Lohman, D. F., Lakin, J.
M., Sternberg, R. J., & Kaufman, S. B. (2009).Reasoning and intelligence. Handbook of intelligence, 419-441.
This is a wonderful chapter about reasoning, which
is part of the fluid ability.
Almost every sentence in this chapter is significant. Here I'll focus on some of the ideas that
were especially interesting to me.
Reasoning processes,
comprehension knowledge and learning
.
People who solve problems efficiently
usually turn their attention, sometimes even unconsciously, to different
aspects of the problem than people who solve problem less efficiently. People who are efficient problem solvers know what to look for and
what to ignore. This results from more
experience that they have with similar problems and from an ability to make
good use of their past experience.
Good thinking about complex problems
depends on knowledge. Expertise is based
on knowledge, and experts think about problems differently than novices. Good reasoning leads to better
organization of knowledge in memory. Every reasoning process we perform depends on
the efficiency of the reasoning processes we performed in the past, and on the
ways we stored the products of these processes in memory. An increasingly sophisticated
knowledge base supports increasingly sophisticated forms of reasoning. A more
sophisticated knowledge base has richer, more abstract associative connections
between concepts and more metacognitive knowledge that links strategies to
goals. In other words, the better our reasoning
processes are, the more complex our comprehension knowledge, which is the
product of these reasoning processes, will be.
Reasoning abilities are apparent even in a
vocabulary test. Individual differences
in a vocabulary test can result from the extent to which we use metacognitive
processes when we learn words. For
instance, do we systematically examine alternative meanings of a word when we
hear it in an unfamiliar context, or do we remain with a vague understanding of
it? When we infer that a word has
additional meanings, and understand them with precision, we are able reorganize
our comprehension knowledge in a way that will assist us in future
learning. Researchers argue, that the ability to derive word
meanings out of the contexts in which they are heard may be the cause of the
high correlation that usually exists between vocabulary and reasoning tests
(and also between vocabulary and g). A wide vocabulary enables the understanding
and expression of a wider variety of ideas, and assists in learning new words
and concepts. Thus language functions as
a tool for expression, refinement and acquisition of thought, and the modest
vocabulary test requires reasoning processes and is a product of reasoning
processes.
Choosing what
knowledge to apply to a new problem is a nontrivial source of reasoning
complexity. Developmental psychologists have long known that children reveal
much about the sophistication of their reasoning by how they classify or sort
objects: on the basis of an arbitrary association, or by using perceptual
characteristics, or, at the highest level, by using several different abstract
concepts. Therefore, deciding how best
to describe the relationships among two or more concepts is a critical step in
reasoning. Poor
reasoners often settle for a vague relationship or rule rather for a more exact
one. This could be because they
terminate the search for a rule or relationship too quickly, or because they do
not critically examine how well candidate rules or relationships describe the
data, or because they simply do not see or know the rule.
It's possible to practice and train
deductive thinking (applying known rules to specific cases), or at least, it's
possible to improve performance in specific tasks that measure deductive
thinking. This means that
deductive reasoning tests can measure different abilities in examinees who have
learned strategies for solving problems like those used on the test than for
examinees who must invent a strategy on the spot. For people who
practiced, performance on such tests leans much more on the retrieval of the
learned strategy out of the knowledge base.
For people who did not practice, these tests are much more fluid.
Reasoning processes require ongoing
activation of executive functions like monitoring, feedback, planning,
adjusting existing strategies to the new situation and inventing new
strategies, and the ability to learn from past attempts to solve the
problem. Reading comprehension, for
example, requires updating our mental model of the text with new information received during reading. For instance, if we perceive one of the
characters in our mental model as a bad person, and we read about a good deed
this person did, we update our mental model of him. Children with monitoring difficulties (executive
function difficulties) find it hard to do that.
They may stick with the initial impression they formed of this
character, and fail to update it with later incoming information.
