# Cognitive Psychology and Cognitive Neuroscience/Situation Models and Inferencing

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## Introduction

An important function and property of the human cognitive system is the
ability to extract important information out of textually and verbally
described situations. This ability plays a vital role in understanding
and remembering. But what happens to this information after it is
extracted, how do we represent it and how do we use it for inferencing?
With this chapter we introduce the concept of a "situation model" (van
Dijk&Kintsch, 1983, "mental model": Johnson-Laird, 1983), which is the
mental representation of what a text is about. We discuss what these
representations might look like and show the various experiments that
try to tackle these questions empirically. By assuming situations to be
encoded by perceptual symbols (Barsalou, 1999), the theory of Situation
Models touches many aspects of Cognitive Philosophy, Linguistics and
Artificial Intelligence. In the beginning of this chapter, we will
mention why Situation Models are important and what we use them for.
Next we will focus on the theory itself by introducing the four primary
types of information - the situation model components, its Levels of
Representation and finally two other basic types of knowledge used in
situation model construction and processing (general world knowledge and
referent specific knowledge).

Situation models not only form a central concept in theories of situated
cognition that helps us in understanding how situational information is
collected and how new information gets integrated, but they can also
explain many other phenomena. According to van Dijk & Kintsch, situation
models are responsible for processes like domain-expertise, translation,
learning from multiple sources or completely understanding situations
just by reading about them. These situation models consist, according to
most researches in this area, of five dimensions, which we will explain
later. When new information concerning one of these dimensions is
extracted, the situation model is changed according to the new
information. The bigger the change in the situation model is, the more
time the reader needs for understanding the situation with the new
information. If there are contradictions, e.g. new information which
does not fit into the model, the reader fails to understand the text and
probably has to reread parts of the text to build up a better model. It
was shown in several experiments that it is easier to understand texts
that have only small changes in the five dimensions of text
understanding. It also has been found that it is easier for readers to
understand a text if the important information is more explicitly
mentioned. For this reason several researchers wrote about the
importance of fore-grounding important information (see Zwaan&Radvansky
1998 for a detailed list). The other important issue about situation
models is the multidimensionality. Here the important question is how
are the different dimensions related and what is their weight for
constructing the model. Some researchers claim that the weight of the
dimensions shifts according to the situation which is described.
Introducing such claims will be the final part of this chapter and aims
to introduce you to current and future research goals.

#### The VIP: Rolf A. Zwaan

Rolf A. Zwaan, born September 13, 1962 in Rotterdam (the Netherlands),
is a very important person for this topic, since he made the most
research (92 publications in total), and also because most of our data
is taken from his work. Zwaan did his MA (1986) and his Ph.D. (1992) at
the Utrecht University (Netherlands), both cum laude. Since then he
collected multiple awards like the Developing Scholar Award (Florida
state University, 1999) or the Fellow of the Hanse Institute for
Advanced Study (Delmenhorst, Germany, 2003) and became member of several
Professional Organisations like the Psychonomic Society, the Cognitive
Science Society or the American Psychological Society. He works as Chair
of the Biology & Cognitive Psychology at the Erasmus University in
Rotterdam (Netherlands), since 2007.

## Why do we need situation models?

A lot of tasks which are based on language processing can only be
explained by the usage of situation models. The so called situation
model or mental model consists of five different dimensions, which refer
to different sources. To comprehend a text or just a simple sentence,
situation models are useful. Furthermore the comprehension and
combination of several texts and sentences can be explained by that
theory much better. In the following, some examples are listed why we
really need situation models.

#### Integration of information across sentences

Integration of information across sentences is more than just
understanding a set of sentences. For example:

*"Gerhard Schroeder is in front of some journalists. Looking forward to
new ideas is nothing special for the Ex-German chancellor. It is like in
the good old days in 1971 when the leader of the Jusos was behind the
polls and talked about changes."*

This example only makes sense to the reader if he is aware that
*"Gerhard Schroeder"*, *"Ex-German chancellor"* and *"the leader of the
Jusos in 1971"* is one and the same person. If we build up a situation
model, in this example *"Gerhard Schroeder"* is our token. Every bit of
information which comes up will be linked to this token, based on
grammatical and world knowledge. The definite article in the second
sentence refers to the individual in the first sentence. This is based
on grammatical knowledge. Every definite article indicates a connection
to an individual in a previous sentence. If there would be an indefinite
article, we have to build a new token for a new individual. The third
sentence is linked by domain knowledge to the token. It has to be known
that "Gerhard Schroeder" was the leader of the Jusos in 1971. Otherwise
the connection can only be guessed. We can see that an integrated
situation model is needed to comprehend the connection between the three
sentences.

