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and principles (Newton & Newton, 2000; Ruiz-Primo & Shavelson, 1996). The
organization of hypermedia system can help learners develop such a framework.
Hypermedia features such as links and cross-references can promote navigation pat-
terns which model expert forms of knowledge organization (Jonassen, 1986; Nunes
& Fowell, 1996; Park, 1991). Links enable semantically and logically related infor-
mation to be tied together in conceptual webs and help learners to understand how
ideas are interrelated. In other words, the nodes and links can be used to provide
explicit conceptual representations to learners. It is the structure embedded in hyper-
media, rather than the media and modalities in which they are presented, that are
important for comprehension of complex systems (Hegarty, Narayanan & Freitas,
2002).
Conceptual representations refer to frameworks or models that people can use to
organize their knowledge (Davis, Shrobe, & Szolovits, 1993). Such representations
can highlight commonalities across different domains or systems (Novick & Hmelo,
1994) and may be used to guide students to see the common framework across
different domains. In complex system learning, conceptual representations can pro-
mote developing a deep understanding by highlighting the key aspects of a complex
system, such as the relationship among structural, functional, and behavioral levels
of a system. One possible approach to helping students learn about complex sys-
tems is to provide instruction that focuses on the functional aspects of the system.
We tested this idea with hypermedia as we investigated effects of two alternative
conceptual representations on student understanding.
Structure-Behavior-Function as a Conceptual Representation
Conceptual representations provide organizing frameworks across domains. Collins
and Ferguson (1993) refer to these as epistemic forms—target structures that are
important in constructing knowledge and engaging in inquiry. These representations
are useful in making sense of the world. Form and function analysis is a classic form
of analysis in many fields of inquiry and is a canonical form of explanation in the life
sciences (Bechtel & Abrahamson, 2005). Such an analysis produces an explanation
of causal mechanisms as it stresses that understanding a form precedes and invites
explaining mechanisms that account for that form's function.
Extending form and function analysis, Goel et al. (1996) designed the Structure-
Behavior-Function (SBF) representation to allow computers to effectively reason
about designed devices. The SBF theory provides a conceptual representation and
sheds light on causal understanding of systems because of its focus on the dynamic
nature and multilevel organization of the system, and the relationships between
structures, functions, and behaviors (Goel et al., 1996). Structures refer to the ele-
ments of a system. Behaviors refer to the mechanisms within a system. Finally
functions refer to outcomes or roles in a system. For example, the diaphragm would
be one of the structures of the human respiratory system. The contracting and
relaxing mechanism is an example of the behavior of the diaphragm. The function
