Download Side-note of Interest: Representation of Images

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Cognitive Information Processing: The Computer as Metaphor
Dr. Eva Mary Bures
EDU301 Educational Psychology FALL 2010
The cognitive information processing perspective focuses on the learner as a processor
of information, analogous to a computer. The overall view is that the learners’
information processing system intervenes between the environment and human
behaviour. Most models of information processing are based on a multistore, multistage
theory of memory. The chapter describes the basic components of memory from this
perspective — sensory memory, short-term memory and long-term memory — as well
as the processes hypothesized to help transfer information from each stage to the next.
Others were interested in the study of cognition (i.e. Vygotsky, Gestalt psychologists).
What distinguishes cognitive information processing is that it relies on the computer as
a metaphor. After World War Two, the computer provided an organizing powerful
metaphor for developing models of human memory, perception and learning. Stimuli
became inputs, and behavior became outputs, with the information processing system
of the learner coming in-between.
Important orienting questions:
What do these models address or explain that behavioristic models do not?
What is learning from this perspective as compared to from the behavioristic
perspective?
Sub-questions:
What kind of epistemological assumptions do you see in this approach?
Is there a conflict between cognitive information processing approaches and
behavioristic approaches or is there a potential complementariness as Driscoll
suggests?
The following notes sketch out the main concepts covered in the reading, and organize
the relevant research. These notes were taken with two main questions in mind:
(1) For each main component of memory, what research evidence contributes to our
understanding? What about for associated processes such as encoding?
(2) What are the instructional implications?
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Overview of Memory components
Most models include three components with processes assumed to help information
transfer from one to another.
1st stage Sensory memory
 holds information in memory briefly – just long enough to be processed
2nd stage Working/short-term memory
 further processing for long-term storage or response
 limited time and limited amount of information
3rd stage Long-term memory
 transferred from short term
 unlimited
Sensory Memory
Processes: Attention, Pattern Recognition, Selectivity, Automaticity
Sensory Memory &
processes
Sensory memory
Attention
Pattern Recognition
Some Relevant Research
Sperling (1960) partial report technique
-- participants can report 3 or 4 of 12 letters in an array of 3
rows; can report 3 or 4 of 4 letters if asked to report on one
row only
-- sensory memory is temporally, not visually, limited;
decays rapidly after 1/4 of a second
Darwin, Turvey & Crowden (1972) replicated Sperling
(1960) with auditory system; auditory decayed after 4
seconds
Broadbent (1957) -- attention seen as a bottleneck or filter
Treisman (1960) demonstrated that attention serves to tune
out stimulation, but not to filter it
i.e. you aren’t listening to another conversation, but if you
hear your own name you will notice
Grabe (1986), Kaheman (1973) demonstrated that
attention is a resource with limited capacity which must be
allocated and shared amongst competing goals; selectivity
helps focus attention; automaticity helps reduce need for
attention
Environmental stimuli recognized as ‘exemplars.’ Process
explained by several models: template matching (fails as
explanation – would need templates for all different A’s);
prototype model; feature analysis. None of these explain
why deteriorated ‘A’ is seen as an ‘A’ on a gravestone:
effects of context. Gestalt principles of organization
suggest we go ‘beyond the information’ given to construct
meaningful interpretation – principles of closure, and
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proximity and similarity effects
Selectivity
Automaticity
Past experience or prior learning can interfere in
appropriate recognition. The Stroop effect: an individual is
shown several color words (i.e. blue) that are printed in
different colors and is then asked to name the colors;
confusion results, and participants tend to name the actual
words
Sternberg & Davidson (1983): in problem-solving, students
often try to solve problems using familiar solutions;
providing them with practice in a variety of contexts can
help reduce this effect.
Good and Brophy (1984) suggest that teachers use
standard signals to influence attention (i.e. “let’s begin!”)
Grabe (1986) suggests that learners be taught to be less
impulsive in responding to a task and that they should be
trained in a strategy for focusing attention.
Shiffrin & Schneider (1977) showed that many procedures
are partially automaticized and partially controlled such as
in driving
LaBerge & Samuels (1974) found that decoding words
becomes automatic in processing text
Anderson (1982) found that readers allocate greater
attention to important elements in a text
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Working Memory
Processes: rehearsal and encoding
Working Memory &
associated processes
Working Memory
Rehearsal
Encoding
Some Relevant Research
George Miller (1956): demonstrated that subjects could
remember 7 +/- numbers. Memory span does appear to
cover this number of chunks (hence, chunking
strategies).
Brown (1958) and Peterson and Peterson (1959) tried to
estimate the duration of working memory. They presented
subjects with sets of 3 letters that they needed to recall. If
rehearsal is prevented, information is lost from working
memory in about 15 to 30 seconds. Rehearsal and coding
help address this loss.
Primacy effect: if subjects are given sets of items to
remember at a slow rate, subjects are able to remember
the most recent items (recency effect) as well as the first
few items (primacy effect). Rehearsal does not help
transfer information into long-term memory. Elaborative
rehearsal can.