#### Explanation of similarities in comprehension performances across modalities

The explanation of similarities in comprehension performances across
modalities can only be done by the usage of situation models. If we read
a newspaper article, watch a report on television or listen to a report
on radio, we come up with a similar understanding of the same
information, which is conveyed through different modalities. Thus we
create a mental representation of the information or event. This mental
representation does not depend on the modalities itself. Furthermore
there is empirical evidence for this intuition. Baggett (1979) found out
that students who saw a short film and students who heard a spoken
version of the events in the short film finally produced a structurally
similar recall protocol. There were differences in the protocols of the
two groups but the differences were due to content aspects. Like the
text version explicitly stated that a boy was on his way to school and
in the movie this had to be inferred.

#### Domain expertise on comprehension

Situation models have a deep influence for effects of domain expertise
on comprehension. In detail this means that person A, whose verbal
skills are less than from person B, is able to outperform person B, if
he has more knowledge of the topic domain. To give evidence for this
intuition, there was a study by Schneider and Körkel (1989). They
compared the recalls of "experts" and novices of a text about a soccer
match. In the study were three different grades: 3rd, 5th and 7th. One
important example in that experiment was that the 3rd grade soccer
experts outperformed the 7th grade novices. The recall of units in the
text was 54% by the 3rd grade experts and 42% by the 7th grade novices.
The explanation is quite simple: The 3rd grade experts built up a
situation model and used knowledge from their long-term memory (Ericsson
& Kintsch, 1995). The 7th grade novices had just the text by which they
can come up with a situation model. Some more studies show evidence for
the theory that domain expertise may counteract with verbal ability,
i.e. Fincher-Kiefer, Post, Greene & Voss, 1988 or Yekovich, Walker, Ogle
& Thompson in 1990.

#### Explanation of translation skills

An other example why we need situation models is by trying to explain
translation. Translating a sentence or a text from one language to
another is not simply done by translating each word and building a new
sentence structure until the sentence seems to be sound. If we have a
look now at the example of a Dutch sentence:

![{width="450"}

Now we can conclude that the translation level between Dutch and English
is not based on the lexical-semantic level; it is based on the situation
level. In this example "don't do something (action) before you haven't
done something else (another action)". Other studies came up with
findings that the ability to construct situation models during the
translation is important for the translation skill (Zwann, Ericsson,
Lally and Hill, in 1998).

#### Multiple source learning

People are able to learn about a domain from multiple documents. This
phenomenon can be explained by a situation model, too. For example, we
try to learn something about the *"Cold War"* we use different documents
with information. The information in one document may be similar to
other documents. Referents can be the same or special relationships in
the "Cold War" can just be figured out by the usage of different
documents. So what we are really doing by learning and reasoning is that
we integrate information on the base of different documents into a
common situation model, which has got an organized order of the
information we've learned.

We have seen that we need situation models in different tasks of
language processing, but situation models are not needed in all tasks of
language processing. An example is proofreading. A proofreader checks
every word for its correctness. This ability does not contain the
ability to construct situation models. This task uses the resources of
the long-term memory in which the correct writing of each word is
stored. The procedure is like:

!Zwaan (2003{width="400"}

This is done word by word. It is unnecessary to create situation models
in this task for language processing.

## Multidimensionality of Situation Models

### Space

Very often, objects that are spatially close to us are more relevant
than more distant objects. Therefore, one would expect the same for
situation models. consistent with this idea, comprehenders are slower to
recognise words denoting objects distant from a protagonist than those
denoting objects close to the protagonist (Glenberg, Meyer & Lindem,
1987).

When comprehenders have extensive knowledge of the spatial layout of the
setting of the story (e.g., a building), they update their
representations according to the location and goals of the protagonist.
They have the fastest mental access to the room that the protagonist is
currently in or is heading to. For example, they can more readily say
whether or not two objects are in the same room if the room mentioned is
one of these rooms than if it is some other room in the building (e.g.,
Morrow, Greenspan, & Bower, 1987). This makes perfect sense intuitively
because these are the rooms that would be relevant to us if we were in
the situation.

People's interpretation of the meaning of a verb denoting movement of
people or objects in space, such as *to approach*, depends on their
situation models. For example, comprehenders interpret the meaning of
*approach* differently in *The tractor is just approaching the fence*
than in *The mouse is just approaching the fence*. Specifically, they
interpret the distance between the figure and the landmark as being
longer when the figure is large (tractor) compared with when it is small
(mouse). The comprehenders' interpretation also depends on the size of
the landmark and the speed of the figure (Morrow & Clark, 1988).
Apparently, comprehenders behave as if they are actually standing in the
situation, looking at the tractor or mouse approaching a fence.