Naïve
interpreters of reasoning tests think that reasoning ability influences achievement
level (in other words, they see causal arrows running
only from reasoning ability to achievement).
But both reasoning ability and achievement are products of leaning and
experience.
Understanding a story, inferring the
meaning of an unknown word, recognizing patterns and rules in information,
abstracting the given information in order to create rules or principles,
applying mathematical concepts to solve a problem – in these and in many other
ways, successful learning requires reasoning strategies. The best way to develop reasoning is through challenging instruction
that requires students to practice familiar reasoning strategies and to invent or
to learn new strategies. Thus, learning
requires reasoning, but the learning process itself develops reasoning.
In the past it was believed that it's good to adjust the
instruction method to the learning style (for example, to give more verbal
instruction to a people who prefers verbal learning and to give instruction
with more graphs and visual material for people who prefer to learn via visual
images).
Contrary to the expectations of virtually all, the profile of specific learning
styles generally does not account for much of the variation in outcomes.
Indeed, interactions between learning styles (such verbalizer versus
visualizer) and instructional methods (such as an emphasis on visual versus
verbal media) are usually small. Instead, it is advisable to
adjust instruction style to the learner's cognitive abilities. For example, a child with poor reasoning
ability can be taught with more examples, and with more explicit explanations. A child with poor comprehension knowledge can
be given texts that are linguistically simpler. Vocabulary from the text can be taught in
advance. The general information
required to understand the text can be also pre-taught.
Reasoning ability
and working memory.
Theories that attempt to explain reasoning
processes assume there are phases in the inference process that include: A. Representing the premises in working
memory. B. Creating mental models of possible solutions
that are derived from the premises, holding these models simultaneously in
working memory and comparing them. These
processes demand significant working memory resources.
Thus limitations in working memory cause individual differences in
reasoning abilities.
Since working memory limits the number of
mental models that can be held simultaneously in working memory, people with a
limited working memory capacity may not succeed in creating enough models to
evaluate the validity of a conclusion.
Researchers find a large overlap between fluid
ability and working memory. The authors
of this chapter argue that this overlap is caused by fluid ability being measured
too narrowly and working memory being measured too broadly.
The authors
claim that matrices tests that require nonverbal reasoning predict learning and
academic achievement in the real world less well than measures of verbal and
quantitative reasoning (for example, verbal analogies tests or mathematical
series tests). Thus, when we assess
reasoning with one test like the Raven, or similar tests, we don't represent
all aspects of the reasoning process.
On the
other hand, working memory tests are more complex than it seems. These tests involve understanding directions
that are fairly complex (for example, in the number – letter series test), forming
a strategy and sometimes altering it, performing a difficult task with high
demands for attention, and keeping a high degree of continuous effort. These tasks also require executive functions
– monitoring the process, inhibiting wrong responses, and switching sets
flexibly. Thus, working memory tests
contain fluid aspects.
To summarize: reasoning abilities are not static. They develop through experience and are
easier to perform after training.
Individual differences in reasoning correlate significantly with the
amount of information people can hold in working memory while performing a
manipulation. The ability to do this
depends on the attention resources that a person has, on his degree of
familiarity with the information, and on his experience with the performance of
the required manipulation. Thus, prior
knowledge and skills determine to a large extent the level of reasoning that
can be reached in reasoning tests and in reasoning situations in daily life.
When assessing fluid ability, it's
important to include a broad range of tests, not only matrices tests that intentionally
decrease the contribution of comprehension knowledge to the reasoning
process. It's important to include tests
requiring verbal and quantitative reasoning, which are closer to the way fluid
ability works in real life.
This chapter emphasizes the importance of
looking at fluid ability clinically – on the ways it is expressed in tests that
do not measure it directly (for example, looking at the child's level of
conceptualization when he defines a word, and at his ability to understand
implicit meanings in texts). It also
emphasizes the dependence of fluid ability on other abilities like working
memory and comprehension knowledge, and the interaction between them.