“…In the simplest (and oldest) form, it is a binary value (known -not known) that enables the model to represent the user's knowledge as an overlay of domain knowledge. While some successful AEH systems (De Bra, 1996) use this classic form of an overlay model, the majority of systems use a weighted overlay model that can distinguish several levels of the user's knowledge of a KE through a qualitative value (Brusilovsky & Anderson, 1998;Papanikolaou et al, 2003) (for example, good-average-poor), an integer numeric value (for example, from 0 to 100) De Bra & Ruiter, 2001), or a probability that the user knows the concept Specht & Klemke, 2001). A few AEH systems use an even more sophisticated layered overlay model (Brusilovsky & Millán, 2007) to store multiple evidences about the user's level of knowledge separately (Brusilovsky & Cooper, 2002;Brusilovsky, Sosnovsky & Yudelson, 2005;Weber & Brusilovsky, 2001).…”