Online Learning Platform Development: Build Comprehensive e-Learning Solutions

Meanwhile, a good LMS is mostly about organizing the eLearning process – delivering content, tracking course completion, meeting compliance requirements. This, too, can become limiting under some circumstances. And that’s where you really need a full-fledged online learning platform:

• when there are multiple courses and audiences (not just segments or cohorts for a single course)
• when there are multiple authors who need to be able to work independently
• when you need more user roles and role-based experiences
• when the analytics need to capture not just learner performance but also course popularity/efficiency, content types, etc.
• when personalization and adaptive learning are desirable.

Multi-course platforms

The broadest and most popular type is a multi-course platform that is built around hosting (and managing) multiple courses at once, oriented towards different audiences. The name of the game here is growth: possibility to create and manage more and more content, organizing it (as well as the authors who post it), versioning, and so on – while features like enrollment, progress tracking and reporting are added according to the philosophy defined by this general scaffold.

Skill- or competence-oriented platforms

The traditional way of looking at the learning process is that there’s a rigid course, consisting of lessons and content that’s to be consumed in a particular order. However, this is not always efficient, since the users may already know some parts of the course and just waste time “running” through the respective units. This is where skill-based platforms come in handy: they organize learning around modular skillsets, measure competencies in those skills and recommend targeted activities to close the gaps with adaptive pacing. While trickier to implement, they are also more effective.

Marketplace & multi-author eLearning platforms

eLearning “marketplaces” allow multiple instructors/experts, partners, or organizations to post learning content within the same ecosystem, sometimes with monetization possibilities. Accordingly, they include author management, moderation workflows, and a bigger accent on course discovery features.

AI-driven & adaptive learning

AI is now entering wide use for personalization purposes. If the supposed user environment is expected to generate a lot of data as a byproduct, building an AI-powered platform can be an excellent idea. Artificial intelligence can analyze both learner behavior and assessment results, as well as other patterns, and adapt content sequencing, recommendations, etc. to formulate individual adaptive learning paths for each learner.

Learning goals → features (not vice versa)

Building on our previous experience in EdTech development, as well as the pedagogical background many specialists in our development team have, we always think in terms of what the learners are supposed to experience and receive, rather than delivering features for their own sake. In this way, the solution you get does exactly the things it is expected to, and every feature is there for a reason.

Architecture with scalability in mind

Modern platforms operate in shifting learning environments, where the audience, content, roles, instructor roles – basically anything – can change. Accordingly, we prioritize scalability potential when making architectural decisions, saving future effort and investment.

Customizability over rigid customization

It is tempting to suggest custom development for unique business visions, but hardcoding niche features is not the best approach when working with learning platforms – simply because things here change quite a lot. That’s why we always leave the wiggle room for further customization, even when the solution we are working on is already highly tailored.