This page lists the projects of the innaugural 2018 session of the REU at GMU.
Project 1: MOOC Visualization/Analytics
Mentors: Dr. Huzefa Rangwala, Jessica Lin and Jill Nelson
Mentees: Jason Baik, William Cho
Develop a system that builds a visual dashboard for instructors and administrators. Data will be used from server logs of 5 MOOC classes obtained from Stanford Edx initiative and KDD Cup Dataset.
- Specific tasks will involve using a frequent mining algorithm to identify common sequential patterns of interaction with a MOOC.
Project 2: In-class Prediction Analysis
Mentor: Dr. Huzefa Rangwala and Aditya Johri
Mentees: Co Tran, Rachel Witner
- model student learning within class for grade prediction using regression/deep learning on LMS data
- develop a visual analytics dashboard to help instructor provide patterns of success
- develop an early warning system for identifying students' survival in class
- Dataset to be used: Canvas Network Dataset
Project 3: Teaching Programming Strategies
Mentor: Dr. Thomas LaToza
Mentees: Efe Ozturkoglu, Andrea Solis
- document programming strategies and see how crowd-programming can be usedful for learning.
- build a system for crowdsourcing strategy refinement
- Intelligent Autocomplete
- Investigate differing models of documents, evaluate performance
- build a tool that explains models back to the user
Project 4: Raising #STEM Awareness
Mentor: Dr. Aditya Johri and Hemant Purohit
Mentees: Byron Biney, Olivia Kruse
- analyze twitter metadata about specific stem-related hashtags to determine who participates
- what kinds of messages are being shared
- what kind of networks form within and across hashtags
- build predictive models forecasting trends in STEM Awareness
Project 5: WELI: Assistive Wearables for Neurodiverse Students in Higher Education
Mentor: Dr. Vivian Motti
Mentees: Mia Cornwell, Kelly Glebus
- track data on neurodiverse students receiving guidance during lectures via wearables.
- develop analytical models for identifying interventions.
- develop analytical models for determining success.
Project 6: Anomolies Detection
Mentor: Dr. Carlotta Domeniconi
Mentee: Jad Rayes
- focus on the discovery of anomalies in graphs - how to properly construct graphs from data, the impact of different similarity measures among actors/entities, how to leverage attributes in graphs
- graphs vs hypegraphs: do hypergraphs help? how to represent hypergraphs?
- use insider trading data collected from publicly available data, and already processed as graphs