Learning

16
LEARNING • Learning is achieved through experience. • Anything that we were born knowing how to do is not a result of learning, but everything else is. • We learn how to walk, we learn how to speak in the language of our parents, and we learn how to read. • Sometimes we learn to do things by trying them ourselves; at other

TAGS:

description

Learning. Learning is achieved through experience. Anything that we were born knowing how to do is not a result of learning, but everything else is. We learn how to walk, we learn how to speak in the language of our parents, and we learn how to read. - PowerPoint PPT Presentation

Transcript of Learning

Page 1: Learning

LEARNING• Learning is achieved

through experience.• Anything that we were

born knowing how to do is not a result of learning, but everything else is.

• We learn how to walk, we learn how to speak in the language of our parents, and we learn how to read.

• Sometimes we learn to do things by trying them ourselves; at other times, we learn by watching others or by reading books.

Page 2: Learning

CONDITIONING = LEARNING• Stimulus – something that

produces a reaction (or response) from a person or animal.

• Classical Conditioning is a simple form of learning in which one stimulus calls forth the response that is usually called forth by another stimulus.

• The founder of classical conditioning was Russian psychologist Ivan Pavlov (1849-1936).

Page 3: Learning

IVAN PAVLOV RINGS A BELL• Pavlov discovered that dogs learn to associate one thing with

another when food is involved.• He was studying salivation to find a relationship between the

nervous system and digestion.• He discovered that dogs did not always wait until they had

received meat to start salivating. • Sometimes they would

salivate in response to the clinking of food trays whenassistants entered the laboratory.

• He looked into this by setting up an experiment where he would stimulate the dog by ringing a bell when meat was near.

Page 4: Learning

LETTERS OF LEARNING• There are four terms that are

associated with Classical Conditioning.

• Unconditioned Stimulus (US or UCS) is a stimulus that causes a response that is automatic, not learned.

• Unconditioned Response (UR or UCR) is the automatic response to the US.

• Conditioned Response (CR) is a learned response to a stimulus that was previously neutral, or meaningless.

• Conditioned Stimulus (CS) is the stimulus that becomes a learned stimulus through repeated association.

• http://www.youtube.com/watch?v=hhqumfpxuzI

http://www.youtube.com/watch?v=hhqumfpxuzI
http://www.youtube.com/watch?v=hhqumfpxuzI
http://www.youtube.com/watch?v=hhqumfpxuzI
Page 5: Learning
Page 6: Learning

QUESTIONWhat are some examples that you can think of in which you have been classically conditioned to something?

Page 7: Learning

ACTIVITYComplete the worksheet of situations that apply to classical conditioning. In each situation identify the neutral stimulus, unconditioned stimulus, unconditioned response, conditioned stimulus, and conditioned response.

Page 8: Learning

WARM-UPDefine the parts in the classical conditioning equation:Neutral StimulusUnconditioned StimulusUnconditioned ResponseConditioned StimulusConditioned Response

Page 9: Learning

ADAPTING TO THE ENVIRONMENT• Taste Aversion is a learned avoidance of a

particular food.• Have you ever eaten a food that made you ill,

perhaps because it was spoiled?• Did you then stay away from that food for a long

time?

• Example: Coyote

Page 10: Learning

EXTINCTION• Extinction occurs when conditioned stimulus is

disconnected from the unconditioned stimulus.• Pavlov discovered that with repeated ringings of

the bell (CS) not followed by meat (US), the dogs eventually stopped salivating (CR) when they heard the bell (CS).

Page 11: Learning

SPONTANEOUS RECOVERY• Spontaneous recovery is when the CR comes

back when the CS is presented again even after an extended period of time.

• Think about a song that you heard that brought back old feelings.

• If it were to become popular again and you started hearing it everyday you probably would no longer experience the same rush of feelings after hearing it over and over.

Page 12: Learning

GENERALIZATION AND DISCRIMINATION• Generalization is when we associate similar

objects to get a CR.• Pavlov’s Dogs and the Circles are an example of

generalization.• Discrimination is knowing the difference

between one CS and another.• A bear cub can distinguish between a wolf and a

mouse is an example of Discrimination.

Page 13: Learning

FLOODING• Flooding is when a person is exposed

to something they fear until fear responses to that stimulus are extinguished.

• This uncomfortable for most people.

• An example of this is that a person with a fear of heights may look out from a sixth story window until she or he is no longer upset by it.

Page 14: Learning

SYSTEMATIC DESENSITIZATION• Systematic desensitization is when people are

taught relaxation techniques and are then exposed gradually to whatever stimulus the fear while they remain relaxed.

• An example of this is a person who fears snakes being shown pictures while they are relaxed.

Page 15: Learning

COUNTERCONDITIONING• Counterconditioning is when a pleasant

stimulus is paired repeatedly with a fearful one, counteracting the fear.

• I hate bunnies but I love cookies.

