EzberX
EzberX
App Design
App Design
I
I
Wireframe, Prototyping
Wireframe, Prototyping
I
UX Research, UI Design
UX Research, UI Design
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I
Logo Design
Logo Design
EzberX is a gamified English vocabulary learning app designed to make word memorization more engaging through interactive mini games.
EzberX is a gamified English vocabulary learning app designed to make word memorization more engaging through interactive mini games.
The goal is to help users strengthen their vocabulary and spelling skills in a fun, challenging, and dynamic environment.
The goal is to help users strengthen their vocabulary and spelling skills in a fun, challenging, and dynamic environment.
Draggable
Project Explain
Objective
Objective
The main objective of EzberX is to transform traditional vocabulary learning into an interactive experience.
The main objective of EzberX is to transform traditional vocabulary learning into an interactive experience.
Using AI tools such as Cursor and Claude, the entire process from design to development was carried out collaboratively with AI. The app introduces a multi-level learning system where difficulty, speed, and gameplay variety adapt to the user’s progress.
Using AI tools such as Cursor and Claude, the entire process from design to development was carried out collaboratively with AI. The app introduces a multi-level learning system where difficulty, speed, and gameplay variety adapt to the user’s progress.
Each mini-game focuses on a different aspect of language learning: matching, spelling, and typing.
Each mini-game focuses on a different aspect of language learning: matching, spelling, and typing.
Process
Process
The app was designed in stages, starting from concept sketches and UI prototyping in Figma to functional development in ReactNative.
The app was designed in stages, starting from concept sketches and UI prototyping in Figma to functional development in ReactNative.
AI-assisted generation was used to create the word dataset, categorized by CEFR levels (A1–C2).
AI-assisted generation was used to create the word dataset, categorized by CEFR levels (A1–C2).
The gameplay logic and UI interactions were built iteratively focusing on seamless transitions, visual feedback, and responsive animations.
The gameplay logic and UI interactions were built iteratively focusing on seamless transitions, visual feedback, and responsive animations.
Outcome
Outcome
WordMatch:
WordMatch:
Match English and Turkish cards correctly within the given time. Wrong matches trigger visual feedback, while correct pairs disappear with an animation and are replaced instantly.
If the user collects enough points within the time limit, they progress to the next stage where the timer shortens and the difficulty increases
Match English and Turkish cards correctly within the given time. Wrong matches trigger visual feedback, while correct pairs disappear with an animation and are replaced instantly.
If the user collects enough points within the time limit, they progress to the next stage where the timer shortens and the difficulty increases
SpellRush:
SpellRush:
A spelling recognition challenge. The player is given a Turkish word and must identify its correct English spelling among similar-looking options. As stages progress, the word complexity increases and the time allowed decreases pushing the user’s focus and precision.
A spelling recognition challenge. The player is given a Turkish word and must identify its correct English spelling among similar-looking options. As stages progress, the word complexity increases and the time allowed decreases pushing the user’s focus and precision.
TypeRush:
TypeRush:
Words appear sequentially on the screen, and the user types them as quickly and accurately as possible. Each correct word increases the counter, and the goal is to type as many correct words as possible before the timer ends. Higher levels introduce longer and more complex words with reduced time limits.
Words appear sequentially on the screen, and the user types them as quickly and accurately as possible. Each correct word increases the counter, and the goal is to type as many correct words as possible before the timer ends. Higher levels introduce longer and more complex words with reduced time limits.
EzberX successfully combines language learning with fast-paced game mechanics. Instead of static memorization, users improve their reflexes, spelling accuracy, and vocabulary retention in an engaging way.
EzberX successfully combines language learning with fast-paced game mechanics. Instead of static memorization, users improve their reflexes, spelling accuracy, and vocabulary retention in an engaging way.
The project demonstrates how AI tools can support the full product lifecycle from concept ideation to deployment. Future versions will include daily challenges, word progress tracking, and AI-generated adaptive word lists.
The project demonstrates how AI tools can support the full product lifecycle from concept ideation to deployment. Future versions will include daily challenges, word progress tracking, and AI-generated adaptive word lists.
