Download Declarative Knowledge

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Three points for today
1. We distinguish between two types of
knowledge – Procedural and Declarative.
2. Knowledge comes in several unit sizes, from
small (concept) to big (schema), with units at
one level connecting to form next level.
3. How these units are processed, especially how
connections among units are formed, influences
learning.
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1. Types of Knowledge
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Two Types of Knowledge
Declarative Knowledge
• Knowledge that you know you have and that
you can report (“declare”)
Procedural Knowledge
• Knowledge of how to do things (e.g., tie
your shoes, do arithmetic).
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2. Knowledge Units
(a) Sizes
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Declarative Knowledge Units
Concept
• Smallest unit of knowledge (not of meaning)
• A concept is a mental representation of a
category of things in the world (e.g. DOG)
• Concept allows you to decide whether a
stimulus is a member of the category
• Issue: nature of the representation – prototype?
Set of exemplars? Feature list?
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Declarative Knowledge Units
Proposition
• Smallest unit of meaning that has a truth value
• A proposition asserts some quality or
behaviour of some entity
• Basically, Subject, Verb, Object or Quality
• e.g., The dog barked; The dog is brown; The
dog wore sneakers
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Declarative Knowledge Units
Schema
• Stored knowledge structure that influences
perception and comprehension
• Capture important information about people,
situations and events
• What usually happens? What is usually
present? When does an event usually occur?
• Acquired slowly; difficult to modify
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Procedural Knowledge Units
Production
• If CONDITION holds, then perform ACTION
• Anderson argues that all behaviour can be
modeled as sequences of productions
• A sequence of productions can become
automatic. This is proceduralization.
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Procedural Knowledge Units
Script
• due primarily to work of Roger Schank in
artificial intelligence.
• a script is like a schema for a process
• detailed, because computer programs won’t run
unless you specify everything necessary
• more recent versions allow scripts to be created
as needed from stored components (episodes,
actors, settings)
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2. Knowledge Units
(b) Connections
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Network Models of Knowledge
Two basic types of models:
Local Representation
• nodes in the network represent concepts
Distributed Representation
• nodes don’t represent anything; concepts are
represented in patterns of activation
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Local Representation Models
Quillian & Collins (1969) TLC
• Teachable Language Comprehender
• Hierarchical organization
• Nodes are empty. They are placeholders in the
network.
• All links the same length.
• ISA links and property links
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Local Representation Models
Collins & Loftus (1975)
• less hierarchical version of TLC
• structure of network reflects person’s experience
rather than objective scientific information
• explained typicality effects
• introduced very important concept of spreading
activation for retrieval of information
• explained priming effects
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Distibuted Representation Models
Parallel Distributed Processing (PDP)
• ‘neural network’ or ‘connectionist’ models
• models have units (neurons) and weighted
connections (axons/synapses)
• concepts are represented as patterns of
activation across many units
• each unit participates in many patterns; no unit
represents any one concept
• knowledge is stored in weights on connections
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Parallel Distributed Processing Models
• Models start out not knowing anything – weights
on connections are random.
• Weights are adjusted during learning so input
pattern becomes more likely to cause activation of
appropriate output pattern
• One set of weights works for all concepts
• PDP models are very good at handling problems
in which multiple constraints have to be satisfied
at the same time
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READ
What are the last two letters in this stimulus?
SHOO
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3. Type of Processing
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Types of Processing
In early 70’s, cognitive psychologists began to
be
• less interested in structural questions (e.g.,
what is the capacity of STM?)
• more interested in process questions (e.g.,
what is the best way to encode information for
later retrieval?).
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Types of Processing
Rehearsal
• Maintenance rehearsal
• Simple repetition of stimulus
• Elaborative rehearsal
• Drawing connections between stimulus and
what you already know
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Types of Processing
Levels of Processing (Craik & Lockhart)
• processing types vary on a depth dimension
• semantic processing is deep; form processing
(e.g., colour, shape) is shallow
• deeper processing facilitates retrieval
• Bransford: what matters is match between
codes generated at encoding and type of retrieval
cues
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Problems with levels of processing theory:
Baddeley has argued that LoP theory
• is circular
• is an empirical failure under some
conditions (doesn’t work with recognition)
• Still,it is a useful heuristic: How you
encode matters
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How you encode matters
• Deeper processing requires elaboration
• Elaboration builds connections between new
information and old
• Elaboration makes new information more
distinctive
• But how you retrieve also matters…
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How you retrieve matters, too:
• Tulving and encoding specificity
• Recognition vs. Recall
• Bartlett and reconstruction
• Relearning
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Tulving’s encoding specificity idea:
• Remembering is best when conditions at
retrieval match conditions at learning
• paired-associates
• type of code generated
• mental and physical state
• context (e.g., Smith, 1986; Godden &
Baddeley, 1975)
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Recognition vs. Recall
Recall
• retrieve learned materials with no further
cues
Recognition
• identify learned materials when presented
or distinguish learned from unlearned
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Reconstruction
• originally suggested by Bartlett (1932)
• remembering involves computing ‘what must
have happened,’ on basis of:
 Some encoded material
 Some knowledge of the world at concept,
proposition, and script levels.
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Relearning
First observed by Ebbinghaus (1885)
• When you re-learn some material, you acquire it
faster than when you learned it the first time
• Reduction in effort or time required = savings
• Holds even over very long intervals (years)
• Very sensitive measure of memory
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Implications for instruction:
Encourage deeper processing
Encourage elaboration
Encourage use of mnemonics and other strategies
Reconstruction is going to happen – don’t try to
resist, try to guide it
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Implications for instruction
Make information retrieval more effective by
• Matching encoding and retrieval conditions
 This includes context and student’s state
• Providing relevant cues at retrieval
• Using prior knowledge to reconstruct missing
information
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