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Learning analytics for the global south
The report “Learning Analytics for the Global South” (recently published) aims to analyse how learning analytics (collection, analysis, and use of data) contribute to improve educational processes, learning and teaching practices.
“(how Learning Analytics) have the potential to broaden access to quality education and improve the efficiency of educational processes andsystems in developing countries around the world”
The report is a compilation commissioned by the Digital Learning for Development (DL4D) project. DL4D is part of the Information Networks in Asia and Sub-Saharan Africa (INASSA) program funded jointly by the International Development Research Centre (IDRC) of Canada and the Department for International Development (DFID) of the United Kingdom, and administered by the Foundation for Information Technology Education and Development (FIT-ED) of the Philippines. DL4D aims to examine how digital learning could be used to address issues of equity, quality, and efficiency at all educational levels in developing countries.
Contributions are based in the Prof. Gašević’s proposal and his perspective about the challenges for promote 21st century skills in new generations. Each of the contributions situates Gašević’s proposals in differents world contexts from the hand of experts in the field of research in Education and Technology. Paul Prinsloo of the University of South Africa; Bodong Chen of the University of Minnesota, USA and Yizhou Fan of Peking University, People’s Republic of China; Ma. Mercedes T. Rodrigo of the Ateneo de Manila University, Philippines, and Cristóbal Cobo and Cecilia Aguerrebere, Ceibal Foundation, Uruguay.
The articles address the following questions:
- What are the main trends and challenges for education in your region?
- How can learning analytics address those challenges?
- What models of learning analytics adoption would be most effective in your region?
- What are the barriers in adoption of learning analytics in your region and how could these be mitigated?
- How do you envision ethical use and privacy protection in connection with learning analytics being addressed in your region?
- How can the operationalization of learning analytics be future proofed in your region?
The publications ends with recommendations about what are the necessary aspects to consider in order to think about learning analytics as the quality and quantity of data, the nature of the tools and techniques used, the available infrastructure. Other substantially relevant issue includes transparency.
