Learning Education: An ‘Educational Big Data’ approach for monitoring, steering and assessment of the process of continuous improvement of education
نویسندگان
چکیده
Changing regulations, pedagogy and didactics worldwide, have ensured that the educational system has changed severely. But the entrance of Web 2.0 and other technologies had a significant impact on the way we educate and assess our education too. The Web 2.0 applications also increase the cooperation between stakeholders in education and has led to the phenomenon ‘Learning Education’. Learning Education is a term we use for the phenomenon where educational stakeholders (i.e. teachers, students, policy-makers, partners etc.) can learn from each other in order to ultimately improve education. The developments within the Interactive Internet (Web 2.0) enabled the development of innovative and sophisticated strategies for monitoring, steering and assessing the ‘learning of education’. These developments give teachers possibilities to enhance their education with digital applications, but also to monitor, steer and assess their own behavior. This process can be done with multiple sources, for example questionnaires, interviews, panel research, but also the more innovative sources like big social data and network interactions. In this article we use the term ‘educational big data’ for these sources and use it for monitoring, steering and assessing the developments within education, according to the Plan, Do, Check, Act principle (PDCA). We specifically analyze the Check-phase and describe it with the Learning Education Check Framework (LECF). We operationalize the LECF with a Learning Education Check System (LECS), which is capable to guide itself and change those directions as well in response to changing ways and trends in education and their practices. The system supports the data-driven decision making process within the learning education processes. So, in this article we work on the LECF and propose and describe a paper-based concept of the – by educational big data driven – LECS. Besides that, we show the possibilities, reliability and validity for measuring the ‘Educational Big Data’ within an educational setting.
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