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A Scientific Approach to the Teaching of Chemistry Centre for Science Education, University of Glasgow, Scotland 1 Norman Reid Thursday, 15 October 2009

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Page 1: A Scientific Approach to the Teaching of Chemistrychemistrynetwork.pixel-online.org/data/SMO_db/doc/18... · 2012-05-14 · A Scientific Approach to the Teaching of Chemistry Centre

A Scientific Approachto the

Teaching of Chemistry

Centre for Science Education, University of Glasgow, Scotland

1

Norman Reid

Thursday, 15 October 2009

Page 2: A Scientific Approach to the Teaching of Chemistrychemistrynetwork.pixel-online.org/data/SMO_db/doc/18... · 2012-05-14 · A Scientific Approach to the Teaching of Chemistry Centre

A Scientific Approachto the

Teaching of Chemistry

Centre for Science Education, University of Glasgow, Scotland

1

What do we know about how students learn chemistry and how

can we make our teaching match this to maximise performance?

Norman Reid

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

2

Where are we Going ?

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

2

Why Chemistry is DifficultInformation Processing - the Key ?How Students LearnBringing in TogetherThe Attitude ProblemA Total Picture

Where are we Going ?

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

2

Why Chemistry is DifficultInformation Processing - the Key ?How Students LearnBringing in TogetherThe Attitude ProblemA Total Picture

Where are we Going ?

What does research tell us about learning?How can we apply it in practice?

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

3

Some History

School Curriculum Revolution in Chemistry started in the 1960s

By the mid-1960s, reports emerged in Scotland: some of the chemistry is too difficult; parallels in other countries Research Studies: Where are the difficulties ? Is there anything we can do? What are the misconceptions ? Are there underlying reasons for the problems?

Numerous Curriculum Revisions, especially the USA

What was the actual evidence?

Could we be scientific about teaching and learning ?

Thursday, 15 October 2009

Page 7: A Scientific Approach to the Teaching of Chemistrychemistrynetwork.pixel-online.org/data/SMO_db/doc/18... · 2012-05-14 · A Scientific Approach to the Teaching of Chemistry Centre

Centre for Science Education, University of Glasgow, Scotland

3

Some History

School Curriculum Revolution in Chemistry started in the 1960s

By the mid-1960s, reports emerged in Scotland: some of the chemistry is too difficult; parallels in other countries Research Studies: Where are the difficulties ? Is there anything we can do? What are the misconceptions ? Are there underlying reasons for the problems?

Numerous Curriculum Revisions, especially the USA

What was the actual evidence?

Could we be scientific about teaching and learning ?

Thursday, 15 October 2009

Page 8: A Scientific Approach to the Teaching of Chemistrychemistrynetwork.pixel-online.org/data/SMO_db/doc/18... · 2012-05-14 · A Scientific Approach to the Teaching of Chemistry Centre

Centre for Science Education, University of Glasgow, Scotland

4

Many Assertions

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

4

Many AssertionsChemistry is abstract

Chemistry is full of conceptsStudents hold many misconceptions

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

4

Many AssertionsChemistry is abstract

Chemistry is full of conceptsStudents hold many misconceptions

It is all the fault of secondary schoolsIt is all the fault of primary schools

Thursday, 15 October 2009

Page 11: A Scientific Approach to the Teaching of Chemistrychemistrynetwork.pixel-online.org/data/SMO_db/doc/18... · 2012-05-14 · A Scientific Approach to the Teaching of Chemistry Centre

Centre for Science Education, University of Glasgow, Scotland

4

Many AssertionsChemistry is abstract

Chemistry is full of conceptsStudents hold many misconceptions

It is all the fault of secondary schoolsIt is all the fault of primary schools

There is poor motivation and bad attitudesThey cannot do mathematics!

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

4

Many AssertionsChemistry is abstract

Chemistry is full of conceptsStudents hold many misconceptions

It is all the fault of secondary schoolsIt is all the fault of primary schools

There is poor motivation and bad attitudesThey cannot do mathematics!

More roadshows, more glossy booklets, more advertising, more school visits, more science centres ..... !!

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

5

Difficulties Survey (1970)

Most difficult topics(from upper school as seen by first year students)

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

5

Difficulties Survey (1970)

Most difficult topics(from upper school as seen by first year students)

Topics related to equations and the mole, eg. volumetric and gravimetric work, Avogadro and the mole.

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

5

Difficulties Survey (1970)

Most difficult topics(from upper school as seen by first year students)

Topics with some arithmetical content eg. thermochemistry and thermodynamics.

