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)…

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…

The purpose of this study was to develop a framework for analyzing and evaluating student-constructed models of physical phenomena and monitoring the progress of these models. Moreover, we aimed to examine whether this framework could capture differences between models created using different computer-based modeling tools; namely, computer-based…

Purpose: To help to clarify the role of XML tools and standards in supporting transition and migration towards a fully XML-based environment for managing access to information. Design/methodology/approach: The Ching Digital Image Library, built on a three-tier architecture, is used as a source of examples to illustrate a number of methods of data…