UNIVERSITY OF UTAH
The Situated Application of
Learning
A Summary of Learning Theorists and Their
Influence
Rose Defa
12/7/2011
IDET 6431, Fall 2011
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The Situated Application of Learning
Situated learning through anchored instruction as a means of effective knowledge acquisition
(P.Driscoll, 1994) is evident in various and evolved forms throughout much of instructional
design literature. This paper will trace the theories that present related concepts and specifically
how problem-based instruction can lead to students better able to develop the mental structures
most useful in transfer of knowledge. An analogous theme will review the impact on
instructional settings in general.
Anchored instruction was introduced in 1990 by the Cognition and Technology Group at
Vanderbilt (CTGV) as a means to facilitate situated learning. (Driscoll, 1994, p. 177) The focus
at that time was the use of "video-based anchors as 'macrocontexts' for teaching and learning."
(Cognition and Technology Group at Vanderbilt, 1993, p. 53) The videos were designed using
stories rather than lectures. The stories portrayed realistic situations that simulate contextualized
learning.
The concept of context-based learning had emerged even earlier. The Collins-Stevens theory,
Inquiry Teaching (1983), which explores effective teaching techniques for discovery learning,
outlines a framework of 1) the goals and subgoals of teachers, 2) the strategies used to realize
different goals and subgoals, and 3) the control structure for selecting and pursuing different
goals and subgoals. (p. 251) Here is where we start to see similarity with situated learning –
teachers pursuing goals where strategies include selecting cases, principles and theories (causal
structure) that demonstrate the real world of the learner.
The goal of Inquiry Teaching is to teach a general rule or theory and how to derive a general rule
or theory. Collins and Stevens identified 10 teaching strategies and their application in multiple
domains and they elaborated on the importance of using appropriate strategies to select the cases.
Causal structure may not be useful in all types of content, such as teaching facts, but if the
strategies (selecting positive and negative exemplars, selecting counter examples, generating
hypothetical cases, etc.) are constructed as an inquiry approach to discovery they can accomplish
the high-level learning desired. Overall, Collins believed students using high-level processsing
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skills such as forming hypotheses learn to construct new rules and theories by dealing with
specific cases and applying new knowledge to new cases – turning learning into problem
solving. (p. 276)
During the same time period David Merrill's Cognitive Display Theory (CDT) (Merrill, 1983)
proposed a set of prescriptions for achieving outcomes within a learning goal. His narrow
approach, which does not attempt to integrate instructional design knowledge, (although he has
drawn, most notably for this paper, on Bruner) focuses on which model to use considering two
dimensions: type of content and desired level of performance (p 281). Merrill's performancecontent classification system, three levels of performance and four types of content, form the
basis for objectives or test items. One of the most useful outcomes of the CDT theory is the
Specifications of Objectives chart (p.292) which calls out input and output for assessing
performance. CDT contributes the most to problem-based learning in consideration of learner
control. For example, through the selection by the learner of relevant, contextualized examples,
practice items and elaboration, Merrill hypothesized that conscious cognitive processing could
facilitate learning. CDT, by its very nature, is embedded and system controlled, but student
controlled options allow for redefining the instruction so that the student can search for internal
or external resources to elaborate on the instruction - enhancing the development of learning
strategies (especially for ill-structured learning environments) and problem-solving. Overall,
Merrill recommends CDT as most appropriate for self-paced materials and instruction that uses
an instructional management system, both which facilitate situated and problem-solving
instruction.
Again, during this time, Elaboration Theory emerged with a set of relationships to integrate
knowledge and instructional design. Ruegeluth & Stein (1983) built on Bruner to develop the
concepts of simple to complex, epitomizing, and prescriptive theoretical structures to scaffold
upper level learning. Elaboration moves a learner from understanding the basic characteristices
of an epitome to organizing and mastering the application. The use of analogy or situations and
anchoring helps the learner move from familar ideas to new knowledge.
This type of learning allows learner control through simple to complex sequencing and clearly
labeled and separate instructional components. For example, an epitome lesson would present
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the learning prerequisites through motivational strategy, analogy or the organization of content
ideas and then synthesize those ideas through elaboration and scaffolding. Ideas and learning are
supported through creating relevant situations and opportunities to reconstruct knowledge in new
situations - situational problem-solving.
Cognitive flexibilty, developed by Spiro, et al, (1992), focused on applying knowledge to new
applications (p. 59) especially in ill-structured domains. But to do so, Spiro was clear that
learners need to represent knowledge from different conceptual and case perspectives. Learners
reassemble pre-exising knowledge to fit the new situation. He purported that that flexible
learning environments, non-linear learning and the computer were all ideal medium for the reassembly of pre-exising knowledge to fit a new situation.
