As a student who most likely has ADHD (has common symptoms, although not diagnosed), I have developed poor study habits in my college courses. Starting assignments, studying for exams, or completing daily tasks often prove challenging. It has become overwhelming to me juggling with work and life as well. I tried numerous methods to combat my procrastination and poor study habits, but all of them seemed to be temporary. I would have to create a whole system for me to pick which method I should go for, at what day, and at what time of the day. I couldn’t keep up the consistency which resulted in poor time management, late nights and late assignments, and barely making time to study for exams. I’m not alone here. Numerous friends I know struggled with the same thing. So, I decided to make a change. I’m sure there are numerous solutions to these problems, but as a college student, I wanted to make sure I made the right financial decisions investing in something I WILL use every day to build better study habits. Most of my purchases didn’t go too well. I tend to be distracted by other mobile apps, or the apps are too overwhelming to use, and those would lead me to procrastinate in most study sessions. I wanted to make a lightweight version of a service that lets me use popular tools while creating an effective impact on my study sessions. In the age of generative AI, there’s no better time to implement them to understand my patterns, peak productivity, and which study method works for any occasion. This led to the birth of PSA.
What it does
PSA (or personalized study assistant) is a system that helps you make good study habits, discover your peak productivity times, identify effective learning preferences, and create an optimized study plan tailored to your needs. Essentially, you are building a relationship with your assistant; you give your input, and the PSA will help you view your best strengths. The whole template is self-guided for the most part, but here is the overview of each important page.
Welcome text and a brief overview of what the template is about. Instructions on how to use the template and Coda.io's AI features.
Peak Productivity Log
A table where users can input their productivity levels at different times.
Learning Preferences Log
A table where users can input their studying strategies and rate their effectiveness. An AI Block that generates different studying strategies and instructions on how to utilize it.
A table where users can input their study tasks, expected time for completion, and deadline. An AI Assistant that adjusts the study schedule based on the peak productivity times and preferred studying strategies.
Insights & Summary
This page uses AI Blocks to summarize key insights from the productivity log and learning preferences log.
How I built it
For this hackathon, I made this project with Coda.io and Coda AI-enabled tools. This is the first time me using Coda in general. I watched some basic essentials made by Maria Marquis and went to an info session Rocky Moon did the quick training.
With my previous knowledge of spreadsheets, database systems, prompt engineering for the backend, and ChatGPT to handle the front side of the project and created mock data.
Challenges I ran into
Originally, my first idea was to create a “super” interactive, adaptable, and personalized productivity tool for students based on their input. Although building it would be easy due to the AI tools, it would take a lot of tinkering with the AI tools to create a perfect prompt to generate a template. So instead of evolving from creating this super tool, I changed the perspective a bit. I made this whole system more of an experience for the user and built a relationship with the assistant, so it can understand the user and the user will understand a bit more about themselves in studying. The tools are still added as smaller features and it fits well with being accountable and actually doing the study tasks.
Accomplishments that I’m proud of
Was able to make an MVP in under a week. The seamless integration of various productivity tools within the planner, like time trackers, productivity logs, and study logs, makes it an all-encompassing solution for students. The implementation of AI in this project is quite innovative. It not only automates the analysis of productivity data but also offers valuable insights that help optimize the study schedule. Despite its sophisticated functionalities, I made sure the planner is user-friendly, ensuring that students of all tech-proficiency levels can utilize it to improve their study routines. This tool specifically addresses the needs of students with ADHD by providing structure, predictability, and personalization, which are key to managing this condition. The tool's ability to adapt to each student's individual learning preferences and productivity patterns can significantly enhance their ability to focus and succeed academically.
What I learned
No size fits all. Everyone has different struggles studying. I had to research and understand the specific challenges these students face (even myself), and I saw how personalized productivity tools can help address these challenges. I dealt with various aspects of data management, such as collecting data, working with time-series data, and using that data to generate AI-driven insights. I learned to maintain a strong focus on the end user throughout the design and development process. This was key to creating a planner that is both highly effective and easy to use. This project gave me the chance to dive deep into the integration of AI tools with productivity platforms. I saw firsthand how AI can automate data analysis and offer personalized insights. I have gained hands-on experience with no-code platforms, furthering my understanding of their potential and learning to work around their limitations. In the process of creating this tool, I have learned to manage a complex project, working through various stages from ideation, design, and development, to testing and iteration.
What's next for PSA: Personalized Study Assistant
In the future for PSA, the sky is truly the limit! As it stands, this project is in the MVP stage, a proof of concept showcasing the potential of AI-assisted planning for students with ADHD.
I'm enthusiastic about adding more features such as integrating new productivity tools to track student progress more comprehensively, developing a feedback system for students to refine AI suggestions, and even considering the prospect of expanding this into a full-fledged SaaS platform for broader audiences.
But the key to any product's evolution is user feedback. As more students use and provide feedback on PSA, we can fine-tune it to meet their unique needs even better.
Investment and interest in this project would certainly accelerate its development, and I am excited about the prospect of driving PSA forward. However, as a software development student, I'm also keen to explore other projects and challenges. Whichever direction the journey takes me, I'm looking forward to applying the invaluable lessons learned from building PSA to my future endeavors.