Study Scheduler

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Inspiration

We noticed that many students struggle to manage their study time effectively, especially when juggling several subjects with different workloads. Traditional planners can feel overwhelming or inflexible, so we wanted to build a tool that creates a structured weekly timetable automatically—one that adapts to each student’s availability and study requirements.

What it does

The system generates a personalized weekly study timetable based on two main inputs: the student’s availability for each day and the number of papers or tasks they need to complete in each subject. It distributes study sessions proportionately, prevents overload on any single day, and ensures that each subject receives appropriate attention. The final output is a clear, optimized weekly timetable that students can follow with ease.

How we built it

We designed the system with a simple yet effective workflow:

Collected user inputs for daily available hours and subject workloads

Built a scheduling algorithm that allocates study sessions throughout the week based on workload distribution

Implemented logic to prevent exceeding daily availability

Created a user-friendly interface (CLI/web/app—adjust as needed) to visualize the final timetable

Added customization options such as priority subjects and adjustable session lengths

We used AI to help us code all the files and make descriptions.

Challenges we ran into

Some of the challenges included:

Balancing workloads fairly across the week

Handling days with very limited availability without creating gaps in the schedule

Ensuring the algorithm could adapt to many different study patterns

Designing a clean and intuitive way for users to input their availability and workload

Accomplishments that we're proud of

We’re proud that we built a tool that genuinely helps students stay organized and reduce stress. Our scheduling logic is flexible, reliable, and able to handle a wide range of inputs. The interface is user-friendly, and the final timetable feels practical and easy to follow.

What we learned

We learned how to design and refine scheduling algorithms, how important user experience is in time-management tools, and how small interface decisions can make a big difference in how approachable a tool feels. We also gained experience in turning real-world problems into clean, solvable technical challenges.