According to Spiro, "All domains which involve the application of knowledge to unconstrained
naturally ocurring situations (cases) are substantially ill-structured." (p. 61) The mastery of
complexity and transfer are possible when students reach more advanced treatments of subject
matter. Facilitating this requires that the instruction go beyond simply retrieving knowledge from
memory in a learning situation to the ability to flexibly reconstruct background information
relevant to the situation. Spiro presents as one solution structuring hypertext learning
environments where multiple exposures through multiple contexts support transfer of problem
solving. (p. 71)
Cognitive load theory became pivotal to understanding the differences between novices and
experts where the mastery of more complex information requires effective problem-solving
abilities. Sweller (1988) determined that "domain-specific knowledge in the form of schemas, is
the major factor in distinguishing experts from novices in problem-solving skill." (p. 258) He
suggests that the traditional method of practicing on many problems is an inefficient way to gain
problem-solving skill because the learner uses limited working memory to focus on attaining the
goal rather than on gaining the schema of how the problem is structured – a necessary
acquisition for knowledge transfer and building related advanced knowledge structures.
Sweller and Chandler (1991) continued to study the relationship between learning and problem
solving. Experiments during the late 1970s and the 1980s indicated that in some cases, learning
and problem solving were incompatible, particularly in that means-end processing of problems
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did not result in learning the structure of problems. Schema and cognitive load theory began to
be used extensively not only to explore the differences in problem-solving skill between novices
and experts, (p. 352) but to analyse the effects of different types of instructional designs.
Cognitive load theory generated many experiments demonstrating the effects of goal-free
problems, worked examples, split-attention and redundancy on instructional effectiveness and
most importantly, learning. These effects and the implications for learning encourages
instructional designers to reduce cognitive load.
Sweller (1994) analyzed intrinsic and extraneous load as an explanation for difficulty in
mastering information. They explored the natural origins of difficulty (the level of difficulty of
the material itself); artificial difficulty (which can be alleviated by instructional management)
and procedures to reduce difficulty. They found that cognitive load effects can be useful in
determining instructional designs that contribute to learning efficiency. Since most knowledge is
encapsulated in schemas which reduce the amount of working memory needed during learning,
careful attention to intrinsic and extraneous load can substantially enhance efficient learning,
particularly in high level learning, by reducing the number of interacting elements with which
the working memory must deal, and avoiding split-attention and redundancy effect. Later,
Sweller, et al (1998) demonstrated that appropriate instructional design (goal-free problems,
particularly in math and science, worked examples, completion problems) can be effective where
problem-solving performance is critical.
Most recently, Schrymer and Spiro (2009) suggested revisiting cognitive load theory and
learning goals in ill-structured domains, especially to acquire flexible knowledge. (p136) Their
work examined learning via the Web as the "quintessential multimedia environment for complex
learning, particularly in ill-structured domains." (p134) However, learners in this environment
"must be prepared for discovery, complexity, change and creativity."
I would suggest that the Web may be the ultimate situated learning - where learners explore
connections, comparisons and contrasts in new contexts and through comparing multiple
examples of situational information. (p. 137) The authors discuss the implications of cognitive
load including the effects of affordance, motivation, and redefining germane cognitive load in ill-
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structured domains, concluding that "web learning (in ill-structured domains) holds great
promise" (p. 148) for freeing resources for knowledge acquisition.
Cognitive load cannot always be avoided; in fact, oversimplification or neglecting in-depth
materials can interfere with building the schemas required for later acquisition of complexity.
While well-structured domains are easily suited to construction and automation of schemas, illstructured knowledge relies on germane cognitive load to build interconnections. Many of the
techniques for creating sophisticated schemas are natural to a web-based instruction, "crisscrossing knowledge landscapes, experiencing multiple perspectives, patterns of context
dependency, identifying how surprising similarities and surprising differences unfold." (p142)
The research is still undefined on the benefits of deep learning on the Web, but I would argue
that the technological revolutions (particularly now Web 2.0) allow for dramatically increased
flexibility in situating, anchoring and contextualizing learning to create the instruction that
minimizes extraneous cognitive load while maximizing the creation of schemas for advanced
knowledge through application of germane information.
Most simply put, the situated, anchored, problem-based value is that humans have constraints to
information; they learn by manipulating relevant information and creating new structures to
apply that information. Instruction that facilitates developing rich schemas in long-term memory,
efficiently retrieving relevant information into working memory (matched to the learner's
abilities and context) will result in the desired spiral of learning.
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