As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

A common approach for introducing students to a new science concept is to present them with multiple cases of the phenomenon and ask them to explore. The expectation is that students will naturally take advantage of the multiple cases to support their learning and seek an underlying principle for the phenomenon. However, the success of such tasks…

A common approach for introducing students to a new science concept is to present them with multiple cases of the phenomenon and ask them to explore. The expectation is that students will naturally take advantage of the multiple cases to support their learning and seek an underlying principle for the phenomenon. However, the success of such tasks…

Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…