responsibility, however. Make sure your product team aligns on your product development strategy. As always, it’s extremely important to conduct user research to ensure an unbiased approach to AI within your product. Your LLM should output the most accurate information and filter proprietary data and misinformation from the web, lest it undermine your entire product.
Analytics
One of the major advantages of AI is its ability to quickly identify and report patterns and summarize them in readable, user-friendly formats. An EdTech AI integration that produces meaningful reporting on user habits and performance has the potential to drive instructors and students with actionable insights. This can improve user outcomes, which in turn boosts your product’s efficacy.
Real world examples of machine learning in EdTech
Numerous EdTech companies have heeded the call to add machine learning to their products.
- Duolingo uses AI to track users’ progress and adjust the difficulty of the exercises accordingly.
- Khan Academy uses AI to recommend personalized learning paths for each student.
- Minecraft Education Edition uses AI to create adaptive challenges that are tailored to each student’s skill level.
- Cognition Builder uses AI to provide students with personalized feedback on their work.
- ClassDojo uses AI to analyze classroom data and provide teachers with insights into student behavior.
In each example, AI has been harnessed thoughtfully to reinforce existing product strengths, improving effectiveness and enhancing the user experience. In deciding how to integrate AI into your EdTech, your UX team should focus on opportunities where AI can be a force multiplier for what your product already does well or strives to achieve.
Let your UX team be the brains behind your AI strategy
The moral here is: don’t rush to add AI features to your EdTech unless it makes sense to do so. AI has the potential to build user loyalty — or erode it. Your approach should include ample UX research. Taking time to test and validate prototypes with machine learning will be instrumental in offsetting the risk of adding an unusable feature.
Ultimately, you need to be a good steward of the user experience and your product goals. If one of your goals is better learning outcomes, it may be prudent for you to add AI integrations that enhance your analytics reporting, for instance. Or add a small, personalized feature here and there.
But you shouldn’t rush to add AI features to your products simply to check a box or appease a stakeholder. In truth, the EdTech UX team that adds new technology to their products in small, methodical doses is going to win out over any company that rushes to add flashy technology — every time.
Openfield has the UX research and design resources to integrate AI into your product strategically. Curious how you might integrate AI into your EdTech product? Reach out.
