Aqute v2
A podcast app with per-episode comprehension quizzes — background playback, local favorites, and a scored quiz history
A Flutter podcast app: search and browse a live third-party podcast catalog, play episodes with a persistent background audio player and lock-screen controls, and — for episodes carrying an authored quiz in Firestore — take a scored multiple-choice comprehension quiz with instant right/wrong feedback. Favorited shows and completed-quiz scores are tracked locally on-device, browsable later in a dedicated quiz-history screen.
Source is private. The per-episode quiz schema, the offline score history and the background-audio stack are explained below.
About this project
The app is built around one loop: find a podcast, follow it, listen, and — where a quiz exists for that episode — get tested on it. Podcast and episode data (search, a best-podcasts chart, podcast/episode detail) is pulled live from a third-party podcast-data API rather than a proprietary content backend. Audio plays through a dedicated background-audio stack (audio_service + just_audio, with lock-screen/notification controls) and a persistent mini-player keeps the current episode visible while the user browses the rest of the app.
Quizzes are authored per episode: questions are stored per podcast/episode in a nested Firestore collection, fetched when the user opens an episode with a quiz attached. Each question renders as four radio-button options in bordered cards; submitting an answer flips the selected and correct options to red/green in place, a back/next flow steps through the question set, and a finish screen totals the score. Completed quizzes and their scores are written to a local SQLite database (alongside a separate table of favorited/subscribed podcasts), so the app's 'Your Quizzes' screen and 'My Shows' list both work fully offline against on-device data rather than round-tripping to a server on every open.
My part covered the mini-player integration, stabilization passes and the quiz answer-selection flow.
Key features
- Live podcast search, a best-podcasts chart, and podcast/episode detail pulled from a third-party podcast-data API — not a static or seeded catalog
- Background-capable audio playback (audio_service + just_audio) with lock-screen/notification controls and a persistent in-app mini-player
- Per-episode comprehension quizzes authored in Firestore: four-option multiple choice, instant red/green right/wrong feedback per question, a back/next flow, and a scored finish screen
- Local SQLite persistence for favorited/subscribed podcasts and completed-quiz scores, powering a fully offline 'My Shows' list and a 'Your Quizzes' score-history screen
- Firebase Analytics wired with a navigation observer, tracking screen views across the app
More in Education
Learning Management System
AI-assisted coaching platform — student app, admin console, and a multi-provider AI backend
A Flutter learning and personal-development platform built as a student app and an admin console over one Firestore backend, with an in-app AI assistant — chat, per-lesson summaries and recommendations — powered by a dedicated OpenAI/Gemini/Groq backend with vector search over the course library.
School Management Suite
Three coordinated apps, one shared backend
A school-management platform built as three coordinated Flutter apps — a student/parent app, a teacher professional-development app and a staff operations app — sharing account and content infrastructure, with a standalone AI prototype exploring automated student-performance summaries.
VU Helping Kit
A timed Firestore quiz engine, PDF handout library and study-group directory for distance-learning students
A solo-built Flutter app for Virtual University of Pakistan students: a category-driven quiz engine pulling randomized, timed questions from Firestore, plus browsable handouts, past papers and assignment solutions delivered as cached PDFs, alongside a WhatsApp study-group directory and video-lecture links.
~/sherazi.dev$./say-hello
Say hello.
Questions about a case study, one of the packages, AI tooling or Flutter in general are always welcome.
// or browse the packages on pub.dev(opens in a new tab)