Page 16: Learning

LITTLE ALBERTOn page 134 in the textbook you will read the selection on baby Albert and then answer the 2 questions. While reading think about whether or not you feel this was ethical and why.

http://www.youtube.com/watch?v=LVJMhk4oANM

http://www.youtube.com/watch?v=LVJMhk4oANM

Bayesian Learning, Regression-based learning. Overview Bayesian Learning Full MAP learning Maximum Likelihood Learning Learning Bayesian Networks.

Bayesian Learning, Regression-based learning. Overview Bayesian Learning Full MAP learning Maximum Likelihood Learning Learning Bayesian Networks.

Suggested Machine Learning Class: – learning-supervised-learning--ud675

Suggested Machine Learning Class: – learning-supervised-learning--ud675

LEARNING OUTCOMES Teaching, learning and assessment methods Learning Outcomes TLA 2.… · LEARNING OUTCOMES Teaching, learning and assessment ... number of teaching/learning and

LEARNING OUTCOMES Teaching, learning and assessment methods Learning Outcomes TLA 2.… · LEARNING OUTCOMES Teaching, learning and assessment ... number of teaching/learning and

Learning Styles and Learning Spaces: Using Learning Style ...

Learning Styles and Learning Spaces: Using Learning Style ...

Learning, E-Learning & Re-Learning: Leadership … @diversitywoman The Innovation of Human Capital: Inclusion & Learning Learning, E-Learning & Re-Learning: Leadership Success in the

Learning, E-Learning & Re-Learning: Leadership … @diversitywoman The Innovation of Human Capital: Inclusion & Learning Learning, E-Learning & Re-Learning: Leadership Success in the

Learning Objective 1 Learning Objective 2 Learning ...

Learning Objective 1 Learning Objective 2 Learning ...

Guided Learning Projects Messy Learning – Real Learning – Successful Learning.

Guided Learning Projects Messy Learning – Real Learning – Successful Learning.

Learning from observations Inductive Learning - learning from examples Machine Learning.

Learning from observations Inductive Learning - learning from examples Machine Learning.

E-LEARNING , B-LEARNING Y M-LEARNING

E-LEARNING , B-LEARNING Y M-LEARNING

EDFD 302 MGMSANTOS Learning Models. Learning Models: Mastery Learning Discovery Learning Guided Discovery Learning Meaningful Reception Learning.

EDFD 302 MGMSANTOS Learning Models. Learning Models: Mastery Learning Discovery Learning Guided Discovery Learning Meaningful Reception Learning.

machine Learning Learning

machine Learning Learning

Reformatted Adaptive Learning and Learning Analytics- a ... · Adaptive)Learning)and)Learning)Analytics:)a)new)learning)design) paradigm) Simon#Paul#Atkinson# Associate#Deanof#Learning#andTeaching#

Reformatted Adaptive Learning and Learning Analytics- a ... · Adaptive)Learning)and)Learning)Analytics:)a)new)learning)design) paradigm) Simon#Paul#Atkinson# Associate#Deanof#Learning#andTeaching#

Learning Deep Learning

Learning Deep Learning

Assessment for Learning - Curriculum · Assessment for Learning Assessment for Learning Assessment of Learning ... Sharing Learning Intentions 1. Identify what pupils will be learning

Assessment for Learning - Curriculum · Assessment for Learning Assessment for Learning Assessment of Learning ... Sharing Learning Intentions 1. Identify what pupils will be learning

Unsupervised Learning Learning Unsupervised...Unsupervised Learning and Data Mining Learning Mining Unsupervised Learning and Data Mining Unsupervised Data Clustering Supervised Learning

Unsupervised Learning Learning Unsupervised...Unsupervised Learning and Data Mining Learning Mining Unsupervised Learning and Data Mining Unsupervised Data Clustering Supervised Learning

(INTER)DEPENDENT LEARNING Learning is …Inter)dependent...(INTER)DEPENDENT LEARNING Learning is Interaction ... DEPENDENT LEARNING Learning is Interaction Inaugural Address ... or

(INTER)DEPENDENT LEARNING Learning is …Inter)dependent...(INTER)DEPENDENT LEARNING Learning is Interaction ... DEPENDENT LEARNING Learning is Interaction Inaugural Address ... or

Learning and Knowledge Microlearning 2006. Business is learning Life is learning Education is learning Aging is learning What isnt learning???

Learning and Knowledge Microlearning 2006. Business is learning Life is learning Education is learning Aging is learning What isnt learning???

Learning about Learning

Learning about Learning

Statistical Learning - homepage.divms.uiowa.edu€¦ · Statistical Learning Some Machine Learning Terminology Two forms of learning: – supervised learning: features and responses

Statistical Learning - homepage.divms.uiowa.edu€¦ · Statistical Learning Some Machine Learning Terminology Two forms of learning: – supervised learning: features and responses

UNIT V: LEARNING. LEARNING Learning from Observation Inductive Learning Decision Trees Explanation based Learning Statistical Learning methods Reinforcement.

UNIT V: LEARNING. LEARNING Learning from Observation Inductive Learning Decision Trees Explanation based Learning Statistical Learning methods Reinforcement.