Network Visualization of Human and Machine-Based Educational Standard Assignment

Rapid growth in the availability of digital libraries of K-12 curriculum, coupled with an increased emphasis on standard-based teaching has led to the development of automated standard assignment tools. To assess the performance of one of those tools and to gain insight into the differences between how human catalogers and automated tools conduct these standard assignments, we explore the use of network modeling and visualization techniques for comparing and contrasting the two. The results show significant differences between the human-based and machine-based network maps. Unlike the machine-based maps, the human-based assignment maps elegantly reflect the rationales and principles of the assignments; i.e., clusters of standards separate along lines of content and pedagogical principles. In addition, humans seem significantly more apt at assigning so-called `methodological' standards.