Back on Track

Back on Track is an AI-powered academic recovery system that helps students organize tasks, track deadlines, manage study materials, and turn academic overload into a clear action plan.

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Inspiration

Back on Track was inspired by my own school experience. In our school, there were many situations when students came to class and suddenly realized that they had forgotten about an important assessment or assignment. Someone would ask, “Is the summative assessment today?” or “Do we have English speaking today?” Sometimes the information had been shared earlier, but it was lost inside long class chats, separate messages, or different platforms. Another problem was that study materials were scattered everywhere. Some files were in Google Drive, some were sent in WhatsApp, some were in Telegram chats, and some information was only written in messages. Because of this, students often wasted time just trying to find the right file, deadline, or instruction instead of actually studying. I also experienced academic overload myself. When there were many assignments and deadlines at the same time, I often did not know where to start. A normal list of tasks was not enough because it did not explain what was urgent, what could wait, or how to recover when I was already behind. Before building the project, we also conducted a student survey to better understand whether other students faced the same issue. The responses showed that many students struggle with organizing schoolwork, remembering deadlines, finding materials, and deciding what to do first when tasks pile up. That is why we created Back on Track: a platform where students can keep everything connected to their learning process in one place and receive structured AI support when they feel overwhelmed.

What it does

Back on Track is an AI-powered academic recovery system for students. It helps learners organize classes, tasks, deadlines, study materials, reminders, topic explanations, suggested tasks, and recovery plans in one platform. Students can register, log in, and join a class using a unique class code. This keeps their tasks and materials connected to the correct learning group or subject. Students can add tasks with titles, descriptions, notes, and deadlines, and the system tracks whether each task is pending, completed, or overdue. The platform also includes a reminder system that highlights approaching deadlines, helping students avoid missing important work. Back on Track also allows students to upload study materials by subject. After a material is uploaded, the system can help explain the topic and suggest useful tasks based on the content. This turns scattered files into organized study actions. The main AI feature is the academic recovery plan. When a student has several unfinished tasks, Back on Track analyzes their pending work, deadlines, notes, task types, and available study time. Then it generates a structured plan showing what to focus on first, how much time it may take, and why each step matters. Instead of giving general advice, Back on Track gives students clear next steps.

How we built it

We built Back on Track using PHP, MySQL, HTML, CSS, JavaScript, and Composer. The backend handles user authentication, class joining, task management, deadline tracking, study materials, reminders, and AI request processing.

For the AI workflow, we integrated the OpenAI API. The system collects task-related academic data from the database, formats it into a structured prompt, sends it to the AI model, receives a structured response, and displays the recovery plan to the student.

We also built an AI caching system to reduce repeated API calls and make the project more efficient and cost-aware.

Challenges we ran into

One challenge was making the project more useful than a simple task list. Students do not only need a place to write tasks; they need a system that helps them understand what to do first, where their materials are, and how to recover when they feel behind. Another challenge was making the AI output practical instead of vague. A general chatbot response would not be enough for students with real deadlines. We needed the system to produce structured, realistic, and useful guidance. We also had to connect many parts of the platform: authentication, classes, unique class codes, tasks, deadlines, reminders, uploaded materials, topic explanation, suggested tasks, database storage, and AI recovery planning. Finally, we had to think carefully about responsible AI. Since the project supports students, the AI should not replace teachers, parents, counselors, or the student’s own judgment. It should only provide guidance while keeping the human in control.

Accomplishments that we're proud of

We built Back on Track as a complete academic support platform, not just a task manager. It combines classes, assignments, reminders, study materials, and AI recovery plans in one place. We are proud that it solves a real student problem: missed deadlines, scattered materials, and academic overload. We also designed AI responsibly—it helps students with guidance and planning while keeping the student in control.

What we learned

We learned that AI works best when combined with a clear workflow, not just as a chatbot. We gained experience with authentication, databases, task management, file uploads, reminders, and AI integration. Most importantly, we learned that responsible AI should support decisions, not make them for users.

What's next for Back on Track

-Full multilingual support (except English, Russian and Kazakh) -Mobile application -Calendar and deadline synchronization -More personalized AI recovery plans -Smarter reminders and notifications -Progress analytics and tracking -Teacher and mentor dashboards -Better study recommendations -Improved collaboration tools -Enhanced accessibility and user experience Our goal is to make Back on Track a complete academic recovery platform that helps students organize, understand, and complete their work more effectively.

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