Research Matters - to the Science Teacher
No. 9003 March 1, 1990
Definition and Assessment of the Higher-Order Cognitive
Skills
by Audrey B. Champagne, Professor of Science Education, State
University of New York - Albany, Albany, NY
Introduction
Imagine glass cylinders containing different quantities of sand.
Students are supplied with three cylinders, one of which is
completely filled with sand, and an inclined board. They are
encouraged to observe the motion of the cylinders as they roll down
the incline. Then students are shown a fourth cylinder and asked to
predict how that cylinder will roll down the incline. How would your
students respond to this exercise? Will they agree with your
interpretations of the students' behavior? My experience suggests
that you and your colleagues will probably not agree. However, this
is an empirical question-if you doubt my premise, try the experiment.
The exact manipulative exercise is not important, but having the
students and some colleagues participate is crucial.
Observers interpret performance on tests of the higher-order
cognitive skills differently because there are no agreed-upon
operational definitions of this skills. Developing such definitions
is difficult, because our understanding of the skills is limited. For
example, we know very little about the relationships between the
higher-order skills and the lower-order skills. Improved instruction
and assessment of higher-order cognitive skills is contingent on
developing operational definitions of those skills. This is the aim
of this paper.
How are lower-order skills distinguished from
higher-order skills?
- Are the two levels distinguished by age? Do children, by
definition, engage only in lower-order thinking and adults engage
only in higher-order thinking?
- Are the two levels distinguished by the frequency with which
we observe them in the population? Are higher-order skills by
definition rarer than lower-order ones?
- Is content the distinguishing characteristic? Are higher-order
skills only exhibited in the context of a formal
discipline-mathematics, physics, economics-or can they be
exhibited in practical situations such as automobile repair or
dressmaking?
- Are definitions of higher-order skills idiosyncratic-that is,
does an observer categorize a skill as higher order if it produces
a solution to a problem that the observer could not do?
If you accept the assertion that operationally defining the
higher-order thinking skills is difficult but potentially useful;
then, you might try collecting and categorizing cognitive skills like
naturalists collect and categorize plant and animal specimens. You
can collect samples from practitioner journals, research journals in
science education and the cognitive sciences, teachers' manuals for
science textbooks, curriculum guides, and technical manuals for
standardized science tests. When a number of skills have been
identified, it is possible to build a taxonomy for the skills.
I found such a collection and categorization activity useful in
illuminating some of the uncertainties in our understanding of the
higher-order cognitive skills. The ordered list of skills that I
collected is displayed in Figure 1. The list is quite long, but
undoubtedly incomplete. You will have little difficulty collecting
new skills and adding them to my list.
Figure 1 - A Collection of Cognitive
Skills
Higher-Order Cognitive Skills
Lower-Order (Algorithmic)
Generic
Metacognitive
Assess Understanding
Assess Validity of Generalizations
Test Facts Against Rules of Evidence
Reasoning
Logical
Inductive
Deductive
Analogical
Creative
Verbal
Spatial
Qualitative
Quantitative
Discipline (Content) Specific
Task Specific
Problem Solving
Patterns of Knowledge
Generic Problem Schemata
Rate
Limit
Proportion/Ratio
Discipline
Formulas
Algorithms
Facts
Rules
Procedural Skills
Heuristics (Strategic Knowledge)
Evaluate Progress
Constraint Satisfaction
Progressive Refinement
Means-ends Analysis
Setting Goals
Monitoring Progress
Making and Adapting Plans
Problem Decomposition
Problem Decontextualization
Elaboration
Reasoning (Rule Based Information Processing)
Inquiry
Generic
Discipline Specific
Scientific
Discipline Knowledge
Procedural Knowledge (Conducting an Inquiry)
Planning and Implementing an Investigation
Problem Definition
Hypothesis Generation
Apparatus Selection
Observation
Data Management and Analysis
Identify Patterns
Graphing
Extrapolation
Generalization
Modeling
Mathematical Learning
The first sort in my taxonomy produces two categories of cognitive
skills, higher-order and lower-order. Leaving aside for the moment
which skills belong in which category, and which criteria influence
this decision, the relationship between the higher- and lower-order
skills is an issue central to the practice of science teaching and to
theory in psychology. Are the higher-order skills simple
concatenations of lower-order ones or are the two kinds of skills
qualitatively different? Your answer to this question will profoundly
effect the way you teach these skills. If you believe that
higher-order skills are concatenations of the lower ones, your
teaching strategy will probably be based on analysis of higher-order
skills that breaks into simpler skills. Each of the simpler skills is
then taught. The assumption underlying this strategy is that when the
individual skills are all learned, the higher-order ones will be
also. This basic idea of building skills from the bottom up pervades
our educational practice and was the theoretical basis for the
instructional model used in Science: A Process Approach
(SAPA).
If, on the other hand, you believe that higher-order cognitive skills
are qualitatively different from concatenations of lower-order ones,
your instruction will probably be more like that used in the
Elementary Science Study (ESS) materials. The assumption underlying
the instructional model used in the ESS materials, is that the
higher-order skills develop as the result of understanding related
phenomenon.
My taxonomy proceeds to sort the higher-order skills into three
categories: problem solving, learning, and inquiry (See Figure 2).
