Prindi

Elinda Dobrovoda

Title: 'Big Data in Education: Using Educational Data Mining and Learning Analytics to Improve Policy in the Field of Education

Supervisor: Dr. Piret Tonurist; Associate Prof. Dr. Innar Liiv

Opponent: Anne Kivimäe, MA

Defense: 20 January 2017

 

Abstract: The thesis gives an exploratory overview of the state of the art of learning analytics and educational data mining in higher education. It highlights the emergence of learning analytics (LA), its drivers, processes and the opportunities it offers for improving policy making in the field of education. While education sector lags behind other sectors in generating valuable insights from big data, to enhance the learning experience, numerous institutions in Australia, UK and US are making significant progress in the field. The field of learning analytics and its associated fields holds much promise in its potential to address the issues and challenges facing higher education institutions. However, in order to adopt learning analytics in the educational domain, universities are in need of policies and frameworks to aid their transition to new educational models that will address these complexities and challenges. This thesis undertakes a comparative case study analysis to address the opportunities learning analytics offer for policy making and to compare the work being done on preparing to make use of educational data to improve policy in Australia, UK, US. Its primary finding is that all three countries echo a strategic national plan to address issues facing their higher education institutions such as reducing drop outs and enhancing learning experience through personalization and real-time feedback. The thesis concludes with a comparison of the selected countries, where according to document analysis US and Australia are ahead of UK in implementing LA on an institutional level whereas UK is progressing more on a national level by equipping institutions with necessary mindset for embracing LA.

Keywords: Learning analytics, educational data mining, policy making, education, Australia, UK, US.