Child’s Play - Reasoning with Multidimensional Data

1. Child’s Play - Reasoning with Multidimensional Data Jim Ridgway, James Nicholson and Sean McCusker jim.ridgway@durham.ac.uk University of Durham www.dur.ac.uk/smart.centre/ OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

2. Child’s Play – Reasoning with Multi-Dimensional Data • Play therapy • Alcohol, Fast Birds, and Sexually Transmitted Infections • Research • Testing smart 9 and 13 year olds – they can reason with multidimensional data • Generalising to representative students – they can do it too • What don’t we know • The threat of education • What are we doing about it all OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

3. Child’s Play • Sexually Transmitted Infections • Alcohol • Fast Birds • http://www.ic.nhs.uk/pubs/alcoholeng2006/alcoholtables/file • www.hpa.org.uk/infections/topics_az/hiv_and_sti/epidemiology/datatables2005.htm In collaboration with CCEA, QCA and The Information Centre OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

4. Child’s Play - Research • Oxygen • Testing smart 9 and 13 year olds • Generalising to representative students OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

5. From Watson and Callingham OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

6. OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

7. The Threat of Education • Condorcet le savoir liberateur and all that… • UK students are taught 1930s statistics (Ridgway et al, 06) • the 1930s principle was fine – ‘take something of interest and mathematise it’ OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

8. Child’s Play – What don’t we know? What do/can people understand from multivariate data – in an emerging field? What can people learn as they interact with data? OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

9. Some Heuristics for Playing • Critique the quality of the data • Describe and explore before you model and explain • Check that the effect size is a lot bigger than the likely measurement error • Look for interactions, and think about ‘data surfaces’ • Think about possible confounding variables • Disaggregate data – are the patterns the same? • Be cautious about ‘causality’ – especially in observational data OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

10. Our Current Work • Interface design • Generic shells as freeware • Empirical studies on difficulty • Curriculum development • Modelling disease spread • Risk taking by young people • Drugs, sex, obesity, alcohol abuse • Conceptual analyses • What is worth knowing? • What develops? • How? • Collaborating! - http://www.dur.ac.uk/smart.centre OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

11. Child’s Play - Reasoning with Multidimensional Data Jim Ridgway, James Nicholson and Sean McCusker jim.ridgway@durham.ac.uk University of Durham www.dur.ac.uk/smart.centre/ OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

12. Levels of Statistical Literacy OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

13. Computer Based Paper Based OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

14. Oxygen OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

15. From AQA OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

16. From AQA OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

17. ALL National Exams (2004) ‘Technique’ as % of Exam OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker

18. Average Score/Maximum Score Computer Based Paper Based OECD March 07 Jim Ridgway, James Nicholson and Sean McCusker