Donaldson, P. , Ntarmos, N. and Portelli, K. (2017) A Systematic Review of the Potential of Machine Learning and Data Science in Primary and Secondary Education. Discussion Paper. Royal Society. (Unpublished)
Full text not currently available from Enlighten.
Publisher's URL: https://royalsociety.org/topics-policy/projects/royal-society-british-academy-educational-research/
Abstract
This review, commissioned by the Royal Society, will examine the current state of the art developments in data science and machine learning within education, if they can be applied more broadly now, or in the future, and the impact they could have on transforming primary and secondary education in the UK. A sample of the total volume of research reviewed is directly referenced in the body of the report to help illustrate key issues. The full list of sources reviewed is included as the last section of the technical appendix. This appendix also provides further details on the systematic review process, important researchers in each sub-field, a list of current and recent research projects and existing tools, applications and products.
Item Type: | Research Reports or Papers (Discussion Paper) |
---|---|
Additional Information: | Available under Evidence documents link. |
Status: | Unpublished |
Glasgow Author(s) Enlighten ID: | Ntarmos, Dr Nikos and Portelli, Mr Kurt and Donaldson, Mr Peter |
Authors: | Donaldson, P., Ntarmos, N., and Portelli, K. |
Subjects: | L Education > LB Theory and practice of education Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
College/School: | College of Science and Engineering > School of Computing Science College of Social Sciences > School of Education College of Social Sciences > School of Education > Pedagogy, Praxis & Faith |
Publisher: | Royal Society |
University Staff: Request a correction | Enlighten Editors: Update this record