Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

Collaborative learning is a complex process during which two or more learners exchange opinions, construct shared knowledge, and solve problems together. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. If intelligent systems could predict…

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…