How to Develop a Great Ed-tech Product for Young People An ed-tech product needs to fill a clear gap in the market in an efficient and effective way
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Learning has become ubiquitous today. Propped up by technology, it has gone beyond traditional classrooms to digital devices, democratizing education along the way. However, mere availability does not ensure adoption as an ed-tech product needs to fill a clear gap in the market, and more importantly, do it in an efficient and effective way.
Here's a step-by-step guide to building a great ed-tech product.
While this step may seem deceptively simple, it is doubtless the most critical exercise that forms the bedrock for how one builds a product. Treating this subset of the population as broadly divergent—and not as a homogenous group—has been a great learning in this drill. Arriving at a parity between all these aspects when working out an audience has been a challenge, and continues to be so.
It is simply not enough to profile users at the product-building stage. It is just as imperative to continue the audit process even after its launch. This invariably throws up new insights which begets content modifications and can be helpful in framing its distribution.
Borrowing from experience, there is a tendency to operate with the assumption that the audience —here, comprising mostly of students from disadvantaged backgrounds—would prefer content in their local languages. But it was a surprise to know that learners struggle with reading and writing in their native languages. Moreover, understanding English—although an issue—is still a priority among these students. They are also new to digital interactions and have sporadic access to Internet. These were insights picked up during daily audits, spurring alterations to the product.
Content that is prioritised and which finally make the cut is borne out of a company's vision. Choosing what is relevant in terms of course material is an internal decision for each company; the form it takes is often the challenging part. Content strategy is created by reorganising and reinterpreting the vast pool of learning material.
It is a good practice to break down complex ideas into smaller nuggets. More importantly, a storytelling approach ensures a wholly immersive experience. It is a good practice to sort content into modules, break it down into lessons and build each narrative by extrapolating situations and characters from the average learners' socio-economic context for greater relatability. A conversational and friendly narrative tone also makes the overall experience interactive and inclusive.
However, working on byte-sized content has challenges as to be able to explain the concept within minutes, to make it non-theoretical and keep learners engaged at the same time is no mean feat.
Often, an analysis of a course's target audience and content lead to the creation of the fundamental design principles for the same.
Designing each lesson calls for creating content outlines, scriptwriting, illustrations, animations, typography and sound design. Guides and templates should be devised so that multiple designers and illustrators can collaborate and meet a project's tight timelines.
The use of voiceovers works well and its impact on a learner cannot be emphasized enough. A good quality and professional voiceover can, for example, impact the engagement with the lesson and improve the learning manifold, as opposed to just being a means to explain the content.
Another learning has been the choice of publishing software. This should be thought through from a long-term perspective. Once content is created using one, migrating to another that has greater capabilities is not easy. Also, even if one wants to work with newer publishing tools, the pace of this adoption depends on how ready one's ecosystem is to adopt it as well. This includes internal or external technology, content team as well as learning communities. Their readiness and skillsets are very critical.
This is usually followed by prototype-based testing to assess the output for usability and to ensure that the textual and visual language will be understood by various users. How should this be done? When one module is completely designed, it should be tested with learners to take decisions regarding the visual style, level of language complexity and nature of digital interactions. This helps to ensure that the abstraction of ideas into visuals becomes legible and visual interpretations of recurring words such as "interests', "abilities', "self', among others, are relatable.
One big learning has been that it is not enough to get insights from the field and implement them. What ultimately blurs the line between an average product and one that successfully goes on to achieve its purpose is the effort of going back to the audience multiple times after the feedback has been incorporated to validate its effectiveness. This is a foolproof way of checking the progress of one's product.
Data becomes the window to evaluate the progress of one's product. This includes determining completion rates of modules, the range of scores awarded as well as the degree of engagement recorded, including frequency of users as well as average time spent on the platform.
And while technology makes it possible to draw a lot of data on user activity and the learning outcomes, it is not a substitute to engaging and interacting with users on the field to see the real-life impact it's bringing. It also helps in identifying gaps in the system and thereby getting a clearer idea of what the future of learning really is.