Case study · № 002 · Mobile EdTech
BKÖRKORTSTEORI · learn the road, rehearse the test
A multilingual mobile learning product that carries drivers from theory chapters through focused practice, realistic timed exams, review, and AI-supported coaching.
The product problem
Driving-theory preparation is not one quiz. Learners need structured reading, category-specific practice, an exam-like test environment, explanations after mistakes, and a clear view of what to study next. The product also has to serve learners across languages and text directions without fragmenting the experience.
The mobile system
- Theory curricula organized by vehicle and licence category, chapter, and topic.
- Relaxed chapter practice plus timed, scored mock exams with flags, review, summaries, and category breakdowns.
- An in-question AI tutor grounded in the answered question and official explanation.
- Weak-area analysis that turns completed sessions into targeted chapter practice and optional streamed coaching.
- Speech playback for questions and answer options with locale fallbacks.
- Six localized interfaces—Swedish, English, Urdu, Norwegian, Danish, and Hindi—with RTL-aware layouts for Urdu.
- Authentication, reset-password deep links, plans and entitlements, study guides, progress history, daily streaks, and reward milestones.
Decisions that mattered
Teach, rehearse, then diagnose. Theory, practice, mock exams, review, and weak-area coaching form one learning loop rather than separate features.
AI appears after evidence. The tutor is enabled after an incorrect practice answer, so its response can be grounded in the exact question, choice, and official explanation.
Localization changes layout. The interface handles native labels, country context, speech-language fallbacks, and right-to-left behavior instead of treating translation as string replacement.
Device interruptions are exam state. Timers reconcile with server time and app foreground changes so a mock test remains credible when the app is paused or resumed.
Evidence boundary
The supplied mobile repository establishes the product surface and implementation details, and its owner identified Hashaam as the developer. The archive does not include Git metadata, so individual commit history, team boundaries, dates, store release status, learner counts, and performance outcomes are intentionally not claimed. Production notes also show that some release integrations still require final configuration.