Let’s be blunt – EdTech is embarrassingly behind. While Netflix, TikTok, and Spotify serve up hyper-personalized content that keeps users hooked for hours, most learning platforms still use data standards from the early 2000s.
The dominant standard in EdTech, SCORM (or its slightly newer cousin, xAPI), is laughably outdated. At best, it tells us if a learner completed a module. That’s it. There are no insights into engagement, adaptive learning paths, or intelligent recommendations – just a binary pass/fail metric in a world where AI can write essays, generate code, and hold entire conversations. Moreover, the data analytics dashboards that learning managers and instructional designers must rely on are relatively poor, offering only a shallow glimpse into learning processes and reducing complex educational experiences to simplistic, inadequate metrics.
The reality is this: education isn’t competing against other educational platforms. It’s competing against every other form of content – YouTube, Instagram, gaming, endless-scrolling dopamine hits – and right now, it’s losing.
The-SCORM-Only-Approach is Dead. Learning Platforms Need to Catch Up
SCORM was created in an era when online learning meant clicking “Next” on a PowerPoint-like interface. Even Tin Can API (xAPI), which was supposed to modernize SCORM, doesn’t come close to the data sophistication that modern platforms require. It’s like trying to run a Formula 1 race with a horse and buggy.
Think about how other industries use data:
- TikTok learns from just a few swipes and instantly adjusts your feed.
- Netflix knows exactly when you stop watching a show and uses that to improve recommendations.
- E-commerce platforms track not just what you buy but what you hesitate on, how long you scroll, and what you compare it to.
Now compare that to EdTech. We have platforms that still expect users to select their learning paths manually, fill out surveys, and complete pre-tests to get a semi-customized experience. Imagine if TikTok made you take a quiz before showing you videos. No one would use it.
True Personalization Requires Data – Not Guesswork
For years, “personalization” has been a buzzword in education. But let’s be honest – most EdTech personalization is barely more than glorified branching logic. A user picks a course from a list, maybe takes a short placement test, and that’s it. The system doesn’t evolve based on their behavior. It doesn’t learn. It doesn’t adapt.
True personalization isn’t a fancy menu of courses. It’s an AI-driven, dynamic experience that evolves in real time based on how users interact with content. It should:
- Track engagement patterns – where learners hesitate, what they skip, and what keeps them engaged.
- Recommend content dynamically, just like the TikTok ‘For You Page’.
- Adapt difficulty levels based on how learners interact, not just how they score on quizzes.
In a world where AI can generate entire lessons on demand, there’s no excuse for EdTech platforms to still rely on primitive, linear course structures.
Learning Data Shouldn’t Exist in a Vacuum
One of the biggest failures of EdTech is its inability to integrate learning data with everything we know about users. Education doesn’t happen in isolation – it’s connected to career goals, job performance, and even daily habits. Yet, most EdTech systems don’t even attempt to tap into this broader information ecosystem.
Learning analytics dashboards should no longer be siloed within traditional boundaries. They must be comprehensive, drawing insights from multiple data sources – including CRM systems, HR databases, payment platforms, and people analytics. The most profound insights emerge at the intersection of these diverse business processes.
Why aren’t we pulling insights from marketing data? If an enterprise LMS knows that an employee is struggling with leadership skills based on past training, why isn’t that data being used to recommend content more smartly?
Why aren’t we using real-world job data? Platforms like LinkedIn know what skills are in demand. Learning platforms should be able to automatically adjust recommendations based on evolving industry needs.
Instead of treating learning data as a closed system that begins and ends within an LMS, we need a more holistic approach. By breaking down these artificial walls and integrating data across different organizational systems, we can create truly intelligent, adaptive learning experiences that respond to individual and organizational needs in real-time.
Lifelong Learning Is More Than a Buzzword – It’s a Business Strategy
Right now, universities and learning platforms treat students like temporary customers. They spend enormous resources attracting students, educating them for a few years, and then… nothing. They let them go.
Why? In almost every other industry, businesses fight to maximize customer lifetime value (LTV). Streaming services, fitness apps, and e-commerce platforms all focus on keeping users engaged in the long term. Yet, in education, we still operate under an outdated model where learning is something you do for a few years and then stop.
Lifelong learning is a massive business opportunity. Imagine if universities, corporate L&D programs, and online platforms thought beyond short-term courses and instead focused on keeping learners engaged for decades.
This isn’t a theory. Companies like Coursera and LinkedIn Learning are already inching in this direction, offering continuous education options tailored to evolving career paths. However, most educational institutions and EdTech platforms are still stuck in the old way of thinking.
The Next Big Shift: Household Learning
Here’s another idea EdTech needs to steal from other industries – stop thinking about individual learners and start thinking about learning households.
The telecom industry figured this out years ago. They used to sell mobile plans to individuals. Then they realized something: people don’t make decisions in isolation. They sell family plans, group bundles, and shared data packages because they understand that acquisition and retention are more manageable when you target groups, not just individuals.
Education is no different. A person taking a course is far more likely to recommend it to their partner, kids, and friends. Learning isn’t an isolated activity. So why aren’t more platforms creating learning bundles for families? Why aren’t universities offering continuous education memberships that extend beyond just alums?
If EdTech companies want to stop fighting for one-off enrollments and start building sustainable businesses, they must rethink their entire model.
AI Co-Pilots for Course Creation
Let’s also discuss the other side of learning – content creation. Right now, educators and instructional designers are flying blind. They receive minimal feedback beyond completion rates and maybe quiz scores. But that’s like designing a product without user testing.
What if we had AI-driven course co-pilots that analyzed real learner behavior and provided actionable insights?
- Notice that 80% of learners drop off in Module 3? The system flags it for review.
- Found that a specific quiz question has an unusually high failure rate? The system suggests rewording it.
- Learners keep rewatching a specific video segment. That content might be particularly valuable – or particularly confusing.
If we’re serious about using data in education, we must treat content like a living, evolving product.
Continuous Course Improvement: The Living Learning Product
The learning course itself is at the heart of education – a constant truth. This is the core product, the vessel of value transferred to learners. However, in our current EdTech landscape, courses are treated as static artifacts rather than dynamic, evolving experiences.
Courses must continuously improve based on comprehensive, real-time analytics. They should adapt based on learner feedback, detailed interaction data, and emerging contextual requirements. For instance, compliance courses must be immediately updated when regulations change, ensuring learners have the most current information.
Today, this improvement process is painfully manual. Instructional designers rely on minimal data, sporadic student surveys, customer feedback, and basic intuition. The result? A slow, inefficient process that fails to keep pace with rapidly changing learning needs.
In the modern world, a course must become a self-evolving system powered by complex, real-time data analytics. This doesn’t mean blind algorithmic changes but a transparent, curated approach with traceable reasons for modifications. Course evolution should maintain human oversight while leveraging advanced technological capabilities.
This isn’t a futuristic fantasy. The technical infrastructure to create such adaptive learning systems already exists. We need the will to break free from outdated EdTech paradigms and embrace a more intelligent, responsive approach to course design.
EdTech Needs to Evolve… or Be Replaced
EdTech is at a crossroads. Platforms can either continue using outdated tracking methods and rigid course structures or embrace real-time, AI-driven, data-powered personalization that competes with modern digital experiences.
Education is a lifelong journey. It’s time for EdTech to start acting like it.
If learning platforms don’t evolve, they won’t just fall behind – they’ll be replaced.