Encoding means connecting new information to familiar
concepts and ideas. This makes new information more
memorable. Bousefield (1953) found that people related
information into categories to help learn them or
remember them. Tulving (1962) found that learners
impose their own organization onto even unrelated
information.
Many cognitive strategies to help learners encode
information have been studied.
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Long Term Memory:
Processes: retrieval
Long term
memory
Representation
of imagery
Retrieval
Recall
Recognition
Retrieval cues
Forgetting
Tulving (1972) distinguishes between episodic versus semantic
memory, where episodic refers to memory of specific events that
is entirely dependent on the context and semantic memory refers
to information that can be recalled independently of how it was
learned. Since Tulving, educators focus on semantic memory.
Several models of semantic long-term memory have been
developed i.e. network models, feature comparison models,
propositional models, parallel distributed processing (PDP)
models
Shepard et al (1978): when subjects have to find a match for a
rotated three-dimensional object, the time it takes to find the
match is directly related to the spatial rotation needed
Paivio (1971) posits a dual-code theory, one system for verbal
information, and another for non-verbal. This explains why
subjects can more easily remember concrete words such as
sailboats -- they draw on both verbal and non-verbal
representations
Kosslyn et al (1973) found that the time subjects take to estimate
the distance between two places on a map reflects the linear
distance between the places
To recall information, no cues or hints are provided to learners.
Subjects do not tend to remember much in these conditions.
Cued recall tasks involve cues that help learners remember the
important relevant information.
To judge reading comprehension, Royer et al (1984) present
learners with old-new recognition tasks. They need to recognize
an original sentence from the passage and a paraphrase of the
original sentence, and need to classify as new both a sentence
that is almost exactly the same as the original sentence with
altered meaning and a distractor sentence which is unrelated to
the original sentence.
Encoding specificity principle (i.e. Thomson & Tulving, 1970):
learners recall best when retrieval cues are the same cues they
used to facilitate encoding.
Common explanations for forgetting: failure to encode, failure to
retrieve and interference.
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Models of LTM
• For each model of memory representation (LTM), what phenomenon does it explain?
What phenomenon does it not explain? What are the basic units?
Model of
LTM
Network
models
Knowledge
Unit
nodes or
concepts
Feature
Comparison
Models
nodes or
concepts
Propositional
Models
proposition
(subject and
predicate)
Parallel
Distributed
Processing
(PDP)
subsymbolic
units and
connections
Relations
amongst units
relations
between nodes
are learned; take
the form of
interconnected
hierarchies
Evidence: what does it explain?
individual differences among learners
speed at which subjects will
recognize truth of statements i.e. a
blue heron has long legs versus a
blue heron is an animal (Collins &
Quillian, 1969)
fails to explain typicality effects i.e.
subjects fail to recognize a penguin
as a bird as quickly as they do a
canary
stored in sets of Smith, Shoben & Rips (1974)
defining
explains typicality effects: some
features;
members are better examples of
concepts are
concepts than are others. Defining
associated with
features are shared by all members,
one another if
whereas characteristic features may
enough features belong only to the more typical
overlap
members of a set.
helps deal with fuzzy concepts
- fails to account for semantic
flexibility
Kintsh (1974) found that subjects
take longer to read sentences
containing many rather than few
propositions, even with the same
number of words used.
In recall, sentence structure tends to
be lost, but propositions are
remembered.
Anderson (1976) has developed
ACT, a network model with
propositional structure.
processing is
account for incremental nature of
distributed
learning (Estes, 1988); integrate role
across a network of goals; may help explain cognitive
of units &
development by clarifying what is
connections;
hard-wired (McClelland, 1988).
weights are
Not clear that PDP models actually
associated with
represent the neural processes in the
the connections. brain (Estes, 1988).
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Implications on instruction:
Three major recommendations listed in the textbook:
Provide organized instruction
Make evident to learners the structure and relations of material such as through
concept maps or other graphic representations.
Arrange extensive and variable practice
Variable practice allows learner to generalize the concept, principle, or skill
beyond the context it was learned in (transfer of learning).
And reduce effect of past experience interfering (for example, in problem solving,
trying a technique for a familiar problem in the wrong situation)
Enhance learners’ self-control of information processing
Assist them in learning, selecting and using appropriate learning strategies such
as summarizing and questioning. Generally, learning strategies should be done
within a specific domain; students need to know how and why various selfregulatory strategies work.
Three variables influence metacognitive ability: person variables (i.e. older
people are more conscious of strategies and using them); task variables (i.e.
learner tends to use general learning strategies with new information and then to
use more content-specific ones as their expertise increases); and strategy
variables (some strategies such as breaking down a complex task are easily
acquired; others such as taking notes take extensive practice).
Other key implications:
Sensory Memory
techniques to help focus attention (limited resource)
Good and Brophy (1984) suggest that teachers use standard signals to influence
attention (i.e. “let’s begin!”)
Grabe (1986) suggests that learners be taught to be less impulsive in responding to a
task and that they should be trained in a strategy for focusing attention.
Learners’ goals and the features of the text influence their allocation of attention to
different elements (Anderson, 1982). Stimulus features, idea unit structure (placement
of ideas in a text), voice inflection or gestures, novelty, questions inserted into the text
and assigning instructional objectives can be used to focus students’ attention on key
aspects of the instructional materials.
