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