Cognitive science for machine learning 1: What is cognitive science? Nick Chater 1.
Science of Learning Overview of Cognitive Science for Teachers.
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Transcript of Science of Learning Overview of Cognitive Science for Teachers.
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Science of Learning
Overview of Cognitive Science for Teachers
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Psychological/Cognitive Revolution
• Freud (1890) • Kohler’s monkeys(1908)• 1900-1960: Two directions
– US: Behaviorism– Europe: Gestalt
• 1960’s- Cognitive Science – Formerly artificial intelligence– Only Nobel prize for psychology
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Behaviorism• Pavlov, Watson, Thorndike & Skinner• Create a science of behavior
– No mention of thinking– Only visible factors considered
• Reinforcement of desired behaviors– Treat all students the same– Feedback is most important
• Teaching machines
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Gestalt Psychology• Kohler, Wertheimer, Piaget• Focus on Perception
– Illusions suggest some of the inner processes
• Brain as an active processor– Not simply taking in information– Fish is fish– http://faculty.uca.edu/~lglenn/gestaltimages.htm
• Research on understanding
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Constructivsm• Jean Piaget (1940-70s)• Knowledge must be constructed
– Assimilation– Accomodation– Ignore/segment knowledge
• Looked at students mistakes and developed theory of development– Sensorimotor stage– Preoperational stage– Concrete operational stage– Formal operations
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Problematic Initial ideas• Earth is flat• When you throw a ball it naturally slows down
and stops• It is much less likely to get ‘heads’ four times
in a row than to get h-t-h-t• Astronaut Question
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Astronaut questionThe astronaut is walking on the
moon when he lets go of his pen. Does the pen:
A. Fall to the moon surface
B. Float up into the sky
C. Float in placeQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.
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Misconceptions?• All ideas are the product of some experience• Students initial ideas are the building blocks
of future ideas• If misconceptions are not addressed many
students will retain them after instruction• How to you promote “conceptual change”
(aka accommodation that involves major change of ideas)?
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Cognitive Science• Understanding thinking using many
perspectives:– Psychology – Computer Science– Linguistics– Anthropology
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Artificial Intelligence
• Starts with Allan Newell and Herb Simon (1956) General Problem Solver
• Computers can solve well structured problems (e.g. geometry, chess)– Identify the goal– Search the “solution space”– Hill climbing
• Most problems are not well structured• Later efforts focus on gestalt type approaches
(neural nets)
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Contemporary Learning Theory
• Constructivism - Role of prior knowledge• Metacognition - Control over thinking process• Expert/Novice - How do experts think• Transfer - Evidence of understanding• Social Constructivism - role of peers, community• Sense Making - actively trying to understand• Mental Models - representations of phenomena• Constructionism - learning through building
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Metacognition• Literally - thinking about thinking• Awareness of ones thinking and knowledge of
skills and limitations– Planning– Checking – Reflection
• Epistemology: knowledge of ideas and their origins– General knowledge of ideas– Specific to field of study eg Nature of Science
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Experts vs Novices• Experts do not
– Think at a faster rate– Use more of their brain– Instantly know the answer to everything– Learn without effort
• Experts do– Organize knowledge by important factors– Chunk information for easy use and retrieval– Identify patterns and make inferences
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X X O
X O X
X O O
O O X
X O O
0 X X
O O X
X X O
X O X
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Transfer• Best test of understanding• Three key types
– Near transfer (parallelograms)– Far transfer (fortress - tumor)– Transfer to real world
• Keys for promoting transfer– Abstraction– Representations of knowledge– Use of analogies
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Lev Vygotsky (1896-1934) -
Social Constructivism• “Every function in the child's
cultural development appears twice: first, on the social level, and later, on the individual level”
• Zone of Proximal Development (ZPD)– The difference between what
you can do by yourself and what you can do with the aid of a coach
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Problem Solving & Sense Making
• Problem Solving– Humans work differently than computers– Students assume they should just know– Experts spend more time planning and checking
• Sense Making– Somewhat undefined: “I know it when I see it”– Effort to try and understand/explain something
something
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Mental Models• A mental representation of a
phenomena or event• Depictive simulations allow people to
see things in their minds eye • Representation that is “run-able” so you
can simulate what will happen and make predictions
• Similar to Schemas but bigger?
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Constructionism• Learning by creating new things
• From Paper (1979) Mindstorms – Research on LOGO programing– Computerized “Microworlds” where you
can build anything you want
• Extended to engineering type projects– Instead of experimentation, build
something