Data Mining from Canvas to Enhance Study Tools – UROP Spring Symposium 2022

Data Mining from Canvas to Enhance Study Tools

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Siddharth Parmar

Pronouns: he/him

Research Mentor(s): Perry Samson
Co-Presenter:
Research Mentor School/College/Department: Climate & Space Sciences & Engineering / Engineering
Presentation Date: April 20
Presentation Type: Oral5
Session: Session 3 – 1:40pm – 2:30 pm
Room: Breakout room 3
Authors: Siddharth Parmar, Perry Samson
Presenter: 6

Abstract

Stress is a major problem affecting students today. The ongoing pandemic has exacerbated the mental health issues that many college students face nationwide. It has also marked a time of falling college enrollments. At such a time, the importance of streamlining the learning process is apparent. The human mind is a wonderfully powerful tool but it has limited resources. Having to account for multiple tools and tasks leads to added mental load which could compound existing stress. Our project seeks to act exactly on that. It is a study tool that integrates with existing platforms that host course content. It collates, collects, and analyzes all of the course data; it uses this to automatically generate study resources that are relevant and helpful. Here, it helps the student by cutting through the clutter and giving them one avenue to make sense of everything presented to them. The pandemic also saw the addition of infrastructure to enable virtual learning. More and more courses are incorporating recordings to help make content more accessible to students. One current issue is that of referencing recorded content. Our project also remedied this problem by providing a search engine that provides any user with instances within recordings of the occurrence of any search tool. Thus, this project can be characterized as an ambitious endeavor to solve major problems that students face today. Currently, the search engine has been implemented and integrated with Canvas at UM. The study resource generation is currently in progress.

Presentation link

Engineering, Interdisciplinary

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