582 Text Comprehension and Discourse Processing
with true inferences, but rather with automatic knowledge
retrieval.
There are other types of automatic inferences, however,
that are not purely a question of knowledge retrieval. For
instance, readers of
(c) Three turtles sat on a log. A fish swam under the log.automatically infer
(d) The turtles were above the fish. (Bransford, Barclay, &
Franks, 1972.)This inference is an automatic consequence of forming an
appropriate situation model, for example an image of the
situation described in (c).
Strategic inferences are a controlled process, as opposed
to automatic inferences (W. Kintsch, 1993, 1998). Strategic
inferences may involve knowledge retrieval, but in the ab-
sence of long-term working memory structures, so that the
retrieval process is resource consuming and often quite diffi-
cult. Or they can be true inferences, not just retrieving pre-
existing knowledge, as in logical inferences such as modus
ponens,which require special training for most people (see
the chapter in this volume by Leighton & Sternberg). Pre-
dicting when strategic inferences will be made is quite diffi-
cult. It depends on a host of factors such as reading goals,
motivation, and background knowledge. For instance, in
reading a story, readers sometimes but by no means always
make forward or predictive inferences (Klin, Guzman, &
Levine, 1999). Indeed, text researchers disagree strongly as
to the prevalence of strategic inferences. Some minimalists
(McKoon & Ratcliff, 1992) find very little evidence for such
inferences, while others (Graesser, Singer, & Trabasso, 1994)
disagree. The question is when such inferences are made—
spontaneously, as an integral part of reading a text (like
bridging inferences), or in response to special task demands
such as a question or verification test afterwards. It seems
clear that this is not an issue that is capable of a general reso-
lution. Rather, the answer must depend on the exact condition
of reading because this kind of inference process is under
strategic control of the reader.
Learning From Text
Learning from a text means that the reader understands the
content and is able to use the information in ways that are not
specific to the text. Thus, learning involves much more than
storage of a text for recall. Unlike memory for a text, actual
learning from the text requires integration of information into
the reader’s existing knowledge and creates a flexible
and powerful representation of the new information. This
integrated representation of text information is called the
situation model.
Development of a situation model has many benefits for
learners. Individuals who have created powerful situation
models are able to transfer their knowledge and apply it to
new domains or situations. The situation model is not just a
more flexible representation, it is the longest lasting of the
text representations. Because it integrates text information
with a reader’s existing knowledge, it offers the long-term
potential to be transferred to other situations and to be incor-
porated into other learning situations. Thus, construction
of the situation model represents true learning from a text
(W. Kintsch, 1994; Zwaan & Radvansky, 1998).
A variety of methods have been used to assess the strength
of the situation model that an individual constructs. Ideally,
the method used to assess the situation model must differen-
tiate between a textbase representation and the situation
model. Tasks that adequately assess the situation model
above and beyond the textbase generally require the learner
to transfer or generalize the information from a text in a new
situation. Short-answer questions requiring inferences and
transfer, concept-key word sorting tasks (McNamara et al.,
1996; Wolfe et al., 1998), and changes in knowledge map-
ping before and after reading a text (Ferstl & Kintsch, 1999)
all have been used to asses the strength of the situation model
after learning.
Although it may seem that the situation model is a more
desirable goal of reading than a textbase representation is, the
purpose for which a text is being studied should be consid-
ered when comparing the effectiveness of the textbase and
the situation model. Because traditional academic tests (such
as multiple-choice recognition) often emphasize textbase
learning, students seeking a peak performance on such exams
may do well to emphasize textbase learning during their
study. At the least, when text memory will be assessed, stu-
dents should prevent emphasizing the situation model at the
expense of textbase learning. However, students who desire
long-term benefits from text learning are best aided by
emphasizing situation model development.
To some extent, the situation model is dependent upon
construction of an accurate and complete textbase. Without
this foundation, integration with background knowledge is
prone to error, misconceptions, and gaps. However, just as
central to the situation model is the presence of adequate and
appropriate domain knowledge with which text information
can be integrated. Thus, it is essential for comprehension that
texts be matched appropriately to readers who have the back-
ground knowledge necessary to comprehend them. Wolfe
et al. (1998) demonstrated that matching readers to texts that
are suited to their levels of background knowledge can result
in substantial comprehension benefits. Understanding the