Topics related to equations and the mole, eg. volumetric and gravimetric work, Avogadro and the mole.

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

5

Difficulties Survey (1970)

Most difficult topics(from upper school as seen by first year students)

Redox (eg E˚) and ion electron ideas

Topics with some arithmetical content eg. thermochemistry and thermodynamics.

Topics related to equations and the mole, eg. volumetric and gravimetric work, Avogadro and the mole.

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

5

Difficulties Survey (1970)

Most difficult topics(from upper school as seen by first year students)

Organic topics like esters, proteins, amines and carbonyls, aromaticity

Redox (eg E˚) and ion electron ideas

Topics with some arithmetical content eg. thermochemistry and thermodynamics.

Topics related to equations and the mole, eg. volumetric and gravimetric work, Avogadro and the mole.

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

6

Some Growing Ideas

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

6

Success might be linked to Information Load

Some Growing Ideas

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Success might be linked to Information Load

Some Growing Ideas

Information Load: Started to be defined in terms of the number of ideas which a student has to hold at the

same time in order to succeed.

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

6

Success might be linked to Information Load

Some Growing Ideas

Information Load: Started to be defined in terms of the number of ideas which a student has to hold at the

same time in order to succeed.

Questions could be analysed by information load

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

7

Exploring Information Load

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

7

Exploring Information Load

I shall give you some dates

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Centre for Science Education, University of Glasgow, Scotland

7

Exploring Information Load

I shall give you some dates

Turn the dates into numbers

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

7

Exploring Information Load

I shall give you some dates

Turn the dates into numbers

Put the numbers in ascending order

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

8

Trial Run

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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8 March 96

Trial Run

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Centre for Science Education, University of Glasgow, Scotland

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8 March 96

Trial Run

8 3 9 6

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Centre for Science Education, University of Glasgow, Scotland

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8 March 96

Trial Run

3 6 8 98 3 9 6

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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26 December

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Thursday, 15 October 2009

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1 2 2 6

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Centre for Science Education, University of Glasgow, Scotland

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June 1984

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Thursday, 15 October 2009

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1 4 6 8 9

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8 May 1996

Centre for Science Education, University of Glasgow, Scotland

11

Thursday, 15 October 2009

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Thursday, 15 October 2009

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1 5 6 8 9 9

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Centre for Science Education, University of Glasgow, Scotland

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11 January 1901

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Centre for Science Education, University of Glasgow, Scotland

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Thursday, 15 October 2009

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0 1 1 1 1 1 9

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23 December 1873

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Thursday, 15 October 2009

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1 1 2 2 3 3 7 8

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Centre for Science Education, University of Glasgow, Scotland

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5.30 am 16 November 2007

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Thursday, 15 October 2009

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0 0 0 1 1 1 2 3 5 6 7

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Centre for Science Education, University of Glasgow, Scotland

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0 0 0 1 1 1 2 3 5 6 7

5.30 am 16 November 2007

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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0 0 0 1 1 1 2 3 5 6 7

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Centre for Science Education, University of Glasgow, Scotland

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Working Memory

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Centre for Science Education, University of Glasgow, Scotland

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Working Memory

Limited capacity: 7 ± 2

Fixed genetically

Grows with age

Can be used efficiently or otherwise

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Measuring Working Memory Capacity

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Measuring Working Memory Capacity

Digit Span Backwards Test

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Measuring Working Memory Capacity

Digit Span Backwards TestRecall numbers backwards

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Measuring Working Memory Capacity

Digit Span Backwards Test

Figural Intersection Test

Recall numbers backwards

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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Measuring Working Memory Capacity

Digit Span Backwards Test

Figural Intersection Test

Recall numbers backwards

Finding overlap between several geometrical shapes

Thursday, 15 October 2009

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Information Load and SuccessReasonable hypothesis:

As load increases, success will fall.

Information Load Level of Questions

SuccessExpected Result

Centre for Science Education, University of Glasgow, Scotland

17

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80

70

60

50

40

30

202 3 4 5 6 7 8 9 10

Information Load

Average Student Performance

%

Centre for Science Education, University of Glasgow, Scotland

18

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80

70

60

50

40

30

202 3 4 5 6 7 8 9 10

Information Load

Average Student Performance

%

Centre for Science Education, University of Glasgow, Scotland

18

Sudden collapse in performance

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80

70

60

50

40

30

202 3 4 5 6 7 8 9 10

Question Working Memory Demand

Average Student Performance

Working Memory = 7

Working Memory > 7

Working Memory < 7

Centre for Science Education, University of Glasgow, Scotland

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80

70

60

50

40

30

202 3 4 5 6 7 8 9 10

Question Working Memory Demand

Average Student Performance

Working Memory = 7

Working Memory > 7

Working Memory < 7

Centre for Science Education, University of Glasgow, Scotland

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Studies in Higher Education, 1989, 14(2), 159-168

