1. An online interactive simulation to aid the learning of probability. by Roger Gossett & Richard Haynes London Metropolitan University

2. Presentation Overview  Project Aim To develop an on-line computer operated resource to aid the learning of probability.  Development of resource  Testing  Evaluation  Findings  Future direction

3. Why probability?  Research methods Why use computer assisted learning?  Conceptual representation Student background  Mature  Little science  Little mathematicsGCSE grade C alternative qualifications little familiarity with basic mathematical procedures such as fractions, decimals and percentages

4. 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).

5. Quantitative data collection

6. Quantitative data – presentation

7. Quantitative data – analysis Legend: Group AGroup B

8. 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.

9. Research Design: Qualitative Open 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

10. Qualitative: data collection and analysis Content Analysis – Online teaching 32 open-ended questionnaires produced 247 statements

11. Content Analysis – face to face teaching

12. The evaluative questionnaire “Is this resource an effective way of supporting the learning of probability?” StatementLectureSimulation 1 There were few mistakes in this presentation. SA A U D SD 2 The information presented was at the correct level. SA A U D SD The 465 raw data statements were condensed into 36 statements for the questionnaire.

13. Generating questionnaire statements from raw data Lower order themes were the common denominator between the content analysis and the development of the evaluative questionnaire.

14. Combination of lower order themes within the on-line teaching situation. Lower order themes On-line teaching MediationResulting 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

15. 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.

16. 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

17. 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