In Work Package 8, the prototype ENLIVEN IDSS has been extended to retrieve similar interventions via four key attributes, to add new interventions, to conduct statistical analysis, and to facilitate machine learning in future exploitation. The conceptual and methodological issues on developing the IDSS, and results of statistical analysis and data mining are presented. To fully exploit the potential of machine learning for automated knowledge discovery and meta-analysis, it is crucial that sufficient data is available with the most typical objects in the interventions.
In future exploitations, the unified framework in the IDSS could be adopted and reused to archive other interventions at European Commission and in Education research. The knowledge base in the IDSS is open and accessible to researchers and practitioners to support consistent analysis of interventions across European countries. The source code of the IDSS is accessible publicly to support future exploitation on computer-aided intelligent systems as more interventions become available, and are acquired, cleaned and processed; consistent evaluation approaches are available from the literature; and enough interventions cases have been documented in a consistent format in the literature.
Horizon 2020 - ENLIVEN 