Modeling, Visualizing, and Analyzing Student Progress on Learning Maps

Abstract

We present a design in which data visualization techniques are applied to meet the needs of teachers and education researchers in analyzing and responding to student learning. Developed using the iterative process fundamental to visualization research and building on established research in the fields of Computer Science and Psychometrics, we present an account of the experimental approaches developed to better understand the project requirements. This will include rationale, observations, and conclusions drawn for each approach. Also presented is the process used to synthesize, from these early efforts, a single visualization tool capable of meeting both predictive and validation requirements as well as the methods used to measure the effectiveness and correctness of the final design. In addition to visualization schemes and methods, we present contributions made to the field of Computer Science in the form of algorithms developed over the course of the research project in response to gaps in prior art. These include novel approaches to simulation of student response patterns, ranked layout of weighted directed graphs with variable edge widths, and enclosing certain groups of graph nodes in envelopes.