There are other ways in which they can be sorted, such as according
to the kind of cognitive task, they might have been sorted according
to the discipline or context in which the skills are demonstrated.
The result of a discipline-based sort is illustrated in Figure 3.
These sorts produce different categories and illuminate another
important issue that has both practical and theoretical importance:
Are the higher-order skills task or discipline specific?
Figure 2 - Higher-Order Cognitive Skills Sorted
According to Task
Task Specific
higher-order
skills
math
physics
problem solving chemistry
economics
(etc)
math
physics
higher-order learning chemistry
skills economics
(etc)
math
math
physics
inquiry chemistry
economics
(etc)
Figure 3 - Higher-Order Cognitive Skills Sorted
According to Discipline
Discipline Specific
learning
chemistry problem solving
inquiry
learning
higher-order physics problem solving
skills inquiry
learning
economics problem solving
inquiry
This question is the subject of major research efforts in
cognitive psychology. The goal of this research is to understand the
relationship between knowledge about a discipline and performance of
problem solving, learning, and inquiry skills in the context of the
discipline. The current research in cognitive science implicates
discipline knowledge in successful performance of most higher-order
thinking skills. Studies of experts' problem solving confirms the
importance of discipline knowledge and illuminates important
differences in the discipline knowledge "of experts and novices".
Experts' knowledge is highly structured in ways that facilitate
problem solution. This suggests that when students practice the
solution of problems, they are not only learning how to solve the
problems. They are also restructuring knowledge of the discipline in
ways that will facilitate future problem solution. Problem solution
serves as both a method for learning (structuring) content and a way
of demonstrating understanding of the content. Another significant
characteristic of experts' knowledge is that much of it is automatic.
The simple formulas, algorithms, facts, and rules of the discipline
are recalled and applied so rapidly that most experts do not even
mention that they are using them unless specifically asked. This
suggests that some memorization is in order if students are to act
like experts. They just can't do problems without basic
information.
Experts have another kind of knowledge that facilitates problem
solution. This is knowledge about problem schemata. Upon reading a
textbook problem, an expert will often identify it as a momentum
problem, or a kinetic energy problem, or a mixture problem, or a rate
problem. Experts categorize the problem by comparing it with problem
schemata stored in their memories. No matter what the physical
context described in the particular problem type in her repertoire of
problem schemata. Having categorized the problem the expert also has
available a method for solving the problem.
With all of this talk about the importance of knowledge, you might
get the idea that there are no generic problem skills. This is not
the case. Expert problem solvers also exhibit procedural skills that
facilitate problem solving. Some of those skills are listed in Figure
1. Some investigators in the field call these procedural skills
heuristics. Others call them strategic knowledge. The use of these
different terms further confuses the distinction between knowledge
and cognitive skills.
The many theoretical issues surrounding the relationship between
knowledge and cognitive skills are by no means resolved. In addition,
the theoretical issues have corresponding instructional ones. Do the
higher-order skills transfer? In practice, that is, in teaching and
testing, the skills are generally treated as if they are discipline
specific. However, educators and laymen alike are often talk about
the skills as if they are generic. If students learn to think
scientifically in science class, will they think scientifically in
context outside science class? Popular belief aside, the mounting
evidence is that students leave their scientific knowledge and
thinking skills in science class and use other knowledge and skills
in their encounters with the real world.
Renewed emphasis on teaching the higher-order skills requires that
science teachers reconsider some basic questions about the
relationship between cognitive skills and discipline learning. Are
these skills best taught/learned in the context of a discipline, or
in separate skills-development courses that focus on rational
thinking, problem solving, inquiry, and critical or creative
thinking? Do the higher-order cognitive skills transfer? If so, under
what conditions? Are the sciences particularly good disciplines for
learning the higher-order skills? If so, how should instruction be
modified to produce better results? The answers to these questions
are not at all clear.
Most of the work in cognitive psychology suggests that use of the
higher-order cognitive skills is closely linked with discipline
specific knowledge. This conclusion is based primarily on research on
problem-solving and learning-to-learn skills. Consequently, the
conclusion is limited to these specific higher-order thinking skills.
The findings may be quite different for higher-order skills such as
metacognition, and logical, analogical, inductive or deductive
reasoning.
All of this comes back to the original point: As a community of
educational practitioners and researchers, we need to be more
scientific in our approach to teaching and assessing the higher-order
cognitive skills. Common operational definitions for these skills are
a necessary condition for more scientific teaching and research to
attain the all-important goal of science education: scientific
thinking in students.
References
Segal, J. W., Chipman, S. F., & Glaser, R. (Eds.) (1985).
Thinking and Learning Skills. Volume 1: Relating Instruction to
Research. Hillsdale, New Jersey: Lawrence Erlbaum
Associates.
deBono, E. (1976). Teaching Thinking. London: Temple
Smith.
Lockhead, J. & Clement, J. (eds.) (1979). Cognitive
Process Instruction. Philadelphia: Franklin Institute Press,
1979.
Linn, M. C., Pulos, S., Gans, A. (1981). Correlates of formal
reasoning: Content and problem effect, Journal of Research in
Science Teaching, 18, 435-447.
Research Matters - to the Science
Teacher
is a publication of the National Association
for Research in Science Teaching
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