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EventsObservations Instructions

Centre for Science Education, University of Glasgow, Scotland

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An Information Processing Model(based on empirical evidence)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

Centre for Science Education, University of Glasgow, Scotland

20

An Information Processing Model(based on empirical evidence)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Centre for Science Education, University of Glasgow, Scotland

20

An Information Processing Model(based on empirical evidence)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Centre for Science Education, University of Glasgow, Scotland

20

An Information Processing Model(based on empirical evidence)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Centre for Science Education, University of Glasgow, Scotland

20

An Information Processing Model(based on empirical evidence)

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Predictions from the Model

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Predictions from the ModelIf working memory is overloaded, learning will more or ceaseIf the perception filter works efficiently, overload is less likelyThe filtration is controlled by what you know alreadyIf knowledge is stored in linked fashion, it will be more easily recalled

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

23

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Predictions from the ModelIf memory is overloaded, learning will more or ceaseIf the perception filter works efficiently, overload is less likelyThe filtration is controlled by what you know alreadyIf knowledge is stored in linked fashion, it will be more easily recalled

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Predictions from the ModelIf memory is overloaded, learning will more or ceaseIf the perception filter works efficiently, overload is less likelyThe filtration is controlled by what you know alreadyIf knowledge is stored in linked fashion, it will be more easily recalled

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

25

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Predictions from the ModelIf memory is overloaded, learning will more or ceaseIf the perception filter works efficiently, overload is less likelyThe filtration is controlled by what you know alreadyIf knowledge is stored in linked fashion, it will be more easily recalled

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Learning

Everyone learns in essentially the same wayThere are many variations in the details

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Selection linked to ability to see what is important (field dependency)

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

The working memory is of limited capacity (7±2)

Its capacity cannot be increased

It can be used more efficiently

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Selection based on previous knowledge, experience and

attitudes

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Students vary in the way they store information

Extent of meaningful links between ideasFavoured storage: visually or symbolicallyConceptual understanding related to links between ideas

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The Idea of Pre-learning

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The Idea of Pre-learning

Watch the skilled school teacher

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The Idea of Pre-learning

Watch the skilled school teacher

The idea of the Pre-lecture

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The Idea of Pre-learning

Watch the skilled school teacher

The idea of the Pre-lecture

The idea of the Pre-laboratory

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First Year General Chemistry ClassFirst Year General Chemistry ClassFirst Year General Chemistry Class

Year Pre-learning Upper Group Average

Lower Group Average

Difference Significance

1993-94 pre-lectures 50.9 48.8 2.1 not sig1994-95 pre-lectures 49.2 49.0 0.2 not sig1995-96 no pre-lectures 46.9 38.7 8.2 sig1996-97 no pre-lectures 48.2 42.0 6.2 sig1997-98 no pre-lectures 46.7 41.3 5.4 sig1998-99 Chemorganisers 49.8 47.7 2.1 not sig

Preparing the Mind for Learning

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Craig Gray and Ghassan Sirhan

University Chemistry Education, 1999, 5, 52-58.

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First Year General Chemistry ClassFirst Year General Chemistry ClassFirst Year General Chemistry Class

Year Pre-learning Upper Group Average

Lower Group Average

Difference Significance

1993-94 pre-lectures 50.9 48.8 2.1 not sig1994-95 pre-lectures 49.2 49.0 0.2 not sig1995-96 no pre-lectures 46.9 38.7 8.2 sig1996-97 no pre-lectures 48.2 42.0 6.2 sig1997-98 no pre-lectures 46.7 41.3 5.4 sig1998-99 Chemorganisers 49.8 47.7 2.1 not sig

Preparing the Mind for Learning

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Craig Gray and Ghassan Sirhan

University Chemistry Education, 1999, 5, 52-58.

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First Year General Chemistry ClassFirst Year General Chemistry ClassFirst Year General Chemistry Class

Year Pre-learning Upper Group Average

Lower Group Average

Difference Significance

1993-94 pre-lectures 50.9 48.8 2.1 not sig1994-95 pre-lectures 49.2 49.0 0.2 not sig1995-96 no pre-lectures 46.9 38.7 8.2 sig1996-97 no pre-lectures 48.2 42.0 6.2 sig1997-98 no pre-lectures 46.7 41.3 5.4 sig1998-99 Chemorganisers 49.8 47.7 2.1 not sig

Preparing the Mind for Learning

Centre for Science Education, University of Glasgow, Scotland

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Craig Gray and Ghassan Sirhan

University Chemistry Education, 1999, 5, 52-58.

