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Researching openness – evidence-based approach - Mairéad Nic Giolla Mhichíl


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Presentation of Mairéad Nic Giolla Mhichíl, Dublin City University, Ireland, for the Open Education Week's fifth-day webinar on "Researching openness – evidence-based approach " - 8 March 2019
Recordings of the discussion are available:

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Researching openness – evidence-based approach - Mairéad Nic Giolla Mhichíl

  1. 1. Professor Mairéad Nic Giolla Mhichíl @1mngm • Head of the Ideas Lab@National Institute of Digital Learning in Dublin City University in Ireland • MOOC based research in a series of Irish language and culture MOOCs • Sentiment Analysis of emotions • Motivation and link to identify - • Learning Design • Unbundling and rebundling of higher education
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  3. 3. Presentation • What are the today most relevant research challenges on Open Education? • Can Evidence-Based Research approach offer a new and better perspective to the Open Education research? • What kind of Evidence-Based research methodologies are more appropriated to research on Open Education?
  4. 4. Q1- Challenges • Sound well-designed research • Ethical issues relating to data collection Selwyn (2014) terms as “dataveillance” – “if you're not paying for the product, you are the product” – Ultimately with the business models of the major platforms becoming increasingly commercial • Will learners become the product? • The influence of platforms on the type and how research can be conducted • Studies which maybe atheoretical and WEIRD (western, educated, industrial, rich and democratic )
  5. 5. Q2- Evidence-Based Research New – Better Perspectives • Particularly in the case of interdisciplinary research in Open Education – Drawing from fields such as psychology, education and applied linguistics and use theory – Existing literatures have to offer and how our research can complement that body of literature • e.g. CALL research mainly in global languages, other languages in various contexts
  6. 6. Q3- Methodologies • Danger of over-reliance on particular methodologies – Quantitative-orientation emphasising a particular type of question, sometimes what can be readily measured and perhaps less-rich understandings – Qualitative interpretive approach using particular research design inclusive of digital-aided analysis