Case Studies

Building an age algorithm app
Developing an adaptive algorithm to assess children’s vocabulary age and personalise learning activities within a children’s language learning app.

Building a vocabulary age algorithm for a children’s learning app

The app is a mobile platform designed to rapidly develop children’s vocabulary through fun, fast, and personalised activities. By combining engaging gameplay with dynamic rewards, the app helps children strengthen their language skills and build confidence in communication.

The challenge

The client wanted to enhance its app experience with a more adaptive and personalised approach to vocabulary learning. The goal was to create an algorithm capable of identifying a child’s “vocabulary age” based on their performance across a variety of puzzles and activities, ensuring that content remained challenging yet achievable.

Our approach

Elemental Concept developed a custom algorithm that assessed and adapted to each user’s ability level through two key phases:

  • Initialisation phase: The algorithm calibrated the user’s starting vocabulary level by analysing performance across activities and puzzles. The algorithm then identifies the level where the user is most comfortable
  • Learning phase: Once the starting level was determined, the system dynamically adjusted question difficulty and pacing. Users received a balanced mix of questions, ensuring both reinforcement and gradual challenge. Scores were weighted by difficulty, and users advanced only after achieving a target cumulative score.

Each level directly corresponded to a vocabulary age, visible within the app, providing both feedback and motivation for continued progress.

Before deployment, Elemental Concept tested the algorithm to confirm accuracy in how questions were served and to simulate how users with varying learning abilities would progress through the platform.

The results

The new adaptive algorithm transformed the app into a more intelligent and responsive learning platform. By aligning difficulty with individual performance, it provided a tailored learning journey for every user, promoting steady vocabulary growth, maintaining engagement, and ensuring measurable educational value.

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