The Unit11 team initially designed and created this app before the company employed me. The team developed it using standard web technologies and Cordova to allow for cross-platform mobile development.
RobbResearch Ltd assigned me to recreate them using the Unity engine after NetEase's education subsidiary Youdao selected these apps for release in the Chinese app market.
I fundamentally rewrote the structure and code of these apps for the Unity version, leaving the artwork and audio mostly unchanged. As Apple hadn't released higher resolution devices at the original publication time, I did need to replace some low-resolution artwork. I designed the improved art to match the look of the original where possible.
Spelling Assistant's aim was for children to practice and plan for their class spelling tests easily and enjoyably. The main functionality needed for the app was the ability for the user to create custom word lists and record themselves speaking the words.
Another key feature of the app was using the native text-to-speech systems on iOS to read out any custom word that did not have a user recording. The real-time speech meant that a user could quickly add a list of custom words and pronounce them when playing the game.
I implemented my Modular Framework for Unity which served as the structural base of the app. I designed each game mode to retrieve local JSON word lists and respond to the content, which meant that we could implement further development and manageable word changes in the future if desired.
I utilised my generic modular system for user accounts to let multiple family members store personal word lists and individual progress on the same device.
The gameplay mechanics are simplistic and designed to be approachable and intuitive, carefully designed to offer a smooth difficulty curve.
The first and easiest practice game mode selects a random word from the list and jumbles it, requiring the user to demonstrate that they recognise the target word to put it back together.
The second game mode proposes three different spellings for a word, and I achieved this using a partial string replacement algorithm that detects letter patterns.
The third practice mode required the user to listen to the word and then spell it out using a custom on-screen keyboard with extraneous characters removed.
The user can explore any of these game modes and complete them as many times as they desire. Once they feel confident enough to take the test, they are presented with a full on-screen keyboard and asked to spell each word in their custom word list.