This project explores an approach for analyzing problem level data received from an intelligent tutoring system, ASSISTments. Through data processing techniques, a dataset representative of student answering patterns is constructed. This data is fed into various machine learning algorithms to model student competency. The output from one such algorithm, an LSTM neural network, is extracted to generalize across success metrics, which the original model was not built to predict. Such a model could be used to determine a threshold for student competency and detect when students need help early. Instructors can then act on this information and follow through with prevention techniques before the student fails.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Doherty, Diana

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-080618-201415

Advisor

• Beck, Joseph E.

Year

• 2018

Date created

• 2018-08-06

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright