StudyBuddy: A Voice-based Studying Assistant

Fariha Pia, Umaid Ali, and Dr. Daehan Kwak School of Computer Science and Technology, Kean University, Union, NJ 07083

The term "academic success" is one that every student is familiar with. From striving for academic success to being expected to achieve it, this concept is the ultimate goal for many students and teachers. One way to achieve academic success is through effective study habits. Flashcards are a common study habit used to self-test while retaining information and strengthening weak spots within the studying material. Prior research has shown that repeated testing exhibits better retention and higher marks on the final test than repeated studying. 

This study examines the effectiveness of self-testing online flashcards via a virtual voice assistant and solely reading materials. Research has shown that speaking aloud is beneficial when it comes to retaining information. In this research, an app developed to create online flashcards will be integrated into the Google Home virtual voice assistant using Google’s FlashCards Action template. Google’s FlashCards Action template includes a customizable Google Sheets where users input questions and answers which is designed and integrated onto the Google Home Assistant. With the machine learning model created, the virtual voice assistant will extract data from the flashcard app and test the user. The app will offer a friendly user interface for students to utilize Google Home Assistant’s actions more conveniently and transform the way students self study with a conversational experience with additional features. To measure the effectiveness of the proposed voice-based flashcard app, the experiment is conducted as follows; There will be twenty participants that will be given a historical article, one group of ten will self-study using the article, while the other half will be given the same reading material in addition with an online flashcard set. Both groups will be tested with ten multiple-choice questions. The data will be measuring correctness and the duration of completion.

Additional Abstract Information

Presenters: Fariha Pia, Umaid Ali

Institution: Kean University

Type: Poster

Subject: Computer Science

Status: Approved

Time and Location

Session: Poster 5
Date/Time: Tue 12:30pm-1:30pm
Session Number: 4028