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Governing by data: Considerations on the role of learning analytics in education

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Presented by Rosanna De Rosa (Università di Napoli Federico II)
and Chiara Ferrari (Ipsos Group) at <a>The International Data Science & Social Research (DSSR) Conference</a> was held in Naples from 17 to 19 February 2016.

Published in: Education
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Governing by data: Considerations on the role of learning analytics in education

  1. 1. 11111111 GOVERNING BY DATA 1 © 2016 Ipsos. Considerations on the role of learning analytics in education Rosanna De Rosa (Università di Napoli Federico II) Chiara Ferrari (Ipsos Group)
  2. 2. 2 Teaching in the digital era is characterized by a predominance of complexity
  3. 3. Physical vs. digital spaces Production vs. consumption Formal vs. informal just to name a few… LEARNING HAS BECOME AN INTERCONNECTED EXPERIENCE In this scenario, the concept of MOOCs and of the learning data attached to them, offer invaluable materials to reflect on how we will need to adapt practices and policies to the changing learning process
  4. 4. THE ROLE OF ANALYTICS IN EDUCATION Not only an educational application of web analytics LEARNING ANALYTICS Which allows to • Profile learners • Analyse students interactions • Measure learning uptake But, also a tool for measuring operational excellence ACADEMIC ANALYTICS “ … the evidence of how the training /learning organisation is aligning with and meeting the goals of the broader organisation” (van Barneveld, Campbell – 2012) And a source of insights aimed at identifying trends to forecast and plan future strategies PREDICTIVE ANALYTICS
  5. 5. LEARNING ANALYTICS One of the most powerful, disruptive and relevant innovations in the field of education BIG DATA A new type of corporate asset, working to leverage competition DISTANCE EDUCATION No longer an institutional accessory, BUT it needs funding Will benefit from the results of the analysis, which will testify of the success of the learning experience and therefore will drive political and social approval = MONEY THE GAME CHANGER EFFECT: the education industry THE TRANSFORMATIVE POWER OF DATA
  6. 6. THE GAME CHANGER EFFECT: the accountability challenge THE TRANSFORMATIVE POWER OF DATA The Italian case • The academic sector needs a re-organization • An assessment system is put in place re. the research production essentially based on peer reviewing • The mono-dimensional nature of the tool – among other weaknesses – appears unsuitable to cover the complexity of the academic activity The risk of taking political decisions (e.g. cost reductions and investments) based on a mono-dimensional evaluation is obvious Institutions accountability must be based on the wealth of data available: students success, research production, organisational work, and so on
  7. 7. THE GAME CHANGER EFFECT: efficiency THE TRANSFORMATIVE POWER OF DATA Data governance can be efficiently managed by the combination of • Data stewardship • Reporting • Query • Analytic tools which, efficiently connected, will be able to deploy the descriptive and the predictive powers of analytics and to inform strategies
  8. 8. THE GAME CHANGER EFFECT: from descriptive to predictive THE TRANSFORMATIVE POWER OF DATA DESCRIPTION The usage of Learning Analytics in the context of online education is being piloted in various European projects • Course design • Retention rates • Completion rates Real time - Retrospective analysis
  9. 9. THE GAME CHANGER EFFECT: from descriptive to predictive THE TRANSFORMATIVE POWER OF DATA PREDICTION / PRESCRIPTION Using data mining on datasets of millions of students records PARframework*, uses descriptive, inferential and predictive analyses to identify variables that should have direct impact on success *PARframework.org, adopted by 35 US academic institutions and leveraging on datasets from 350 campuses THE CHALLENGES  PRIVACY • Records are de-identified  GOVERNANCE • Who translates data into policies? (and, with what kind of expertise?) • Who sets the objectives? • Who governs the results?
  10. 10. The percentage of 25- to 34-year-olds in the U.S. who have completed an associate's degree or higher 69,3% 18,1% 26,5% 45,8% 38,8% 0 20 40 60 80 ASIAN HISPANIC BLACK WHITE TOTAL US Who governs the results? Depending on how this data are looked at and by whom, one might conclude that some groups of students are not doing well enough and are not worth investing in, which may reproduce /perpetuate social inequalities
  11. 11. THE GAME CHANGER EFFECT: governance THE TRANSFORMATIVE POWER OF DATA THE NEW KID ON THE BLOCK Ben Williamson, in the World Yearbook of Education 2014, identifies ‘public policy labs’ as a new actor in educational governance scene and highlights the inherent risks • Not only they diagnose problems but they also translate ideas and processes into educational policy proposals • They transform education into a ‘problematic object’ • They re-configure learners into ‘calculable governing resources’ Individual learners’ data used to inform policies on which pedagogies and practices work best. Education as a self-regulating system using database driven processes
  12. 12. THE GAME CHANGER EFFECT: governance THE TRANSFORMATIVE POWER OF DATA A WAY OF OVERCOMING THE CHALLENGES* *FERGUSON, 2012 The Learning Analytics community needs to • Build strong connections with the learning sciences • Develop methods of working with a wide range of datasets in order to optimise learning environments • Focus on the perspectives of the learners • Develop and apply a clear set of ethical guidelines BIG DATA need to be deeply rooted in institutional and organisational practices and to be supported by • Strong leadership commitment • A genuine culture of evidence, intertwined with • a discipline of interpretation (assumption, description, interpretation, prediction, implication)
  13. 13. BIG DATA implications FOOD FOR THOUGHT AND FOR FURTHER DISCUSSION What is the social impact of big data and analytics, on standardisation or on social control ? • the realisation of Clarke’s digital persona “a model of the individual established through the collection, storage and analysis of data about that person”, • the ‘dataveillance1’ potential, • the ‘dataspace2’ influence on our life, • the data as a ‘meme3’ and the risk of their “naïve or nefarious uses, to restrict access or to punish”, • the ‘hidden curriculum4’ effect, … 1 Roger Clarke, 1987 2 Perry, 2011 3 Ellen Wagner, 2014 4 Edwards, 2015
  14. 14. 14 Thank you!! Rosanna De Rosa Università di Napoli Federico II rderosa@iunina.it Chiara Ferrari Ipsos Group chiara.ferrari@ipsos.com

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