### Time

We assume by default that events are narrated in their chronological
order, with nothing left out. Presumably this assumption exists because
this is how we experience events in everyday life. Events occur to us in
a continuous flow, sometimes in close succession, sometimes in parallel,
and often partially overlapping. Language allows us to deviate from
chronological order, however. For example, we can say, "Before the
psychologist submitted the manuscript, the journal changed its policy."
The psychologist submitting the manuscript is reported first, even
though it was the last of the two events to occur. If people construct a
situation model, this sentence should be more difficult to process than
its chronological counterpart (the same sentence, but beginning with
"After"). Recent neuroscientific evidence supports this prediction.
Event-related brain potential (ERP) measurements indicate that "before"
sentences elicit, within 300 ms, greater negativity than "after"
sentences. This difference in potential is primarily located in the left
anterior part of the brain and is indicative of greater cognitive effort
(Münte, Schiltz, & Kutas, 1998). In real life, events follow each other
seamlessly. However, narratives can have temporal discontinuities, when
writers omit events not relevant to the plot. Such temporal gaps,
typically signalled by phrases such as *a few days later*, are quite
common in narratives. Nonetheless, they present a departure from
everyday experience. Therefore, time shifts should lead to (minor)
disruptions of the comprehension process. And they do. Reading times for
sentences that introduce a time shift tend to be longer than those for
sentences that do not (Zwaan, 1996).

`All other things being equal, events that happened just recently are more accessible to us than events that happened a while ago. `\
`Thus, in a situation model, `*`enter`*` should be less accessible after `*`An hour ago, John entered the building`*` than after `*`A moment ago, John entered the building`*`. `\
`Recent probe-word recognition experiments support this prediction (e.g., Zwaan, 1996).`

### Causation

As we interact with the environment, we have a strong tendency to
interpret event sequences as causal sequences. It is important to note
that, just as we infer the goals of a protagonist, we have to infer
causality; we cannot perceive it directly. Singer and his colleagues
(e.g., Singer, Halldorson, Lear, & Andrusiak, 1992) have investigated
how readers use their world knowledge to validate causal connections
between narrated events. Subjects read sentence pairs, such as 1a and
then 1b or 1a' and then 1b, and were subsequently presented with a
question like 1c:

(1a) Mark poured the bucket of water on the bonfire.

(1a') Mark placed the bucket of water by the bonfire.

(1b) The bonfire went out.

(1c) Does water extinguish fire?

Subjects were faster in responding to 1c after the sequence 1a-1b than
after 1a'-1b. According to Singer, the reason for the speed difference
is that the knowledge that water extinguishes fire was activated to
validate the events described in 1a-1b. However, because this knowledge
cannot be used to validate 1a'-1b, it was not activated when subjects
read that sentence pair.

### Intentionality

We are often able to predict people's future actions by inferring their
intentionality, i.e. their goals. For example, when we see a man walking
over to a chair, we assume that he wants to sit, especially when he has
been standing for a long time. Thus, we might generate the inference "He
is going to sit." Keefe and McDaniel (1993) presented subjects with
sentences like *After standing through the 3-hr debate, the tired
speaker walked over to his chair (and sat down)* and then with probe
words (e.g., sat, in this case). Subjects took about the same amount of
time to name sat when the clause about the speaker sitting down was
omitted and when it was included. Moreover, naming times were
significantly faster in both of these conditions than in a control
condition in which it was implied that the speaker remained standing.

### Protagonists and Objects

Comprehenders are quick to make inferences about protagonists,
presumably in an attempt to construct a more complete situation model.
Consider, for example, what happens after subjects read the sentence
*The electrician examined the light fitting*. If the following sentence
is *She took out her screwdriver*, their reading speed is slowed down
compared with when the second sentence is *He took out his screwdriver*.
This happens because she provides a mismatch with the stereotypical
gender of an electrician, which the subjects apparently inferred while
reading the first sentence (Carreiras, Garnham, Oakhill, & Cain, 1996).

`Comprehenders also make inferences about the emotional states of characters. `\
`For example, if we read a story about Paul, who wants his brother Luke to be good in baseball, the concept of “pride” becomes activated in our mind when we read`\
`that Luke receives the Most Valuable Player Award (Gernsbacher, Goldsmith, & Robertson, 1992). `\
`Thus, just as in real life, we make inferences about people’s emotions when we comprehend stories.`

## Processing Frameworks

### Introduction

In the process of language and text comprehension new information has to
be integrated into the current situation model. This is achieved by a
processing framework. There are various theories and insights on this
process. Most of them only model one or some aspects of Situation Models
and language comprehension.

A list of theories, insights and developments in language comprehension
frameworks:

-   an interactive model of comprehension (Kintsch and van Dijk, 1978)
-   early Computatinal Model (Miller, Kintsch, 1980)
-   Constructing-integration Model (Kintsch, 1988)
-   Structure-Building-Framework (Gernsbacher,1990)
-   Capacity Constraint Reader Model (Just, Carpenter, 1992)
-   Constructivist framework (Graesser, Singer, Trabasso, 1994)
-   Event Indexing Model (Zwaan, Langston, Graesser, 1995)
-   Landscape Model (van den Brock, Risden, Fletcher, & Thurlow, 1996)
-   Capacity-constrained construction-integration Model (Goldman, Varma,
    Coté, 1996)
-   The Immersed Experiencer Framework (Zwaan, 2003)

In this part of the chapter on Situation Models we will talk about
several models; we will start with some of the early stuff and then go
to the popular later ones. We will start with the work of Kintsch in the
70s and 80s and then go on to later research which is based on this.