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Physics Laboratories

What Was Done

Four Experiments

Each student did two of them with pre-laboratory exercises and two without.

Combinations were varied.

Each student was assessed on learning by two means:Traditional demonstrator marked performancePost-laboratory exercises, testing understanding and application of ideas.

Student attitudes were assessed.

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Physics Laboratories

What was Found

Pre-laboratories increased performance on student marking by around 5%Pre-laboratories increased performance on exercises by around 11%Students were dramatically more positive about pre-laboratories

Physics Education (1998) 33(1) , 22-29

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First Year Chemistry Laboratories

What was done

Four Groups of Students (N = 500)

Group 1 ControlGroup 2 Pre-laboratory exercises usedGroup 3 Mini-project usedGroup 4 Pre-laboratory plus miniproject

Understanding checked by looking at questions askedAttitudes measured

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First Year Chemistry LaboratoriesWhat was found

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First Year Chemistry LaboratoriesWhat was found

Questions asked

Group 1 Control 121

Group 2 Pre-laboratory exercises used 58

Group 3 Mini-project used 145

Group 4 Pre-laboratory and miniproject 64

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First Year Chemistry LaboratoriesWhat was found

Questions asked

Group 1 Control 121

Group 2 Pre-laboratory exercises used 58

Group 3 Mini-project used 145

Group 4 Pre-laboratory and miniproject 64

Studies in Higher Education, 1994, 19(1), 77-88.

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First Year Chemistry LaboratoriesWhat was found

Questions asked

Group 1 Control 121

Group 2 Pre-laboratory exercises used 58

Group 3 Mini-project used 145

Group 4 Pre-laboratory and miniproject 64

Studies in Higher Education, 1994, 19(1), 77-88.

Enhancing Chemistry Laboratories, RSC

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Reducing the Load on Working Memory

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Reducing the Load on Working MemoryThis must NOT involve:

Changing what is to be taughtChanging the time demand

Simply avoiding problem areasMassive re-training of lecturers/teachers

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Reducing the Load on Working Memory

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Reducing the Load on Working Memory

It may involve:

Changing the teaching orderModifying speed and sequencingBreaking down complex areas

Allowing learning to fit human psychology

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Can We Reduce the Load on Working Memory?

The work of Eleni Danili in Greece

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Can We Reduce the Load on Working Memory?

The work of Eleni Danili in Greece

She measured the working memory capacity of the students and also their ability to ‘see the message from the noise’.

Thursday, 15 October 2009

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Can We Reduce the Load on Working Memory?

The work of Eleni Danili in Greece

She measured the working memory capacity of the students and also their ability to ‘see the message from the noise’.

She re-designed a large section of chemistry teaching at school level, specifically to reduce working memory overload problems.

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5w.m. = 6w.m. ≥ 7

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5 54w.m. = 6 60w.m. ≥ 7 69

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5w.m. = 6 46 60 72w.m. ≥ 7

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5 47 54 59w.m. = 6 46 60 72w.m. ≥ 7 59 69 78

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5 47 54 59w.m. = 6 46 60 72w.m. ≥ 7 59 69 78

Thursday, 15 October 2009

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5 47 54 59w.m. = 6 46 60 72w.m. ≥ 7 59 69 7878

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Performance Depends on ....

Working Memory Capacity

Field dependency (seeing the ‘message’ amidst the ‘noise’)

Performance (%)Performance (%)Performance (%)Performance (%)N = 105 - field dependency + - field dependency + - field dependency +w.m. ≤ 5 47 54 59w.m. = 6 46 60 72w.m. ≥ 7 59 69 7878

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

Normal Teaching

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

Normal Teaching Reduce workingmemory demand

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

N = 211 Performance Improvement

Control Group

Experimental Group

Normal Teaching Reduce workingmemory demand

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

N = 211 Performance Improvement

Control Group

Experimental Group

13%

Normal Teaching Reduce workingmemory demand

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Performance ImprovementUsing Control and Experimental Groups

(pre and post tests)

N = 211 Performance Improvement

Control Group

Experimental Group

13%

22%

Normal Teaching Reduce workingmemory demand

Thursday, 15 October 2009

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A Larger Experiment(800 Senior School Students)

Furat Hussein in the Emirates

Thursday, 15 October 2009

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A Larger Experiment(800 Senior School Students)

