In this paper we maintain that there are benefits to extending the sco
pe of student models to include additional information as part of the
explicit student model. We illustrate our argument by describing a stu
dent model which focuses on 1. performance in the domain; 2. acquisiti
on older of the target knowledge; 3. analogy; 4. learning strategies;
5. awareness and reflection. The first four of these issues are explic
itly represented in the student model. Awareness and reflection should
occur as the student model is transparent; it is used to promote lear
ner reflection by encouraging the learner to view, and even negotiate
changes to the model. Although the architecture is transferable across
domains, each instantiation of the student model will necessarily be
domain specific due to the importance of factors such as the relevant
background knowledge for analogy, and typical progress through the tar
get material. As an example of this approach we describe the student m
odel of an intelligent computer assisted language learning system whic
h was based on research findings on the above five topics in the field
of second language acquisition. Throughout we address the issue of th
e generality of this model, with particular reference to the possibili
ty of a similar architecture reflecting comparable issues in the domai
n of learning about electrical circuits.