ERIC Identifier: ED481716
Publication Date: 2003
Author: Boston, Carol
Source: ERIC Clearinghouse on Assessment and Evaluation
Cognitive Science and Assessment. ERIC Digest.
Cognitive science is devoted to the study of how people think and learn
and how, when, and whether they use what they know to solve problems (Greeno,
Collins, & Resnick, 1997; National Research Council, 2001). The cognitive
perspective in education encompasses how learners develop and structure
their knowledge in specific subject areas and how assessment tasks might
be designed to enable students to demonstrate the knowledge and cognitive
processes necessary to be judged proficient in these subject areas. This
Digest provides educators with an overview of some important facets of
cognitive science research and suggests implications for classroom assessment.
HOW DO EXPERTS AND NOVICES DIFFER IN THEIR APPROACH TO PROBLEMS?
Education researchers study the thinking of experts in various subject
areas to gain an understanding of what concepts and procedures are most
important to teach and how they are interrelated. The concept is that educators
can and should be moving students along a continuum toward real-world subject
mastery based on a deep understanding of how subject knowledge is organized
(Bereiter & Scardamalia, 1986).
When faced with a problem, learners tend to search their memories for
a schema, or learned technique for organizing and interpreting information
in a certain subject, in
order to solve it (Rumelhart, 1980). Over time, individuals build mental
models to guide their problem solving efficiently so they do not depend
on trial-and-error approaches and can instead create analogies and make
inferences to support new learning (Glaser & Baxter, 1999).
When compared with novice learners, experts in a subject are notable
well-organized their knowledge is, which in turn enables them to see
patterns quickly, recall information, and study novel problems in light
of concepts and principles they know already (Glaser & Chi, 1988).
In other words, their schemas are well-connected and they are able to retrieve
chunks of information relevant to a task at hand. Experts also have strong
problem-solving skills. They know what they know and what they don'tknow,
and plan and monitor the implementation of various mental strategies (Hatano,
COGNITIVE SCIENCE IN THE CLASSROOM
Ideally, developmental models of learning could be created that note
progression and milestones as a learner advances from novice to competent
to expert and describe the types of experiences that lead to change. For
example, students generally have naive or intuitive understandings of the
sciences, based in part on misconceptions that are corrected as they are
exposed to new learning (e.g., Gabel, 1994, Feldman & Minstrell, 2000).
And while there are individual differences among learners, when large samples
are studied, patterns tend to emerge, particularly related to erroneous
beliefs and incorrect procedures. For example, there appear to be a certain
limited number of "subtraction bugs" that account for almost all of the
ways young children make mistakes when learning to subtract two- or three-digit
numbers, and these are constant even across languages (Brown and Burton,
Allowing for variations among learners, it is possible to discover the
pathways toward acquiring knowledge and use this information diagnostically.
example, Case, Griffin, and colleagues have developed an assessment
tool based on their empirical research regarding how children from ages
4 to 10 change in their
conception of numbers through growth and practice. While 4-year-olds
groups of objects, they have to guess if they face a theoretical question
such as, "Which is more--four or five?" Between 4 and 6, most children
develop a "mental number line" that helps them envision the answer to such
a question, even when actual objects aren't present. Between 6 and 8, children
gradually come to envision other number lines for counting by 2s, 5s, 10s,
and 100s. By 10, many children have a better understanding of the base-10
number system, which enables them to reach a more sophisticated understanding
of concepts such as regrouping and estimation (Case, 1996; Griffin and
Case, 1997). Teachers can use assessments based on this research to determine
their next steps in arithmetic instruction.
More research has been done about domain structure in some disciplines
others. Mathematics, physics, beginning reading, and U.S. history are
among the areas that have been studied (see, for example, Niemi, 1996,
and Wineburg, 1996).
Subject-area standards such as the National Council of Teachers of
Standards generally reflect current thinking on cognitive processes
and are a good
place for teachers to begin their explorations of this topic. The National
Council's How People Learn: Brain, Mind, Experience, and School
(http://stills.nap.edu/html/howpeople1/) provides another helpful introduction.
HOW DO LEARNERS STORE AND ACCESS KNOWLEDGE?
Memory may be divided into two types: short-term, or working memory,
determines how much mental processing can go on at any one time, and
memory, where people organize their content knowledge. Short-term memory,
or working memory, is connected with fluid intelligence, or the ability
to solve new and
unusual problems, while long-term memory is connected to crystallized
intelligence, or the bringing of past experience to bear on current problems
(Anderson, Greeno, Reder, and Simon, 2000). When students are learning
a new skill, they must rely heavily on their working memory to represent
the task and may need to talk themselves through a task. As the skill moves
into long-term memory, it becomes fluent, and eventually, automatic (Anderson,
To support the learning process, students can be taught meta-cognitive
techniques to reflect on and assess their own thinking. To improve
comprehension, for example, young children can be taught to monitor
understanding of passages by asking questions, summarizing, clarifying
uncertainties, and predicting next events (Palincsar & Brown, 1984).
HOW CAN ASSESSMENT DESIGNERS USE FINDINGS FROM COGNITIVE SCIENCE?
The design of any assessment should begin with a statement of purpose
assessment and a definition of the particular subject area or content
domain. How do people demonstrate knowledge and become competent in this
domain? What important aspects of learning do we want to draw inferences
from when measuring student achievement in a given subject area? What situations
and tasks can we observe to make the appropriate inferences?
Cognitive science calls for test developers to:
* Work from a deep knowledge of the central concepts and principles
of a given subject area, and the most important related information.
* Identify or develop those tasks that allow students to demonstrate
understanding and skills in these areas, as opposed to rote memorization.
* Make sure tasks or questions are sufficiently complex to get at how
students have organized their knowledge and how and when they use it.
* Emphasize the contents of long-term memory rather than short-term,
or working, memory by not burdening test-takers withrequirements to track
a large number of response options or major quantities of extraneous information
while answering a question.
* Emphasize relevant constructs--for example, a mathematics assessment
should not over-emphasize reading and writing, unless communicating about
mathematics is the skill to be measured.
* Not limit choice of item format. Both multiple-choice and
performance-based assessments have the potential to be effective or
Carefully constructed multiple-choice questions can tap complex cognitive
processes, not just lower level skills, as traditionally believed. And
performance assessments, though generally praised for capturing higher
level skills, may inadvertently focus on lower level skills (Baxter &
Glaser, 1998; Hamilton, Nussbaum, and Snow, 1997; Linn, Baker, & Dunbar,
* Regard task difficulty in terms of underlying knowledge of cognitive
processes required, rather than statistical information such as how many
respondents answered correctly.
At the classroom assessment level, cognitive science findings encourage
* Teach learners how and when to apply various approaches and procedures.
* Teach meta-cognitive skills within content areas so learners become
capable of directing their thinking and reflecting on their progress.
* Observe students as they solve problems.
* Have students think aloud as they work or describe the reasoning that
leads them to a particular solution.
* Analyze student errors on assignments or tests to determine which
students got a question or problem wrong and why it appeared difficult
for them. Knowing the source of difficulty can lead to more targeted, effective
Teachers should also be aware that acquiring important knowledge and
skills at an
in-depth level takes a significant amount of time, practice, and feedback.
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