### An interactive Model of Comprehension

This model was already developed in the 80s; it is the basis for many
later models like the CI-Model, or even the Immersed-Experiencer
Framework. According to Kintsch and van Dijk (1978), text comprehension
proceeds in cycles. In every cycle a few propositions are processed,
this number is determined by the capacity of the Short-Term Memory, so 7
plus or minus 2. In every cycle the new propositions are connected to
existing ones, they therefore form a connected and hierarchical set.

### Early Computational Model

This computational model from Miller and Kintsch tried to model earlier
theories of comprehension, to make predictions according to these and
compare them to behavioural studies and experiments. It consisted of
several modules. One was a chunking program: It\'s task is to read in
one word at the moment, identify if it is a proposition and decide
whether to integrate it or not. This part of the model was not done
computationally. The next part in the input order was the Microstructure
Coherence Program (MCP). The MCP sorted the propositions and stored them
in the Working Memory Coherence Graph. The task of the Working Memory
Coherence Graph was then to decide which propositions should be kept
active during the next processing cycle. All propositions are stored in
the Long Term Memory Coherence Graph, this decided which propositions
should be transferred back in to the Working Memory or it can construct
a whole new Working Memory Graph with a different superordinate node.
The problem with this Computational Model was that it show a really low
performance. But still it led to further research which tried to
overcome it\'s shortcomings.

### Event-Indexing Model

The *Event-Indexing Model* was first proposed by Zwaan, Langston and
Graesser (1995). It makes claims about how the incoming information in
comprehension is processed and how it is represented in the long-term
memory.

According to the *Event-Indexing Model* all incoming actions events are
split into five indexes. The five indexes are the same as the five
situational dimensions, though Zwaan & Radvasnky(1998) claim that there
are possibly more dimensions. These might be found in future research.
One basic point of this model is the processing time of integrating new
events into the current model. It is easier to integrate a new incoming
event if it shares indexes with a previous event. The more contiguous
the new event is, the easier it is integrated into the new Situation
Model. This prediction made by Zwaan & Radvanksy (1998) is supported by
some prior research (Zwaan, Magliano and Graesser, 1995). The other
important point of the *Event-Indexing Model* is the representation in
long-term memory. Zwaan & Radvasnky (1998) predict that this
representation is a network of nodes, these nodes encode the events. The
nodes are linked with each other through situational links according to
the indexes they share. This connection does not only encode if two
nodes share indexes but it also encodes the number of shared indexes
through its strength. This second point already hints what the
*Event-Indexing Model* lacks. There are several things which it does not
include. For example it does not encode the temporal order of the events
nor the direction of the causal relationships. The biggest disadvantage
of the *Event-Indexing Model* is clearly that it treats the different
dimensions as different entities though they probably interact with each
other.

Zwaan & Radvansky (1998) updated the *Event-Indexing Model* with some
features. This new model splits the processed information into three
types. These three types are the situational framework, the situational
relations and the situational content. The situational framework grounds
the situation in space and time, and its construction is obligatory. If
no information is given this framework is probably built up by standard
values retrieved from prior world knowledge or some empty variable would
be instantiated. he situational relations are based on the five
situational dimensions. These are analysed through the *Event-Indexing
Model*. This kind of situational information includes not the basic
information, which is given in the situational framework, but the
relationships between the different entities or nodes in the network. In
contrast to the situational framework the situational relations are not
obligatory. If there is no information given or there are no possible
inferences between entities, then there is simply no relationship there.
There is also an index which addresses importance to the different
relations. This importance consists of the necessity of the information
to understand the situation, the easiness to inference it when it would
not be mentioned and how easy the information can later be remembered.
Another distinction this theory makes is the one between functional and
non-functional relations (Carlson-Radvansky & Radvansky, 1996; Garrod &
Sanford, 1989). Functional relations describe the interaction between
different entities whereas non-functional relations are the ones between
non-interacting entities. The situational content consists of the
entities in the situation like protagonists and objects and their
properties. These are only integrated explicitly in the Situation Model,
like situational relations, if they are necessary for the understanding
of the situation. Nonetheless the central and most important entities
and their properties are obligatory again. It is proposed that, in order
to keep the processing time low, non-essential information is only
represented by something like a pointer so that this information can be
retrieved if necessary.

