This article is Part 1 of our 2-part series in modeling educational data. In this first part, we introduce the theory of graphs and network structures. We then give an overview of the different types of educational mapping.
In the second part of our introductory series, we walk you through how to create a network map of your own educational data.
A network structure consists of vertices and edges. Vertices represent entities in a system, and edges between vertices represent relationships between entities.
Different types of entities can exist in different models. For example, in doing curriculum analysis, we model as entities the Institution, the Departments within the Institution and the Courses within Departments.
Entities are represented as vertices. A vertex is assigned text and numeric attributes that represent information on the entity. For example, the name of the entity can be an attribute.
Similarly, an edge is assigned text and numeric attributes that describe the relationship, for example, the strength of the relationship expressed on a scale from 0 – 1.
For a directed edge, the relationship applies only in one direction — the direction of the edge matters and is indicated visually with an arrow. An undirected edge is bidirectional — the relationship applies in both directions.
With this framework, we can think of representing curricular data as composed of entities and relationships. The term "curricular data" is deliberately broad — to give a few examples: these data can be courses in a curriculum, student learning records, teachers in a system, etc.
In the images below, we depict a few examples of common maps. From left to right: an outcomes map showing how Courses address Outcomes; a concept map showing how Concepts address Outcomes that lead to other Outcomes; a curriculum map showing a more coarse-grained view of how Courses relate to each other.
In the next section, we discuss how to apply network modeling to educational data and how you can get started modeling your own data.