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…

Purpose: Massive open online courses (MOOCs) have received wide publicity and many institutions have invested considerable effort in developing, promoting and delivering such courses. However, there are still many unresolved questions relating to MOOCs and their effectiveness in a blended-learning context. One of the major recurring issues raised…

Learning to program, especially in the object-oriented paradigm, is a difficult undertaking for many students. As a result, computing educators have tried a variety of instructional methods to assist beginning programmers. These include developing approaches geared specifically toward novices and experimenting with different introductory…