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

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

Learning (& practicing) science requires statistics “Statistics is the grammar of science” - Karl Pearson (1857-1936) Statistics taught in all science programmes Scientific practice Science skills Research methods Unhelpfully, students tend to dislike statistics… Statistics - a taboo word?

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?

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

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”

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

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!

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

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

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

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 (1866-1946) 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.

Evaluation: marks Mann-Whitney Test and CI: 2018, 2017 N Median 2018 147 80.000 2017 149 90.000 Point estimate for η1 - η2 is -13.333 95.0 Percent CI for η1 - η2 is (-13.335,-10.002) W = 16966.0 Test of η1 = η2 vs η1 ≠ η2 is significant at < 0.00005

Evaluation: engagement Test and CI for Two Proportions - NonSubmissions Sample X N Sample p 2017 9 158 0.057 2018 11 158 0.070 Difference = p (1) - p (2) Estimate for difference: -0.013 95% CI for difference: (-0.066, 0.041) Test for difference = 0 (vs ≠ 0): Z = -0.46 P-Value = 0.644 Fisher’s exact test: P-Value = 0.818

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