An online interactive simulation to aid the learning of probability.

by

Roger Gossett & Richard Haynes

London Metropolitan University

Presentation OverviewProject Aim

To develop an on-line computer operated resource to aid the learning of probability.

Development of resource

Testing

Evaluation

Findings

Future direction

Why probability?

Research methods

Why use computer assisted learning?

Conceptual representation

Student background

Mature

Little science

Little mathematics GCSE grade C

alternative qualifications

little familiarity with basic mathematical procedures such as fractions, decimals and percentages

Research Design

Quantitative and Qualitative

Quantitative

Three mathematical tests

Test 1 – before any teaching (baseline)

Test 2 – following on-line teaching

Test 3 – following traditional lecture

Questions graded according to Blooms Taxonomy of learning objectives (knowledge, comprehension, application, analysis, synthesis and evaluation).

Quantitative data collection

Quantitative data – presentation

Quantitative data – analysis

Legend: Group A Group B

Test Scores Low Level Objectives

Test Number

321

Mea

n T

est

Sco

re

12.0

11.5

11.0

10.5

10.0

9.5

9.0

8.5

Test Scores High Level Objectives

Test Number

321

Mea

n T

est

Sco

re

6.6

6.4

6.2

6.0

5.8

5.6

5.4

Quantitative data – findings

For low level objectives

The computer simulation was no better at improving student learning than the traditional lecture.

High level objectives

Although computer simulation methods can enrich a student’s learning experience, additional activities are required in order for students to change their misconceptions.

Research Design: QualitativeOpen ended questionnaire

Inductive content analysis

Used for three purposes

(I) to inform the evaluation of the resource

(II) to gain feedback on the affective learning experience of the students across both learning modes

(III) to aid the development of an evaluative questionnaire to be used in an extended project

Qualitative: data collection and analysisContent Analysis – Online teaching

32 open-ended questionnaires produced 247 statements

95

201

102

23

6

0

20

40

60

80

100

120

Higher order themes

Lower order

Content Analysis – face to face teaching

13

6

1115

1

19

1

48

23 24

1

42

8 60

10

20

30

40

50

60

Lectu

re fa

voure

d ove

r sim

ulatio

n

Simula

tion fa

voure

d ove

r lec

ture

Content p

ositiv

e as

pects

Content n

egat

ive

aspec

ts

Struct

ure p

ositiv

e as

pects

Struct

ure n

egat

ive

aspec

ts

Test n

egat

ive

aspec

ts

Deliv

ery

positiv

e as

pects

Deliv

ery

negat

ive

aspec

ts

Studen

t per

form

ance

posi

tive

aspec

ts

Studen

t per

form

ance

neg

ativ

e as

pects

Prior l

earn

ing

OIR p

ositiv

e as

pects

Enhance

d lear

ning

General dimension (GD)Teacher centred aspects

GD Studentcentred aspects

Higherorder

themes

The evaluative questionnaire

“Is this resource an effective way of supporting the learning of probability?”

  Statement Lecture Simulation

1There were few mistakes in this presentation.

SA A U D SD SA A U D SD

2The information presented was at the correct level.

SA A U D SD SA A U D SD

The 465 raw data statements were condensed into 36 statements for the questionnaire.

Generating questionnaire statements from raw data

81 low er order themes

On-line teaching247 raw data statements

73 low er order themes

F2F teaching218 raw data statements

465 Raw data statements

Lower order themes were the common denominator between the content analysis and the

development of the evaluative questionnaire.

Combination of lower order themes within the on-line teaching situation.

Lower order themes    

On-line teaching Mediation Resulting statement

Examples useful (1)explanations useful (1) simulation useful (1) simulation improved understanding (1)

Four lower order themes combined into a single statement

The examples and explanations helped my understanding

More explanation needed (1) explanations inflexible (1) explanations incomplete (1)Insufficient examples (4) …

Eight lower order themes combined into a single statement

I would have preferred more explanations and examples

48 pooled low er order statments

36 joint statements

37 combined low er order statements

81 low er order themes (on-line)

21 low er order statements

73 low er order themes (F2F)

Pooling the statements made it clear that there were similarities in the affective feedback not only within but across teaching situations.

Condensing of pooled statements resulted in 36 statements equally applicable to both teaching situations.

Further developments (1)Improve SENDA compatibility

Explore gender differences

Develop a more intellectually challenging resource

Improve interactivity

Develop resource as a series of learning objects

Quantitative tests to include a more even spread of questions across learning objectives

Further developments (2)

Increase sample size with students from a greater variety of backgrounds

Use alternative qualitative data collection techniques

Test transfer of learning by ability in a different context

Continue evaluation using the questionnaire

Test validity of questionnaire using factor analysis