Concept Inventories are multiple choice instruments that map students’ conceptual understanding in a given subject area. They underpin some of the most effective teaching methods in science education, but they are labour intensive and expensive to construct, which limits their wide use in instruction. We describe how we use Latent Semantic Analysis to accelerate the construction of Concept Inventories in general, and the Biology Concept Inventory in particular.

Over forty years ago, Vannevar Bush articulated his vision of a “Memex” machine: “associative indexing, … whereby any item may be caused at will to select immediately and automatically another” [Bush 45]. In the sixties, Engelbart [Engelbart, English 68] built collaborative systems to provide idea structuring and sharing. Nelson [Nelson 81] coined “hypertext” and proposed world-wide networks for publishing, linking, annotating and indexing multiple versions of documents. With increasing numbers of research projects, papers, panels and conferences, and commercially available systems (e.g. Notecards by Xerox, Guide by Owl and HyperCard by Apple) in recent years, hypertext may be an idea whose time has finally come — or at least a phenomenon not to be ignored.