Models of Knowledge Representation 589The Capacity-Constrained
Construction-Integration Model
Inclusion of working memory constraints in comprehension mod-
els offers some clear benefits to explaining individual differences
in comprehension. Both the construction-integration model and
the CAPS architecture are quite successful in explaining some as-
pects of comprehension. Given that construction-integration seeks
to model comprehension in general (rather than stopping with text
comprehension) but CAPS provides a successful account of
individual differences in text comprehension based on working
memory constraints, could the two models be combined as a
capacity-limited model of general comprehension? The capacity-
constrained construction integration model (CCCI; Goldman &
Varma, 1995) attempts to combine the ways in which knowledge
is constructed, represented, and integrated in the construction-
integration (CI) model within the more flexible capacity-
constrained CAPS system. Instantiating construction-integration
in a working-memory limited system has the effect of changing
the way in which propositions are held over for additional pro-
cessing cycles. Whereas the CI model uses a buffer of fixed size
to simulate limitations of working memory in text processing,
Goldman and Varma’s (1995) CCCI model retains all proposi-
tions not exceeding capacity limitations for further processing.
When capacity limits are reached (as in CAPS), new propositions
may draw activation away from retained elements, which grace-
fully fall below threshold.
The main strength of the CCCI model is that it repro-
duces the major, successful comprehension results of the
construction-integration model at the same time as it auto-
matically produces stronger weights for propositions repre-
senting main points from a text passage instead of assigning
initial weights to reflect differences in text importance. Thus,
providing the construction-integration model with working
memory limits may help us understand how comprehension
processes arrive at different representation strengths for dif-
ferent text elements.
The Landscape Model
The landscape model (van den Broek, Risden, Fletcher, &
Thurlow, 1996) also assumes that patterns of activation work
within constraints during a cyclical process of comprehension.
However, the landscape model deals more specifically with
the process by which coherence is computed and represented
during comprehension. In this model, activation strengths
during each processing cycle are set on a 5-point scale deter-
mined by the degree to which the concept is necessary to es-
tablish coherence in the text. Accordingly, concepts that are
explicitly defined are assigned the highest weights, whereas
inferences that are not necessary to establish coherence re-
ceive the lowest activation weights. Concepts that contribute
to coherence are weighted to varying degrees along this con-
tinuum as a function of their degree of contribution to the
coherence.
The landscape model draws its name from the patterns
of activations seen for text concepts across all processing
cycles during comprehension. That is, an activation map
of all concepts across cycles is constructed and graphically
demonstrates the degree to which concepts are activated
during the progression of the story, as well as the number of
concepts that are concurrently activated in each cycle of
comprehension. According to van den Broek et al., the
topography of activation suggests the way in which com-
prehended text becomes encoded as a stable, coherent
representation. Further, van den Broek et al. argue that the
total activation of a concept across cycles predicts the im-
portance of the concept to the story and that concepts acti-
vated together during a processing cycle will be linked in
memory.
Testing by van den Broek et al. (1996) suggests that the
activation of concepts during processing cycles can predict
patterns of human recall for story concepts. In their research,
nearly all (94%) concepts first recalled by participants were
the concepts that demonstrated greatest overall activation
during the course of reading. Further, the pattern of subse-
quent concepts recalled was predicted by the degree to which
the prior and subsequent concepts were coactivated during
reading. The landscape model, then, provides a description of
and a general methodology for testing the ways concepts
are emphasized and linked in a text. However, the landscape
model falls short of offering a theoretical rationale for
the ways in which humans construct, represent, and integrate
their knowledge. In general, models of comprehension reflect
similar assumptions about the way in which knowledge is
represented, but it is valid to question the precise nature of
such representations.MODELS OF KNOWLEDGE REPRESENTATIONOne of the central problems in cognitive science is how to model
human knowledge. How can we defineknowledge?The word
knowis used in so many ways; is what we know always knowl-
edge? Consider this list, selected from the 11 senses ofknow
listed in WordNet (http://www.cogsci.princeton.edu/~wn/):1.I know who is winning the game.
2.She knows how to knit.
3.Galileo knew that the earth moved around the sun.