1. Open data for science learning
Mario Orsi
Department of Applied Sciences
UWE Bristol

2. Acknowledgments Faculty of Health and Applied Sciences
Learning & Teaching Innovation competition

3. Learning (& practicing) science requires statistics
“Statistics is the grammar of science” - Karl Pearson ( )
Statistics taught in all science programmes
Scientific practice
Science skills
Research methods
Unhelpfully, students tend to dislike statistics…
Statistics - a taboo word?

4. Traditional statistics teaching is boring
Maths/stats, to a point, are inevitably dry subjects, but there is scope for improvement
How to improve students’ engagement?
Activities should be meaningful, worthwhile, authentic – but how?

5. Using real data OpenIntro Statistics textbook (2015)
Free and open-source
Use of real (literature) data
Working on real problem is motivational
Use new data, do new science?
Problem: traditionally difficult to generate/access data
Solution: open data

6. Open access to real data is fast increasing
Funding agencies now typically require data to be deposited and freely accessible
“The Government is releasing public data to become more transparent and foster innovation” [data.gov.uk]
Research councils now promote use of “secondary data”

7. Coursework: Criminality & Inequality
Correlation between homicide rates and economic inequality
Published results were obtained with old data (before 2009)

8. Coursework: Criminality & Inequality
Task: reproduce correlation analysis
New data from public database (CIA World Factbook)
Students to perform new analysis of real problem on current data
Original finding not reproduced!

9. Unintended (yet very positive) outcomes
Confidence-building:
Learners directly experience (re)creation of published research
Critical thinking:
New data may disprove original findings
Demystification of science
Especially important for students of non-traditional academic background, first generation university students.
The metaphorical ivory tower of academia can become more accessible.
Of course this can be achieved without open data – however open data make the process much easier

10. Open data – open opportunities
Freedom for learners to shape own assessment
Ready availability of data without having to do experiments
Opportunity for weaker/nontraditional students
Previously: no labs, no data - ‘relegated’ to literature reviews
Now: can do ‘real’ science projects using open data

11. New website under development (opendatastat.org)
For students:
Curated data
Ideas for projects
Tutorials
For staff:
Data repository (free publicity)
Collaboration
Secondary data research

12. Alignment to more general objectives
“Our graduates […] well equipped to make a positive contribution to society […] in developing a sustainable global society and knowledge economy […] globally responsible, future-facing.”
"Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write“ - H.G. Wells ( )
Statistics can be a powerful tool to improve society, as it can provide solid, quantitative arguments against divisive lies and propaganda. Students can apply statistics to analyze data potentially relevant to global issues such as health, sustainability, climate change, and the economy.

13. Evaluation: marks Mann-Whitney Test and CI: 2018, 2017 N Median
Point estimate for η1 - η2 is
95.0 Percent CI for η1 - η2 is ( , )
W =
Test of η1 = η2 vs η1 ≠ η2 is significant at <

14. Evaluation: engagement
Test and CI for Two Proportions - NonSubmissions
Sample X N Sample p
Difference = p (1) - p (2)
Estimate for difference:
95% CI for difference: (-0.066, 0.041)
Test for difference = 0 (vs ≠ 0): Z = P-Value = 0.644
Fisher’s exact test: P-Value = 0.818

15. Evaluation summary
Difficult to draw conclusions: different cohorts, different tasks
Website: hits, downloads, feedback