### The Immersed Experiencer Framework

The Immersed Experiencer Framework (IEF) is based on prior processing
framework models (see above for a detailed list) but tries to include
several other research findings too. For example it was found that
during comprehension brain regions are activated, which are very close
or even overlap with brain regions which are active during the
perception or the action of the words meaning (Isenberg et al., 2000;
Martin & Chao, 2001; Pulvermüller, 1999, 2002). During comprehension
there is also a visual representation of shape and orientation of
objects (Dahan & Tanenhaus, 2002; Stanfield & Zwaan, 2002; Zwaan et al.,
2002; Zwaan & Yaxley, in press a, b). Visual-spatial information primes
sentence processing (Boroditsky, 2000). These visual representations can
interfer with the comprehension (Fincher-Kiefer, 2001). Findings from
(Glenberg, Meyer, & Lindem, 1987; Kaup & Zwaan, in press; Morrow *et
al.*, 1987; Horton & Rapp, in press; Trabasso & Suh, 1993; Zwaan et al.,
2000) suggest that information which is part of the situation and the
text is more active in the reader\'s mind than information which is not
included. The fourth research finding is that people move their eyes and
hand during comprehension in a consistent way with the described the
situation. (Glenberg & Kaschak, in press; Klatzky et al., 1989; Spivey
et al., 2000).

The main point of the Immersed Experiencer Framework is the idea that
words active experiences with their referents. For example \"an eagle in
the sky\" activates a visual experience of a eagle with stretched-out
wings while \"an eagle in the nest\" activates a different visual
experience. According to Zwaan (2003) the IEF should be seen as an
engine to make predictions about language comprehension. These
predictions are then suggested for further research.

According to the IEF the process of language comprehension consists of
three components, these are activation, construal and integration. Each
component works at a different level. Activation works at the world
level, construal is responsible for the clause level while integration
is active at the discourse level. Though the IEF shares many points with
earlier models of language comprehension it differs in some main points.
For example it suggests that language comprehension involves action and
perceptual representations and not amodal propositions (Zwaan, 2003).

## Levels of Representation in Language and Text Comprehension

A lot of theories try to explain the situation model or so called mental
model in different representations. Several theories of the
representation deal with the comprehension from the text into the
situation model itself. How many levels are included or needed and how
is the situation model constructed, is it done by once like:

Sentence → Situation Model

Or are there levels in between which have to be passed until the model
is constructed? Here are three different representations shown which try
to explain the construction of the situation model by a text.

#### Propositional Representation

The propositional Representation claims that a sentence will be
structured in another way and then it is stored. Included information
does not get lost. We will have a look at the simple sentence:

*"George loves Sally"* the propositional representation is
\[LOVES(GEORGE, SALLY)\]

It is easy to see that the propositional representation is easy to
create and the information is still available.

#### Three levels of representation

!Fletcher(1994); van Dijk & Kintch(1983); Zwaan & Radvansky
(1998); van Dijk & Kintch(1983); Zwaan & Radvansky (1998)"){width="150"}
This theory says that there exist three levels of representation the
surface form, text base and the situation model. In this example the
sentence "The frog ate the bug." Is already the surface form. We
naturally create semantically relations to understand the sentence
(semantic tree in the figure). The next level is the "Text base".
\[EAT(FROG, BUG)\] is the propositional representation and *Text base*
is close to this kind of representation, except that it is rather
spatial. Finally the situation model is constructed by the "Text base"
representation. We can see that the situation model does not include any
kind of text. It is a mental picture of information in the sentence
itself.

#### Two levels of representation

!Frank Koppen, Nordman, Vonk (to appear) Zwaan
(2004) Zwaan (2004)"){width="150"}
This theory is like the "three levels of representations" theory. But
the "Text base" level is left out. The theory itself claims that the
situation model is created by the sentence itself and there is no "Text
base" level needed.

Further situation model theories directing experiences exist. So not
only text comprehension is done by situation models, learning through
direct experience is handled by situation models, too.

#### KIWi-Model

!A unified model by \"Prof. Dr.\"
Schmalhofer{width="250"}
One unified model the so called KIWi-Model tries to explain how text
representation and direct experience interact with a situation model.
Additionally the domain knowledge is integrated. The domain knowledge is
used by forming a situation model in different tasks like simple
sentence comprehension (chapter: Why do we need Situation Models). The
KIWi-Model shows that a permanent interaction between "text
representation → situation model" and between "sensory encoding →
situation model" exists. These interactions supports the theory of a
permanent updating of the mental model.

## Inferencing

Inferencing is used to build up complex situation models with limited
information. For example: in 1973 John Bransford and Marcia Johnson made
a memory experiment in which they had two groups reading variations of
the same sentence.

The first group read the text \"*John was trying to fix the bird house.
He was **pounding** the nail when his father came out to watch him do
the work*\"

The second group read the text \"*John was trying to fix the bird house.
He was **looking for** the nail when his father came out to watch him do
the work*\"

After reading, some test statements were presented to the participants.
These statements contained the word *hammer* which did not occur in the
original sentences, e.g.: \"*John was using a hammer to fix the
birdhouse. He was looking for the nail when his father came out to watch
him*\". Participants of the first group said they had seen 57% of the
test statements, while the participants from the second group had seen
only 20% of the test statements.

