IQP and MQP
At WPI, all students engage in meaningful, interdisciplinary, project-based learning experiences. In their junior year, students complete an interdepartmental project that is outside their primary area of study. In their senior year, students complete a second project that is within their major. The junior year project is called their Interactive Qualifying Project (IQP), while their senior year project is called their Major Qualifying Project (MQP). Each of these projects is the equivalent of 3 classes. Dr. Heffernan has supervised over 100 students working on these projects. Please view a list of the projects Dr. Heffernan has advised. He just posted a new COVID19 project.
MQP and IQP Projects for WPI Undergraduates
Dr. Heffernan advises a variety of projects for WPI Juniors and Seniors. He accepts student projects on the following topics:
Software engineering topics related to building the ASSISTments system:
AUTOMATIC REASSESSMENT AND RELEARNING SYSTEM (ARRS): A feature that is popular for spacing out time. (Based on the MQP by Sam Song)
PLACEments: a feature that gives computer adaptive tests and practice
Software Development Kit for the ASSISTments Family of applications
How to crowdsource from teacher and students problems (answers and solutions and feedback) from every textbook in America.
Deep learning: data mining to predict student knowledge using assistments data sets.
Researchers at Google and Stanford applied Deep Learning to predict Khan Academy Data and ASSISTments Data. The ASSISTments team uses TensorFlow to beat them at this game. The data set they used is here.
Mobile App Development: ASSISTments has developed apps for iOS and Android. Please reach out if you are interested in working on these apps.
We have build a version of ASSISTments that run in Google Classroom. If you want to get some experience using some google API, this is a nice project.
I want a team to investigate the applicability of the current state of the art student knowledge and affect models to ASSISTments data. You will apply these models to our current data and see if we can better understanding student knowledge within ASSISTments.
Before applying, please watch this video in which Dr. Heffernan describes the scope of different projects. It is also advantageous to read Dr. Heffernan's pieces on crowdsourcing and open-ed tech platforms for research. Please fill out this document to apply and return it to Angela Kao at firstname.lastname@example.org to apply. Come Join the ASSISTments Team!