Testing Two Hypotheses

1. Reducing load on working memory will bring improved understanding.

2. Use appropriate applications and interaction will enhance attitudes

Furat Hussein in the Emirates

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A Larger Experiment(800 Senior School Students)

Minimise working memory overload;Use relevant applications;Encourage understanding not memorising;Link new material to previously taught material in a meaningful way

Testing Two Hypotheses

1. Reducing load on working memory will bring improved understanding.

2. Use appropriate applications and interaction will enhance attitudes

Furat Hussein in the Emirates

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Experimental Structure

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Group 1 Periodic Table Chemical Equations(200 students) (Booklet) (normal teaching)

Group 2 Periodic Table Chemical Equations (200 students) (normal teaching) (Booklet)

Assessment Assessment

Time

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Experimental Structure

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Group 1 Periodic Table Chemical Equations(200 students) (Booklet) (normal teaching)

Group 2 Periodic Table Chemical Equations (200 students) (normal teaching) (Booklet)

Assessment Assessment

Time

Group 1 Organic Chemistry Acids and Alkalis(200 students) (Booklet) (normal teaching)

Group 2 Organic Chemistry Acids and Alkalis (200 students) (normal teaching) (Booklet)

Assessment Assessment

Time

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Experimental Structure

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N = 800 Mean (%) Gain t-test Probability

Periodic Table (Year 10)Experimental Group 79.2 18.2 26.2 p < 0.001

Control Group 61.0

Chemical Equations (Year 10)Experimental Group 80.2 9.2 9.7 p < 0.001

Control Group 71.0

Organic (Year 11)Experimental Group 71.0 14.0 19.7 p < 0.001

Control Group 57.0

Acids and Alkalis (Year 11)Experimental Group 75.0 10.7 15.1 p < 0.001

Control Group 64.3

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Performance Data

Thursday, 15 October 2009

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N = 800 Mean (%) Gain t-test Probability

Periodic Table (Year 10)Experimental Group 79.2 18.2 26.2 p < 0.001

Control Group 61.0

Chemical Equations (Year 10)Experimental Group 80.2 9.2 9.7 p < 0.001

Control Group 71.0

Organic (Year 11)Experimental Group 71.0 14.0 19.7 p < 0.001

Control Group 57.0

Acids and Alkalis (Year 11)Experimental Group 75.0 10.7 15.1 p < 0.001

Control Group 64.3

Centre for Science Education, University of Glasgow, Scotland

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Performance Data

Thursday, 15 October 2009

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N = 800 Mean (%) Gain t-test Probability

Periodic Table (Year 10)Experimental Group 79.2 18.2 26.2 p < 0.001

Control Group 61.0

Chemical Equations (Year 10)Experimental Group 80.2 9.2 9.7 p < 0.001

Control Group 71.0

Organic (Year 11)Experimental Group 71.0 14.0 19.7 p < 0.001

Control Group 57.0

Acids and Alkalis (Year 11)Experimental Group 75.0 10.7 15.1 p < 0.001

Control Group 64.3

Centre for Science Education, University of Glasgow, Scotland

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Performance Data

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N = 800 Mean (%) Gain t-test Probability

Periodic Table (Year 10)Experimental Group 79.2 18.2 26.2 p < 0.001

Control Group 61.0

Chemical Equations (Year 10)Experimental Group 80.2 9.2 9.7 p < 0.001

Control Group 71.0

Organic (Year 11)Experimental Group 71.0 14.0 19.7 p < 0.001

Control Group 57.0

Acids and Alkalis (Year 11)Experimental Group 75.0 10.7 15.1 p < 0.001

Control Group 64.3

Centre for Science Education, University of Glasgow, Scotland

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Performance Data

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N = 800 Mean (%) Gain t-test Probability

Periodic Table (Year 10)Experimental Group 79.2 18.2 26.2 p < 0.001

Control Group 61.0

Chemical Equations (Year 10)Experimental Group 80.2 9.2 9.7 p < 0.001

Control Group 71.0

Organic (Year 11)Experimental Group 71.0 14.0 19.7 p < 0.001

Control Group 57.0

Acids and Alkalis (Year 11)Experimental Group 75.0 10.7 15.1 p < 0.001

Control Group 64.3

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Performance Data

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χ2

I like chemistry lessons 40 17 11 10 12 10 I hate chemistry lessons70 10 3 2 3 12 36.7 (p < 0.001)

Boring 17 9 11 14 20 29 Interesting20 1 1 2 5 71 66.0 (p < 0.001)