As one can see, in the first group there is a tendency of believing to
have seen the word *hammer*. The participants of this group made the
inference, that John used a hammer to pound the nail. This memory
influence test is good example to get an idea what is meant by making
inferences and how they are used to complete situation models.

While reading a text, inferencing creates information which is not
explicitly stated in the text; hence it is a creative process. It is
very important for text understanding in general, because texts cannot
include all information needed to understand the sense of a story. Texts
usually leave out what is known as *world knowledge*. World knowledge is
knowledge about situations, persons or items that most people share, and
therefore don\'t need to be explicitly stated. Each person should be
able to infer this kind of information, as for example that we usually
use hammers to pound nails. It would be impossible to write a text, if
it had to include all information it deals with; if there was no such
thing like inferencing or if it was not automatically done by our brain.

There is a number of different kinds of inferences:

### Anaphoric Inference

This kind of Inferencing usually connects objects or persons from one to
another sentence. Therefore it is responsible for connecting
cross-sentence information. E.g. in \"*John hit the nail. He was proud
of his stroke*\", we directly infer that \"he\" and \"his\" relate to
\"John\". We normally make this kind of inference quite easily. But
there can be sentences where more persons and other words relating to
them are mixed up and people have problems understanding the story at
first. This is normally regarded as bad writing style.

### Instrumental Inference

This type of Inference is about the tools and the methods used in the
text, like the hammer in the example above. Or for example, if you read
about somebody flying to New York, you would not infer that this person
has built a dragon-flyer and jumped off a cliff but that he or she used
a plane, since there is nothing else mentioned in the text and a plane
is the most common form of flying to New York. If there is no specific
information about tools, instruments and methods, we get this
information from our *General World Knowledge*

### Causal Inference

Causal Inference is the conclusion that one event caused another in the
text, like in \"He hit his nail. So his finger ached\". The first
sentence gives the reason why the situation described in the second
sentence came to be. It would be more difficult to draw a causal
inference in an example like \"He hit his nail. So his father ran
away\", although one could create an inference on this with some
fantasy.

Causal inferences create causal connections between text elements. These
connections are separated into *local connections* and *global
connections*. Local connections are made within a range of 1 to 3
sentences. This depends on factors like the capacity of the working
memory and the concentration due reading. Global connections are drawn
between the information in one sentence together with the background
information gathered so far about the whole text. Problems can occur
with Causal Inferences when a story is *inconsistent.* For example,
vegans eating steak would be inconsistent. An interesting fact about
Causal Inferences (Goldstein, 2005) is that the kind of Inferences we
draw here that are not easily seen at first are easier to remember. This
may be due to the fact that they required a higher mental processing
capacity while drawing the inference. So this \"not-so-easy\" inference
seems to be marked in a way that it is easier to remember it.

### Predictive / Forward Inference

Predictive/Forward Inferences uses the *General World Knowledge* of the
reader to build his prediction of the consequences of what is currently
happening in the story into the Situation Model.

### Integrating Inferences into Situation Models

The question how models enter inferential processes is highly
controversial in the two disciplines of cognitive psychology and
artificial intelligence. A.I. gave a deep insight in psychological
procedures and since the two disciplines crossed their ways and give two
main bases of the cognitive science. The arguments in these are largely
independent from each other although they have much in common.

Johnson-Laird (1983) makes a distinction between three types of
reasoning-theories in which inferencing plays an important role. The
first class gears to logical calculi and have been implemented in many
formal system. The programming language Prolog arises from this way of
dealing with reasoning and in psychology many theories postulate formal
rules of inference, a \"mental logic.\" These rules work in a purely
syntactic way and so are \"context free,\" blind for the context of its
content. A simple example clarifies the problem with this type of
theory:

`    If patients have cystitis, then they are given penicillin.`

and the logical conclusion:

`    If patients have cystitis and are allergic to penicillin, then they are given penicillin`

This is logically correct, but seems to fail our common sense of logic.

The second class of theories postulate content specific rules of
inference. Their origin lies in programming languages and production
systems. They work with forms like \"If x is a, then x is b\". If one
wants to show that x is b, showing that x is a sub-goal of this
argumentation. The idea of basing psychological theories of reasoning on
content specific rules was discussed by Johnson-Laird and Wason and
various sorts of such theories have been proposed. A related idea is
that reasoning depends on the accumulation of specific examples within a
connectionist framework, where the distinction between inference and
recall is blurred.

The third class of theories is based on mental models and does not use
any rules of inferencing. The process of building mental models of
things heard or read. The models are in an permanent change of updates.
A model built, will be equipped with new features of the new information
as long as there is no information, which generates a conflict with that
model. If this is the case the model is generally re-built, so that the
conflict generating information fits into the new model.

