Low Element Interactivity Material

Low Element Interactivity Material
Laboratory-based paired associate learning tasks provide one example of
learning low element interactivity material. Each paired associate can be
learned without consciously considering any of the other paired associates
that require learning. In that sense, the elements of the task do not interact.
They can be learned in isolation without imposing a heavy cognitive load
and without any loss of understanding of the task at hand.
Many realistic tasks resemble paired associate learning. Learning the
names of any set of entities such as people’s names, the vocabulary of a
second language, or chemical symbols provide examples. Such material may
be diYcult to learn because there may be many elements that require
learning, but the diYculty is unrelated to cognitive load. The elements can
be learned in serial fashion without loss of understanding. Indeed, the
concept of understanding is not normally applied to the learning of such
material. One may have not learned or forgotten a particular foreign word,
such as the translation of the word ‘‘cat,’’ but one does not fail to
‘‘understand’’ the word. The distinction between rote learning and learning
with understanding does not apply to such material. Failure to understand is
reserved exclusively for high element interactivity material for which there is
a heavy load if it is to be learned with understanding (Marcus, Cooper, &
Sweller, 1996).
2. High Element Interactivity Material
Modern examples of high element interactivity material include learning the
syntax of a second language, deriving meaning from words or symbols,
Evolution of human cognitive architecture 217balancing chemical equations, or most areas of mathematics. Examples
of high element interactivity information that our ancestors had to
process at a time when the human cognitive system evolved to its present
point include learning a spatial layout, such as a route from point A to
point B, learning to find food and shelter, learning to avoid danger,
or learning complex social relations. To demonstrate the concept, the
element interactivity associated with learning some of these areas is
considered next.
While much of the vocabulary of a second language can be learned
element by independent element with little or no interactivity, syntax cannot
be learned in this manner. Elements interact and must be processed
simultaneously for understanding and learning to occur. For example, word
order is important in English, and word order cannot be learned without
considering several words simultaneously. Consider the two sentences:
‘‘Word order is important in English’’ and ‘‘English in important is order
word.’’ One cannot learn that the first is grammatical but the second is not
by considering each word in isolation. Learning the appropriate order of
words in English requires the learner to consider all of the relevant words
simultaneously. Each word and its interaction with at least some and, in
some cases, all of the other words must be considered. Element interactivity
is high and, as a consequence, cognitive load is high because at least at
some point, all of the elements and their relations must be processed
simultaneously.
Understanding and learning the structure of any mathematical process
that incorporates an equation invariably involve a high degree of element
interactivity. Assume a student is learning how to make a the subject of
the equation a=b ¼ c. In order to understand and learn the procedure, the
structure of the initial equation must be considered, the numerator on
the left side must be multiplied by b, which means the numerator on the
right side must be multiplied by b in order to retain the equality, and the b in
both the numerator and the denominator must be canceled, leaving the
solution a ¼ cb. While this procedure can be memorized step by step,
understanding only occurs when the entire procedure can be processed
simultaneously. Multiplying the left side by b without multiplying the right
side by b simultaneously reflects a lack of understanding of the procedure.
The entire procedure needs to be processed simultaneously if it is to be
learned with understanding rather than by rote because all of the elements
that need learning interact. Rote learning will reduce cognitive load
substantially, but at the cost of understanding. Learning with understanding
imposes a heavy cognitive load because the elements that require learning
interact and so must be processed simultaneously if appropriate meaning is
to be derived.
218 John Sweller3. An Alternative Conceptualization of Element Interactivity
Halford, Wilson, and Phillips (1998) have provided a formal model of what
they term ‘‘relational complexity’’ that provides an alternative to the
concept of element interactivity. The model was intended primarily to
provide a metric measuring individual diVerences, including developmental
diVerences, in working memory. Nevertheless, it can equally provide a
measure of the working memory load imposed by various tasks, especially
problems that require solution. The model assumes that any task or problem
can be characterized by the number of dimensions that need to be related. A
unary dimension relates constants: The cat walked, provides an example. A
binary dimension relates two variables, ternary dimension three variables,
quaternary four variables, etc. The proportion a=b ¼ c=d is an example of a
quaternary relation with its four variables. The number of dimensions that
must be related provides the relational complexity of a task or problem, and
the number of dimensions that a person can process in working memory
provides a measure of working memory capacity.
Relational complexity and element interactivity may well be diVerent
terms for the same concept. Because element interactivity was devised
specifically to measure diVerences in working memory load imposed by
diVerent tasks has been applied experimentally to a very wide variety of
tasks (e.g., see Marcus et al., 1996; Sweller & Chandler, 1994; Tindall-Ford,
Chandler, & Sweller, 1997) and, as shown later, has been closely related to
schema-based knowledge held in long-term memory, it is used in this
chapter. Nevertheless, the similarity and perhaps identity of element
interactivity and relational complexity need to be kept in mind.
How has human cognitive architecture evolved to handle these infor-
mation structures? In particular, how do we handle intellectually diYcult,
high element interactivity material? Finding one’s way around new
locations, understanding relations between the environment and food
sources or the environment and danger, and establishing social relations and
interactions with friends and enemies have been part of human life for a very
long time and, along with a myriad of other activities, can all involve high
element interactivity information. The nature of the mechanisms required to
deal with these situations is discussed next