Easy 19 21 16 7 11 26 Difficult60 9 1 4 1 25 47.1 (p < 0.001)

Useless 8 4 5 8 13 62 Useful10 8 2 2 5 73 14.1 (p < 0.001)

Important 60 10 10 4 8 8 Unimportant69 11 2 3 6 9 13.2 (p < 0.001)

Enjoyable 18 17 18 16 8 2 Boring66 12 1 1 3 17 104.1 (p < 0.001)

Control Group N = 115Experimental Group N = 400

Centre for Science Education, University of Glasgow, Scotland

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Some Attitude Changes

Thursday, 15 October 2009

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χ2

I like chemistry lessons 40 17 11 10 12 10 I hate chemistry lessons70 10 3 2 3 12 36.7 (p < 0.001)

Boring 17 9 11 14 20 29 Interesting20 1 1 2 5 71 66.0 (p < 0.001)

Easy 19 21 16 7 11 26 Difficult60 9 1 4 1 25 47.1 (p < 0.001)

Useless 8 4 5 8 13 62 Useful10 8 2 2 5 73 14.1 (p < 0.001)

Important 60 10 10 4 8 8 Unimportant69 11 2 3 6 9 13.2 (p < 0.001)

Enjoyable 18 17 18 16 8 2 Boring66 12 1 1 3 17 104.1 (p < 0.001)

Control Group N = 115Experimental Group N = 400

Centre for Science Education, University of Glasgow, Scotland

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Some Attitude Changes

Thursday, 15 October 2009

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χ2

I am enjoying the subject 15 24 13 25 9 14 I am NOT enjoying the subjectI am NOT enjoying the subject66 6 2 2 5 19 104.2(p < 0.001)

I feel I am NOT coping well 18 10 11 10 24 27 I feel I am coping well30 10 11 3 7 39 39.6 (p < 0.001)

I find it very easy 22 27 23 16 8 4 find it very hard67 4 3 2 2 22 129.0 (p < 0.001)

I am NOT obtaining 6 12 12 12 24 34 I am obtaining a lot of new skillsI am obtaining a lot of new skillsa lot of new skills 5 9 10 9 12 55 19.6 (p < 0.001)I am getting better 35 23 15 12 9 6 I am getting worse in the subjectI am getting worse in the subjectin the subject 68 6 2 1 7 16 67.5 (p < 0.001)It is definitely 'my' subject 15 23 29 18 10 5 It is definitely not 'my' subject

35 9 14 20 20 2 31.1 (p < 0.01)Control Group N = 115Experimental Group N = 400

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More Attitude Changes

Thursday, 15 October 2009

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χ2

I am enjoying the subject 15 24 13 25 9 14 I am NOT enjoying the subjectI am NOT enjoying the subject66 6 2 2 5 19 104.2(p < 0.001)

I feel I am NOT coping well 18 10 11 10 24 27 I feel I am coping well30 10 11 3 7 39 39.6 (p < 0.001)

I find it very easy 22 27 23 16 8 4 find it very hard67 4 3 2 2 22 129.0 (p < 0.001)

I am NOT obtaining 6 12 12 12 24 34 I am obtaining a lot of new skillsI am obtaining a lot of new skillsa lot of new skills 5 9 10 9 12 55 19.6 (p < 0.001)I am getting better 35 23 15 12 9 6 I am getting worse in the subjectI am getting worse in the subjectin the subject 68 6 2 1 7 16 67.5 (p < 0.001)It is definitely 'my' subject 15 23 29 18 10 5 It is definitely not 'my' subject

35 9 14 20 20 2 31.1 (p < 0.01)Control Group N = 115Experimental Group N = 400

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More Attitude Changes

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Thursday, 15 October 2009

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EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Improve Selection

Lower Working Memory demand

Encourage Understanding

Thursday, 15 October 2009

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48

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Improve Selection

Lower Working Memory demand

Encourage Understanding

Pre-learning

Thursday, 15 October 2009

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48

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Improve Selection

Lower Working Memory demand

Encourage Understanding

Pre-learning

Re-designpresentation

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

48

EventsObservations Instructions

Perception Filter

InterpretingRearrangingComparing

Problem SolvingPreparing for storage

Working Memory

Feedback loop

Long Term Memory

Storage

Long term store of infinite capacity.(Knowledge, attitudes and skills)

Information can be stored in highly complex matrix, with cross links and

connections

Sometimes stored as separate fragments(eg rote memory learning)

Improve Selection

Lower Working Memory demand

Encourage Understanding

Pre-learning

Re-designpresentation

Emphasise links and assess for understanding

Thursday, 15 October 2009

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Teaching and Learning Successfullyin

Physical Sciences

Stimulating and Enjoyable ?