## Important Topics of current research

### Linguistic Cues versus World Knowledge

According to many researchers, language is the set of processing
instructions on how to build up the Situation Model of the represented
situation (Gernsbacher, 1990; Givon, 1992; Kintsch, 1992; Zwaan &
Radvansky, 1998). As mentioned, readers use the lexical cues and
information to connect the different situational dimensions and
integrate them into the model. Another important point here is prior
world knowledge. World knowledge also influences how the different
information in a situation model are related. The relation between
linguistic cues and world knowledge is therefore an important topic of
current and future research in the area of Situation Models.

### Multidimensionality

Another important aspect of current research in the area of Situation
Models is the Multidimensionality of the Models. The main aspect is here
how the different dimensions relate to each other, how they influence
and interact. The question here is also if they interact at all and
which interact. Most studies in the field were only about one or a few
of the situational dimensions.

## References

Ashwin Ram, et al. (1999) Understanding Language Understanding - chapter
5

Baggett, P. (1979). Structurally equivalent stories in movie and text
and the effect of the medium on recall. Journal of Verbal Learning and
Verbal Behavior, 18, 333-356.

Bertram F. Malle, et al. (2001) Intentions and Intentionality - chapter
9

Boroditsky, L. (2000). Metaphoric Structuring: Understanding time
through spatial metaphors. Cognition, 75, 1-28.

Carlson-Radvansky, L. A., & Radvansky, G. A. (1996). The influence of
functional relations on spatial term selection. Psychological Science,
7, 56-60.

Carreiras, M., et al. (1996). The use of stereotypical gender
information in constructing a mental model: Evidence from English and
Spanish. Quarterly Journal of Experimental Psychology, 49A, 639-663.

Dahan, D., & Tanenhaus, M.K. (2002). Activation of conceptual
representations during spoken word recognition. Abstracts of the
Psychonomic Society, 7, 14.

Ericsson, K. A., & Kintsch, W. (1995). Long-term working memory.
Psychological Review, 102, 211-245.

Farah, M. J., & McClelland, J. L. (1991). A computational model of
semantic memory impairment: modality specificity and emergent category
specificity. Journal of Experimental Psychology: General, 210, 339-357.

Fincher-Kiefer (2001). Perceptual components of situation models. Memory
& Cognition, 29 , 336-343.

Fincher-Kiefer, R., et al. (1988). On the role of prior knowledge and
task demands in the processing of text. Journal of Memory and Language,
27, 416-428.

Garrod, S. C., & Sanford, A. J. (1989). Discourse models as interfaces
between language and the spatial world. Journal of Semantics, 6,
147-160.

Gernsbacher, M.A. (1990), Language comprehension as structure building.
Hillsdale, NJ: Erlbaum.

Glenberg, A. M., & Kaschak, M. P. (2002). Grounding language in action.
Psychonomic Bulletin & Review, 9, 558-565.

Glenberg, A. M., et al. (1987) Mental models contribute to foregrounding
during text comprehension. Journal of Memory and Language 26:69-83.

Givon, T. (1992), The grammar of referential coherence as mental
processing instructions, Linguistics, 30, 5-55.

Goldman, S.R., et al. (1996). Extending capacityconstrained construction
integration: Towards \"smarter\" and flexible models of text
comprehension. Models of understanding text (pp. 73--113).

Goldstein, E.Bruce, Cognitive Psychology, Connecting Mind, Research, and
Everyday Experience (2005) - .

Graesser, A. C., Singer, M., & Trabasso, T. (1994), Constructing
inferences during narrative text comprehension. Psychological Review,
101, 371-395.

Holland, John H. , et al. (1986) Induction.

Horton, W.S., Rapp, D.N. (in press). Occlusion and the Accessibility of
Information in Narrative Comprehension. Psychonomic Bulletin & Review.

Isenberg, N., et al. (1999). Linguistic threat activates the human
amygdala. Proceedings of the National Academy of Sciences, 96,
10456-10459.

Johnson-Laird, P. N. (1983). Mental models: Towards a cognitive science
of language, inference, and consciousness. Cambridge, MA: Harvard
University Press.

John R. Koza, et al. (1996) Genetic Programming

Just, M. A., & Carpenter, P. A. (1992). A capacity hypothesis of
comprehension: Individual differences ih working memory. Psychological
Review, 99, 122-149.

Kaup, B., & Zwaan, R.A. (in press). Effects of negation and situational
presence on the accessibility of text information. Journal of
Experimental Psychology: Learning, Memory, and Cognition.

Keefe, D. E., & McDaniel, M. A. (1993). The time course and durability
of predictive inferences. Journal of Memory and Language, 32, 446-463.

Kintsch, W. (1988), The role of knowledge in discourse comprehension: A
construction-integration model, Psychological Review, 95, 163-182.

