Audrey Chen¹ and Victor Phan², ¹USA, ²California State Polytechnic University, USA

Tutoring is not a commonly available service for middle and high school students who often have to learn the toughest subjects in the K-12 education system [1][2]. This can negatively impact their learning and cause losses in opportunities that could have been avoided. In response, we suggest a mobile application that is able to assist students in their learning as well as help them educate others so that all students can learn together [3]. This application uses the Flutter framework as well as Google's Firebase service to store user-generated data [4]. An AI recommender system as well as a subject assignment system is hosted on a Python Flask backend server [5]. It will determine what questions someone should look at, as well as what kind of subject a question seems to be, respectively. These systems rely on an AI that uses natural language processing. To test the effectiveness of our application, we devise two experiments. In the first experiment, we determine the accuracy of our subject assigner by giving it several mock questions. In our second experiment, we compare and contrast different recommender systems. Ultimately, our subject assigner is at 50% accuracy and the recommenders we used were roughly the same in accuracy. Overall, this application is polished and with some more improvements to the backend and AI integration, it will be a useful tool for students who need an extra boost in school.

Education, Database, Natural Language Processing, Machine Learning