Thursday, 15 October 2009

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Teaching and Learning Successfullyin

Physical Sciences

Stimulating and Enjoyable ?

What does Research Evidence tell usabout attitudes ?

Thursday, 15 October 2009

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How to Attract Learners to Physical Sciences

Thursday, 15 October 2009

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How to Attract Learners to Physical Sciences

Some Key Research Findings

Thursday, 15 October 2009

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How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

School teachers have a very critical role

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

School teachers have a very critical role

Things outside the school have almost no impact

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

School teachers have a very critical role

Things outside the school have almost no impact

There is a successful curriculum approach

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

School teachers have a very critical role

Things outside the school have almost no impact

There is a successful curriculum approach

Integrated science courses are disasters

Thursday, 15 October 2009

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50

How to Attract Learners to Physical Sciences

Some Key Research Findings

Interest develops early (by age 14)

Boys and girls are equally interested

School teachers have a very critical role

Things outside the school have almost no impact

There is a successful curriculum approach

Integrated science courses are disasters

Career potential must be perceived

Thursday, 15 October 2009

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A Successful Curriculum Approach

Thursday, 15 October 2009

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The Applications-Led Idea

A Successful Curriculum Approach

Thursday, 15 October 2009

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51

The Applications-Led Idea

My first encounter:

The findings of Elena Skryabina in relation to Physics

A Successful Curriculum Approach

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

Usual pattern

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Usual pattern

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Glamour, from ignorance!

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Integrated science

Glamour, from ignorance!

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Integrated science

Applications-led CurriculumGlamour, from

ignorance!

Thursday, 15 October 2009

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What She Found(greatly over-simplified)

AttitudesTowardsPhysics

Age10 1412 1816

What was found

Integrated science

Applications-led Curriculum

Too demanding

Glamour, from ignorance!

Thursday, 15 October 2009

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The Applications-led Syllabus(Scotland aged 14-16)

Thursday, 15 October 2009

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The Applications-led Syllabus(Scotland aged 14-16)

1990

Unit 1: Telecommunication

Unit 2: Using Electricity

Unit 3: Health Physics

Unit 4: Electronics

Unit 5: Transport

Unit 6: Energy Matters

Unit 7: Leisure

Unit 8: Space Physics

Thursday, 15 October 2009

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The Applications-led Syllabus(Scotland aged 14-16)

1990

Unit 1: Telecommunication

Unit 2: Using Electricity

Unit 3: Health Physics

Unit 4: Electronics

Unit 5: Transport

Unit 6: Energy Matters

Unit 7: Leisure

Unit 8: Space Physics

2006

Unit 1: Telecommunication

Unit 2: Using Electricity

Unit 3: Health Physics

Unit 4: Electronics

Unit 5: Transport

Unit 6: Energy Matters

Unit 7: Space Physics

Thursday, 15 October 2009

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The Applications-led Syllabus

Possible Definition

The physics or chemistry to be taught and its teaching order is determined by the learners - their needs, what is perceived by them to be related to their context and lifestyle

Thursday, 15 October 2009

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The Applications-led Syllabus

Towards an Application-Led Curriculum, Staff and Educational Development International, 1999, 3(1), 71-84.

Possible Definition

The physics or chemistry to be taught and its teaching order is determined by the learners - their needs, what is perceived by them to be related to their context and lifestyle

Thursday, 15 October 2009

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More on Attitudes

Thursday, 15 October 2009

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More on Attitudes

Positive Attitudes arise when:

The curriculum is designed as applications-ledIt is taught by enthusiastic and supportive subject specialists

Thursday, 15 October 2009

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More on Attitudes

Positive Attitudes arise when:

The curriculum is designed as applications-ledIt is taught by enthusiastic and supportive subject specialists

What about the Working Memory Problem ??