Kintsch, W., & van Dijk, T. A. (1978), Toward a model of text
comprehension and production, Psychological Review, 85, 363-394.

Kintsch, W. (1992), How readers construct situation models for stories:
The role of syntactic cues and causal inferences. In A. E Healy, S. M.
Kosslyn, & R. M. Shiffrin (Eds.), From learning processes to cognitive
processes. Essays in honor of William K. Estes (Vol. 2, pp. 261 -- 278).

Klatzky, R.L., et al. (1989). Can you squeeze a tomato? The role of
motor representations in semantic sensibility judgments. Journal of
Memory and Language, 28, 56-77.

Martin, A., & Chao, L. L. (2001). Semantic memory and the brain:
structure and processes. Current Opinion in Neurobiology, 11, 194-201.

McRae, K., et al. (1997). On the nature and scope of featural
representations of word meaning. Journal of Experimental Psychology:
General, 126, 99-130.

Mehler, Jacques, & Franck, Susana. (1995) Cognition on Cognition -
chapter 9

Miceli, G., et al. (2001). The dissociation of color from form and
function knowledge. Nature Neuroscience, 4, 662-667.

Morrow, D., et al. (1987). Accessibility and situation models in
narrative comprehension. Journal of Memory and Language, 26, 165-187.

Pulvermüller, F. (1999). Words in the brain\'s language. Behavioral and
Brain Sciences, 22, 253-270.

Pulvermüller, F. (2002). A brain perspective on language mechanisms:
from discrete neuronal ensembles to serial order. Progress in
Neurobiology, 67, 85--111.

Radvansky, G. A., & Zwaan, R.A. (1998). Situation models.

Schmalhofer, F., MacDaniel, D. Keefe (2002). A Unified Model for
Predictive and Bridging Inferences

Schneider, W., & Körkel, J. (1989). The knowledge base and text recall:
Evidence from a short-term longitudinal study. Contemporary Educational
Psychology, 14, 382-393.

Singer, M., et al. (1992). Validation of causal bridging inferences.
Journal of Memory and Language, 31, 507-524.

Spivey, M.J., et al. (2000). Eye movements during comprehension of
spoken scene descriptions. Proceedings of the Twenty-second Annual
Meeting of the Cognitive Science Society (pp. 487--492).

Stanfield, R.A. & Zwaan, R.A. (2001). The effect of implied orientation
derived from verbal context on picture recognition. Psychological
Science, 12, 153-156.

Talmy, Leonard,(2000) Toward a Cognitive Semantics - Vol. 1 - chapter1

van den Broek, P., et al. (1996). A \"landscape\" view of reading:
Fluctuating patterns of activation and the construction of a memory
representation. In B. K. Britton & A. C. Graesser (Eds.), Models of
understanding text (pp. 165--187).

Van Dijk, T. A., and W. Kintsch. (1983).Strategies of discourse
comprehension.

Yekovich, F.R., et al. (1990). The influence of domain knowledge on
inferencing in low-aptitude individuals. In A. C. Graesser & G. H. Bower
(Eds.), The psychology of learning and motivation (Vol. 25,
pp. 175--196). New York: Academic Press.

Zwaan, R.A. (1996). Processing narrative time shifts. Journal of
Experimental Psychology: Learning, Memory and Cognition, 22, 1196-1207

Zwaan, R.A. (2003), The Immersed Experiencer: Toward an embodied theory
of language comprehension.B.H. Ross (Ed.) The Psychology of Learning and
Motivation, Vol. 44. New York: Academic Press.

Zwaan, R. A., et al. (1998). Situation-model construction during
translation. Manuscript in preparation, Florida State University.

Zwaan, R. A., et al. ( 1995 ). The construction of situation models in
narrative comprehension: An event-indexing model. Psychological Science,
6, 292-297.

Zwaan, R. A., et al. (1995). Dimensions of situation model construction
in narrative comprehension. Journal of Experimental Psychology.\"
Learning, Memory, and Cognition, 21, 386-397.

Zwaan, R. A., Radvansky (1998), Situation Models in Language
Comprehension and Memory. in Psychological Bulletin, Vol.123,No2
p. 162-185.

Zwaan, R.A., et al. (2002). Do language comprehenders routinely
represent the shapes of objects? Psychological Science, 13, 168-171.

Zwaan, R.A., & Yaxley, R.H. (a). Spatial iconicity affects
semantic-relatedness judgments. Psychonomic Bulletin & Review.

Zwaan, R.A., & Yaxley, R.H. (b). Hemispheric differences in
semantic-relatedness judgments. Cognition.

## Links

Cognitive Psychology
Osnabrück

Summer School course on Situation Models and Embodied Language
Processes

Dr. Rolf A. Zwaan\'s Homepage with many
Papers

International Hanse-Conference on Higher level language processes in
the brain: Inference and Comprehension Processes
2003

University of Notre Dame Situation Model Research
Group