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Schemata and Information Processing
Types of Declarative Knowledge Chunks
Image Proposition
Type of information preserved
Spatial relationships among objects
Meaningful relationships among words, ideas, and concepts
Example
is aC h lo ro p h y llP ig m en t
is aChlorophyll
Pigment
Schema
• The idea that knowledge has a structural representation in the mind
• Stresses the idea of connectivity in the relationships
Characteristics of Schemata
• A schema may be small or large in size• One schema can become a part of another.• With experience schemata can become more
detailed.• Schemata are flexible.
Network Model
of Declarative Knowledge(e.g. concept
mapping!)
Copyright © Allyn & Bacon 2005
can be
can be
can be
may freeze to form may evaporate to form
e.g.e.g.
e.g.
may sublimate to form
is composed of
have
unite during process of
is the result of deceasing
is inversely proportional to
separate during the process of
creates
creates
is directly proportional to
causes
measures
can be
Under normal pressures existsUnder normal pressures exists
can be
can be
Under normal pressures exists
describes transistions between different forms of
is explained in terms of
condenses to form
may produce
upon falling may create evaporate to create
e.g.e.g.
e.g.
Water
Solid
Liquid
Gas
ice
vapor
rain
Particles
Movement
Condensation
Space
Density
Evaporation
Heat Sunlight
Temperature
At or below 0 degrees Celsius At or above
100 degrees Celsius
Between 0 and 100 degrees Celsius
The Water Cycle
clouds
puddles
snow
Information Processing
• Learning Theory that is analogous to how a computer operates– Information is stored (hard drive)
– There is a place in the brain that deals with “working” information
• Theory holds that knowledge is discrete and objective– Objective means that learners do not have unique structures.
– Contrast this with Constructivism
• Theory advocates a gradual, incremental accumulation of knowledge.– This is distinct from Piaget!
• Theory advocates types of knowledge:– Declarative
– Procedural
An Information-Processing Model
Selective
Perception
Processes
Working
Memory
Declarative
Memory
Procedural
Memory
Long-term
Memory
Retrieval
Compilation
Rehearsal
Automatic
Action
Sensory
Register
Consciously
Controlled
Action
Encoding
Selective Perception
Selective Perception
A D 1 F P 3 3 D W 4 Q
P U T R 3 1
Selective Perception
Selective Perception
A D 1 F P 3 3 D W 4 Q
P U T R 3 1
Selective Perception
You can see 6 different cards.Think on one.Just think on it.Are you thinking intently?I will find the card on your mind.
Selective Perception
Now, look straight into my eyes and think about your card…
I can’t see the card you have chosen…
…but I know exactly the card that is on your mind…
Selective Perception
Look!Your card is gone!
Do it again?
You can see 6 different cards.Think on one.Just think on it.Are you thinking intently?I will find the card on your mind.
Selective Perception
Now, look straight into my eyes and think about your card…
I can’t see the card you have chosen…
…but I know exactly the card that is on your mind…
Selective Perception
Look!Your card is gone!
What factors might influence (positively or negatively) “Selective Perception”?
The Efficiency of Working Memory
• Working Memory is finite– Only so much can be held and processed at once
Selective
Perception
Processes
Working
Memory
Declarative
Memory
Procedural
Memory
Long-term
Memory
Retrieval
Compilation
Rehearsal
Automatic
Action
Sensory
Register
Consciously
Controlled
Action
Encoding
Remembering Numbers
The 7 +/- 2 rule
Enhancing the Efficiency of Working Memory
• Maintenance Rehearsal• Chunking• Automaticity
Maximizing Students’ Encoding and Retrieval
• Active Learning• Aligning Learning and Performance• Review and Practice
– Distributed practice
Selective
Perception
Processes
Working
Memory
Declarative
Memory
Procedural
Memory
Long-term
Memory
Retrieval
Compilation
Rehearsal
Automatic
Action
Sensory
Register
Consciously
Controlled
Action
Encoding
An Example of Information Processing
Students draw from Long Term Memory into Working Memory:
objects closer to areis
3rd planet fromSun
Hot
Earth
Hotter
Students perceive from sensory instruction:
objects closer to areis
3rd planet fromSun
Hot
Earth
HotterPluto is a planet.Pluto is the 9thplanet from the sun.
New info coded into working memory:
objects closer to areis
3rd planet fromSun
Hot
Earth
Hotter
9th Planet in SS
Pluto
Planet
New propositional relationships by combining new and old
objects closer to areis
3rd planet from
9th Planet in SS
colder than
Sun
Hot
Earth
Hotter
Pluto
Planet
Considerations Using Information Processing Theory:
Minimize distractions (especially with younger children)
Base instruction on what students already know Use teaching strategies to organize information (e.g.
agendas, summary diagrams (e.g. Venn), etc.) Give students many opportunities to assess their own
learning efforts and identify what they do and do not know
Connecting to Practice
Selective
Perception
Processes
Working
Memory
Declarative
Memory
Procedural
Memory
Long-term
Memory
Retrieval
Compilation
Rehearsal
Automatic
Action
Sensory
Register
Consciously
Controlled
Action
Encoding
Use concepts from IP Model to explain the following:
• Teachers often use examples from students’ lives to help them better understand new and complicated ideas. • A teacher provides students with a list of questions to answer as they are reading a chapter in the textbook. • A teacher provides students with an outline of her lecture to look at as she delivers her lecture. • A teacher tries to have students learn new skills in the way they will have to use them.