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Li, Kam-Cheong; Wong, Billy Tak-Ming – Interactive Technology and Smart Education, 2020
Purpose: This paper aims to present a review of case studies on the use of learning analytics in Science, Technology, Engineering, (Arts), and Mathematics (or STE[A]M) education. It covers the features and trends of learning analytics practices as revealed in case studies. Design/methodology/approach: A total of 34 case studies published from 2013…
Descriptors: Learning Analytics, Art Education, STEM Education, Adoption (Ideas)
Norqvist, Lars; Leffler, Eva – International Review of Education, 2017
This article offers insights into the practices of a non-formal education programme for youth provided by the European Union (EU). It takes a qualitative approach and is based on a case study of the European Voluntary Service (EVS). Data were collected during individual and focus group interviews with learners (the EVS volunteers), decision takers…
Descriptors: Foreign Countries, Informal Education, Educational Practices, Youth
Vossensteyn, Hans; Kolster, Renze; Kaiser, Frans; File, Jon; Huisman, Jeroen; Seeber, Marco; Vukasovic, Martina; Muehleck, Kai; Gwosc, Christoph – European Commission, 2018
Europe's knowledge economies need high-level skills, the capacity to innovate and to support democratic societies. In this perspective, the main objective of this study is to provide a comprehensive analysis of the relevance of higher education and how this is promoted in various countries in Europe and beyond. The evidence, conclusions and…
Descriptors: Foreign Countries, Relevance (Education), Higher Education, Definitions
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection