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Open data in Education



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Open data in Education

  1. 1. Open data in Education What? Why? How? Where? When? Marieke Guy Edtalk, November 26th 2014
  2. 2. Open Knowledge Promoting open knowledge in a digital age ● A community-based, not-for-profit with projects and partnerships throughout the world ● We build tools, apps and communities to create, use and share open data and content - information that everyone can use, share and build on ● We believe that by creating an open knowledge commons and developing tools and communities around this we can make a significant contribution to improving governance, research and the economy ● Collaboration not control, empowerment not exploitation, open not closed
  4. 4. By Mark Johnstone, Flowing data
  5. 5. Open Data What exactly is it? “Open means anyone can freely access, use, modify, and share for any purpose (subject, at most, to requirements that preserve provenance and openness).” “Open data and content can be freely used, modified, and shared by anyone for any purpose” Taken from the Open definition
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  7. 7. Types of Open Data Data sets that are openly licensed ● Cultural: Data about cultural works and artefacts ● Science: Data that is produced as part of scientific research ● Finance: Data such as government accounts (expenditure and revenue) and information on financial markets (stocks, shares, bonds etc). ● Statistics: Data produced by statistical offices such as the census and key socioeconomic indicators. ● Weather and environment: Climate and natural environment ● Transport: Data such as timetables, routes, on-time statistics.
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  13. 13. • Open data that comes out of education institutions • Open data that can be exploited/ used by education institutions • Open research data Open Education Data
  14. 14. open data that can be used in an educational way Terms? open data in education Open education data open educational data open data from education
  16. 16. Open Education Data What data are we talking about? ● Student data: attendance, grades, skills, exams, homework ● Course data: employability related to courses, curriculum, syllabus, VLE data, number of textbooks, skills, digital literacy… ● Institution data: location data, results, infrastructure, location, student enrolment, textbook budget, teacher details… ● User-generated data: learning analytics, assessments, performance data, job placements, laptop data, time on tasks, use of different programmes/apps, web site data… ● Policy/Government data: equity, budgets, spending, UNESCO literacy data, deprivation and marginalisation in education, participation data…
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  18. 18. ‘Open’ Data Sets Related to UK education ● Department for education data sets / / Ofsted ● Programme for International Student Assessment (PISA) ● Office for National Statistics ● - snapshot of Edubase taken in 2009, linked data ● Higher Education Statistics agency - HESA ● Higher Education Information Database for Institutions - HEIDI ● University Key Information Sets (KIS) ● University linked open data – LinkedUp Catalogue ● Excellent list from Open Data Institute:
  19. 19. Paper provisory title: My Transparent School – A comparative analysis of open government data in basic education between Brazil and England By Octavio Ritter
  20. 20. Open Data Analysis • Macro (Education Policy) • Census data, School performance indicators, Spending data • Accountability model (high stake, low stake) • Media (rankings, data journalism) • Watchdogs (official and unofficial) • Participation (NGOs, private companies, hackathons, etc) • Meso (School Management) • School performance indicators , administrative data (academic, management) • Data Benchmark • Collaboration vs Competition models (i.e. London challenge) • Data support to local authorities • Local open data groups (i.e. Manchester) • Free data analysis tools to poor councils (Brazil) • Micro (Student) • Pupil personal data, academic history data, big learning data • Conflict with private data (i.e. open government data vs data sharing) • Personalized Learning • Education Data Mining (EDM) • Government as Plataform
  21. 21. National Pupil Database What is in it? ● Test and exam results ● Attainment data for students in non-maintained special schools, sixth-form and further education colleges ● Information on pupils in independent schools, where available ● Gender, ethnicity, first language, eligibility for free school meals ● Special educational needs (SEN), pupil absence and exclusions ● Researchers and third-party organisations can apply for data extracts from the national pupil database ●
  23. 23. Open Public Service Network Empowering Parents, improving accountability ● Report published September 2013 by RSA ● Calls for release of data sets: Ofsted, free & private schools data, teacher survey, parents views ● “Dangers of overemphasising the role of school choice as the main driver of parental interest in information about their children’s schools. It is equally important as contextual information for parents and children wanting to understand their own or their child’s educational progress” (Millar & Wood)
  24. 24. Using Open Data meet educational needs By supporting students ● New tools, enriching resources, exploration, informed choices By supporting schools and institutions ● Learning analytics, improve efficiencies, benchmarking By supporting governments and policy ● Change in policy, transparency, trust, education reform ● Value often in mashing together different datasets!
  25. 25. UniversitiesUK & Deloitte government’s open data user group harvey-lewis-research-director-analytics-deloitte-london
  26. 26. • School funding - corruption resulted in gov money never reaching its destination • 1995 and 2001 funding reaching schools rose from 24% to 82%. • Programme of publishing data • See Hubbard 2007 & Reinikke and Svensson (2004)
  27. 27. ● Won Making All Voices Count global innovation competition ● Mobile app that allows officials and citizens to monitor attendance by teachers and students at school ● Data released openly ● The initiative has led to improved teacher attendance, which in turn has led to improved pupil grades
  28. 28. Case Studies Burkina Faso RMSchoolfinder
  29. 29. Data Hacking Challenges
  30. 30. Creating Open Data And releasing it… ● See the open data handbook!! ● Keep it simple. Start out small, simple and fast. ● Remember this is about innovation. ● Engage early and engage often, consider ethics ● Remember the data is likey to reach info-mediaries ● Use open licenses ● Make the data available - in bulk and in a useful format ● Remember people will want to combine data sets, use local data & open data – here lies the value!
  31. 31. Universities & Open Data Creating value from open data ● Universities UK seminar series: ● Jisc funding – partners - Universities UK, ODI, NUS, Leadership Foundation ● Universities signed up: Edinburgh, Oxford, Cambridge, Newcastle, Aberdeen, OU, Southampton, Greenwich ● Possible work to develop a web based app, data set release ● Looking at staff recruitment, business processes, research management and the REF, student experience (e.g use of labour market information) ● Data capability study – data skills curriculum
  32. 32. Monetising Open Data The figures…. ● McKinsey - open data has a potential global value of $3tn ● Omidyar Network - open data – including open access research – could contribute as much as $13tn to the economies of the G20 nations cumulatively over the next five years. ● EU research - Open government data in EU would increase business activity of €40bn - reduction in transaction costs, transparency, savings etc. ● ???
  33. 33. Monetising Open Data How is it done? ● Transparency and improved efficiencies ● Business models: freemium (added value), cross subsidy (more customers), network effects ● Open Data 500 is the first comprehensive study of U.S. companies that use open government data to generate new business and develop new products ● Open Data Institute – Make a business case
  35. 35. Learning Analytics What is it? ● “The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” ● Who is the collection for? What is the collection for? ● There have been conflicts between analytics for individual learners and organisational stakeholders ● New area of Learning analytics for online courses such as MOOCs ● See &
  36. 36. Learning Analytics Data Can be used to… ● Enable grade prediction and student success ● Improve student retention ● Measure student performance ● Determine what learners know and what they currently do not know ● Monitor learner engagement ● Personalize learning and ensure relevant content is delivered ● Reduce classroom administrative work ● More potential – it’s a tool…
  37. 37. AND LEARNING?
  38. 38. …and learning
  39. 39. Open Data Use in Education Ideas for another day… ● So many data sets available including open research data ● Could be used by those in education online and in classrooms ● Use open data in as raw materials ● Will get people engaged in politics, interested in the world ● Need core data sets, linked with curriculum ● Data expeditions concept at School of Data: ● Great examples in LinkedUp Challenge – used for teaching in politics, agriculture, history, culture, ecology, medicine etc. ● LinkedUp Project:
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  42. 42. Challenges, Issues And opportunities… ● Measuring, monitoring, protecting privacy and ownership ● Difficulties of improving learning without intruding on privacy ● What should be collected/released? How should it be assessed? ● Measurement and data leading to reductionist myth ● Will greater measurement lead to “better grades, test scores and graduation rates”? ● Data literacy – correlation vs causation ● Stress of measurement ● The transparency trap ● Sustainability of applications
  43. 43. Measuring and Monitoring What? Where? When? ● The bus stop ● School office ● The classroom ● The cafeteria ● Nurse’s office ● The gym ● At home ● Online
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  45. 45. Privacy Quality, quantity and context “At first approximation privacy seems to be related to secrecy, to limiting the knowledge of others about ones self. This notion must be refined. It is not true, for instance, that the less that is known about us the more privacy we have. Privacy is not simply an absence of information about [us] in the minds of others; rather it is the control we have over information about ourselves.” Charles Fried, Privacy, 77 Yale L.J (1968)
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  47. 47. Reductionist Myth Does it apply to open education data? ● Idea that complex phenomenon can be broken down into conceptual chunks small enough to be analysed or measured ● Will greater measurement lead to “better grades, test scores and graduation rates”? ● Measurement is complex - correlation vs causation ● Data is rarely open to the public in any meaningful sense - “data divide” ● Need for data literacy (see School of Data: ● Need for data to be actionable – open data standards – conformant licences
  48. 48. Food for Thought How do you feel about open education data? ● What data should be collected within education institutions or for assessment? ● Do we need an open education data census? ● Government open data reflects actual public policy – what is available is variable from country to country ● How do we evaluate this data? i.e. What makes a good student/citizen? What makes a good school? ● Can open data open up the debate to a wider audience? ● Can open data lead to policy change and better education systems? Worldwide? ● Remember – good questions lead to better answers!
  49. 49. Shaping Change With open education data… Our opportunities for improvement are immense, and data provide a powerful lens to understand how we are doing internally and relative to our peers. This applies across all segments of what we do, from teaching and learning to administrative support. Performance metrics and dashboards are the beginning, but using data to understand deeper correlations and causality so we can shape change will be critical as we strive to advance our effectiveness. David Lassner, Interim president and former chief information officer at the University of Hawaii
  50. 50. Conclusion How can your institution use open data ● Open education data holds huge value and potential ● You need to consider the real value to you and your institution ● This value may relate to: v Transparency v Commercial value v Social value v Participation and engagement v Making learning better ● Open knowledge is what open data becomes when it’s useful, usable and used
  51. 51. Open Education WG People, projects and initiatives ● Brings together people and groups interested in open education ● Wants to initiate cross-sector, cross-domain, global activity that encompasses the various facets of open education ● Active mailing list and Twitter feed, activities are co-ordinated through bimonthly working group calls ● Includes open data in education, open educational content, open learning and teaching practices and open accreditation ● Just released ePub, PDF and online version of Open Education Handbook
  52. 52. Marieke Guy Twitter @mariekeguy