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Sample = 714, Aged 12-15South Korea

Kendall’s Tau-b Correlation

I am enjoying studying science 0.17

Science is interesting 0.13

Sciences is an important subject for my life 0.16

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Sample = 714, Aged 12-15South Korea

Kendall’s Tau-b Correlation

I am enjoying studying science 0.17

Science is interesting 0.13

Sciences is an important subject for my life 0.16

The work of Eun Sook Jung in South KoreaWorking Memory and Attitudes (2009) Research in Science and Technological Education

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Attitudes and Working Memory Capacity

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Are you interested in science? Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

YES 66% 55% 39% 48% 36% 22%

NO 33% 42% 57% 53% 64% 78%

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Are you interested in science? Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

YES 66% 55% 39% 48% 36% 22%

NO 33% 42% 57% 53% 64% 78%

Thursday, 15 October 2009

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Attitudes and Working Memory Capacity

Are you interested in science? Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

YES 66% 55% 39% 48% 36% 22%

NO 33% 42% 57% 53% 64% 78%

Thursday, 15 October 2009

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Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

I have tried to understand science 71% 54% 50% 70% 61% 37%

I have tried to memorise science 24% 34% 39% 21% 35% 45%

Attitudes and Working Memory Capacity

I have tried to understand science knowledge such as concepts, rules, theoryas much as I can

Thursday, 15 October 2009

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Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

I have tried to understand science 71% 54% 50% 70% 61% 37%

I have tried to memorise science 24% 34% 39% 21% 35% 45%

Attitudes and Working Memory Capacity

I have tried to understand science knowledge such as concepts, rules, theoryas much as I can

Thursday, 15 October 2009

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Level 1 Level 1 Level 1 Level 3 Level 3 Level 3

High(N = 100)

Mid(N = 166)

Low(N = 98)

High(N = 95)

Mid(N = 172)

Low(N = 83)

I have tried to understand science 71% 54% 50% 70% 61% 37%

I have tried to memorise science 24% 34% 39% 21% 35% 45%

Attitudes and Working Memory Capacity

I have tried to understand science knowledge such as concepts, rules, theoryas much as I can

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Attitudes and Working Memory Capacity

A Working Hypothesis

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High Working Memory Capacity

Low Working Memory Capacity

Learners seek to understand

Attitudes and Working Memory Capacity

A Working Hypothesis

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Understanding mainly possible

Understanding often impossible

High Working Memory Capacity

Low Working Memory Capacity

Learners seek to understand

Attitudes and Working Memory Capacity

A Working Hypothesis

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More positive attitudes

Less positive attitudes

Understanding mainly possible

Understanding often impossible

High Working Memory Capacity

Low Working Memory Capacity

Learners seek to understand

Attitudes and Working Memory Capacity

A Working Hypothesis

Thursday, 15 October 2009

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Making LearningAccessible, Stimulating and Enjoyable

What Does Research Tell Us ??

Accessible

Stimulating

Enjoyable

Thursday, 15 October 2009

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Making LearningAccessible, Stimulating and Enjoyable

What Does Research Tell Us ??

Accessible

Stimulating

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating

Enjoyable

Thursday, 15 October 2009

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Making LearningAccessible, Stimulating and Enjoyable

What Does Research Tell Us ??

Accessible

Stimulating

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating Presentation based on Meaningful Applications

Enjoyable

Thursday, 15 October 2009

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Centre for Science Education, University of Glasgow, Scotland

60

Making LearningAccessible, Stimulating and Enjoyable

What Does Research Tell Us ??

Accessible

Stimulating

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating Presentation based on Meaningful Applications

Enjoyable

Accessible Working Memory is Critical for Understanding

Stimulating Presentation based on Meaningful Applications

Enjoyable Understanding is critical for positive attitudes

Thursday, 15 October 2009

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Thursday, 15 October 2009

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Tries to understand the physical world around

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Tries to understand the physical world around

Working Memory can cope

Thursday, 15 October 2009

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Tries to understand the physical world around

Working Memory is overloadedWorking Memory can cope

Thursday, 15 October 2009

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Thursday, 15 October 2009

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I cannot understandI find it difficult

I shall never understand

I shall give up and opt out

Thursday, 15 October 2009

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I cannot understandI find it difficult

I shall never understand

I shall give up and opt out

Memorisation is the only way to pass

Working Memoryis overloaded

Thursday, 15 October 2009

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I can cope

I can understand

I find it accessible, stimulating and enjoyable

I cannot understandI find it difficult

I shall never understand

I shall give up and opt out

Memorisation is the only way to pass

Working Memoryis overloaded

Thursday, 15 October 2009

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I can cope

I can understand

I find it accessible, stimulating and enjoyable

I cannot understandI find it difficult

I shall never understand

I shall give up and opt out

Memorisation is the only way to pass

Working Memoryis overloaded

Working Memoryis coping

Understanding is possible

Thursday, 15 October 2009

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A Scientific Approachto the

Teaching of Chemistry

Norman [email protected]

Thursday, 15 October 2009

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A Scientific Approachto the

Teaching of Chemistry

Norman [email protected]

Thank You

Thursday, 15 October 2009