It is well known that meaningful knowledge of statistics involves more than simple factual or procedural knowledge of statistics. For an intelligent use of statistics, conceptual understanding of the underlying theory is essential. As conceptual understanding is usually defined as the ability to perceive links and connections between important concepts that may be hierarchically organized, researchers often speak of this type of knowledge as structural knowledge. In order to gain insight into the actual structure of a student's knowledge network, specific methods of assessment are sometimes used. In this article we discuss a newly developed, specific method for assessing structural knowledge and compare its merits with more traditional methods like concept mapping and the use of simple open questions.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education