Automaticity: LaBerge & Samuels (1974) suggest that learners should be able to
decode words automatically in order to read for meaning. Reading aloud and extended
word identification practice are two strategies to increase automaticity.
Other implications focused on pattern recognition:
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Drawing on feature analysis, Tennyson & Cocchiarella (1986) propose model for
teaching concepts: present a prototypic concept followed by examples that vary
systematically from it.
Past experience has an influence on pattern recognition. Knowledge can help; it scan
also interfere. Solving problems can require seeing things a different way. Practice on
many different kinds of problems may help (role of context becomes a variable they see
is important in solving problems).
Short-term Memory
Enhancing Rehearsal
To improve rehearsal, recognize limitations of short-term memory. Use the concept of
chunking: don't present 49 separate items, make them 7 groups of 7. Use elaboration
and multiple contexts.
Enhancing Encoding
Having and activating relevant prior knowledge – very very important.
Outlines, hierarchies and concept trees help people encode meaningfully.
Mneumonics (although some people are skeptical that this leads to deep processing)
and mediation.
Imagery.
Elaborative encoding better than mere repetition. But learners do develop own
idiosyncratic encoding strategies, which it may be best to encourage (i.e. Pressley &
Levin, 1983). i.e. invent own mnemonics; self-questioning.
Match encoding strategies with the material to be learned. To encourage deeper
processing, avoid mnemonic techniques.
Provide opportunities for both verbal and imaginal encoding. Concrete words are
remembered better than abstract ones.
Long-term memory
Enhancing retrieval
Cues can enhance students’ recall: implication is cue tasks i.e. add qualifiers to essay
questions.
Note-taking, elaboration
Decrease proactive interference especially with older adults: signal main ideas; visual
displays organizing information in concepts and showing structure.
Encoding specificity principle (i.e. Thomson & Tulving, 1970): learners recall best when
retrieval cues are the same cues they used to facilitate encoding: place (Bilodeau &
Schlossberg, 1951); drugs (Goodwin et al, 1969); emotions (Brown, 1981).
Representation in multiple perspectives and in multiple contexts.
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Other important implications will be discussed in chapter ten:
For example: Gagne’s nine events of instruction: gaining attention, informing learners of
objectives, stimulating recall of prior learning, presenting the stimulus, providing
learning guidance, eliciting performance, providing feedback, assessing performance,
enhancing retention and transfer.
Side-note of Interest: Representation of Images
One issue covered briefly in the textbook is the representation of information other than
verbal information. Imagery has been discussed since Platonic times. It has special
significance to educational technologists of our day. Research suggests that visual and
verbal information are not stored the same way. For example, Kosslyn, Ball & Reiser
found evidence that visual images preserve spatial information. Shepard & Metzler
(1971)
* Kosslyn, S.M., Ball, T.M., & Reiser, B.J. (1978). Visual images preserve metric spatial
information. Evidence from studies of image scanning. Journal of Experimental
Psychology: Human Perception and Performance, 4: 47 - 60.
Jolicoeur, P. & Kosslyn, S.M. (1985). Is time to scan images due to demand
characteristics? Memory and Cognition 13: 320-332.
• tested hypothesis that experimenter expectancy effects operated to increase times
in distance subjects perceived. were unable to replicate the effects found by IntonsPeterson (1983).
Intons-Peterson, M. J. (1983). Imagery paradigms: How vulnerable are they to
experimenters’ expectations? Journal of Experimental Psychology: Human Perception
and Performance 9: 394-412.
for applications to educational technology:
see Paivio dual-code theory applied to inclusion of multiple representations in
instructional materials and related research.
• What evidence exists concerning the role of images in memory?
• What are the implications of different type of mental representations for educational
technologists?
Précis of Mental Rotation of Three-Dimensional Objects
Shepard & Metzler (1971).
The experiment investigated the amount of time human subjects took to identify
whether 2-dimensional depictions of 3-dimensional geometric shapes were different.
Sixteen hundred pairs of geometric objects were presented to 8 adult participants. Of
these pairs, 800 were different, 400 were the same and differed by a multiple of a 20
rotation in the two dimensional picture plane (‘picture-plane pairs’), and 400 were the
same and differed by a multiple of a 20 rotation about a vertical axis (‘depth pairs’).
Participants were presented with a total of 800 unique pairs: each pair was shown
twice. The same pairs consisted of 20 depth and 20 picture plane pairs at each 20
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interval from 0 to 180 (10 different angles). In both the case of the picture-plane and
the depth pairs, the mean reaction times of subjects was linearly related to the angle of
rotation. Of course individual reaction times varied. Nonetheless, the linearity of the
relationships were evident. Each individual’s scores were plotted separately for each
type of rotation. In all 16 cases, all tests against deviations from linearity were
significant (p<0.001) and no quadratic relationships were found (p>0.05). The reaction
times suggested that subjects took roughly 60 per second for both 3-dimensional and
2-dimensional rotations to ‘mentally rotate’ the objects.