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Purposes of Big Data in Higher Education
Some of the major purposes of Big Data education are listed below, Can you think of any other?
GOAL SETTING
This can help leaders in setting the goals for their organization, for example, with respect to educational quality indicators, set by themselves or the government. They can use big data for setting goals at the different levels of the system (Romero/Ventura 2010). What are important goals at the level of the school, what are important classroom level goals, and what are student level goals? These goals can pertain to cognitive goals, such asstudent achievement results, but also to non-cognitive goals, such as well-being and the socio-emotional development of students.
MONITORING
School leaders can also use big data for monitoring purposes, for example, to monitor to which extent the goals set are being accomplished. For this purpose, dashboards are becoming increasingly popular in educational institutions. User friendly software tools, such as Tableau, are available and facilitate the development and support of personalized dashboards that bring together information from various sources and administrative systems.
IDENTIFY & SOLVE PROBLEMS
Based on continuous monitoring, institutions also can identify and solve problems. Big data can assist in the analysis of problems and the causes of these problems (Manyika et al. 2011). The problem can be defined in a measurable manner (e.g., these schools or students are underperforming, their average score is x, and our goal is y), and big data can be used to identify the root causes of underperformance, which can help in solving these problems. In this sense, big data can also assist in decision-making to improve the quality of an educational organization (Manyika et al. 2011).
LEARNING ANALYTICS IN HIGHER EDUCATION
Here are a few tools used in higher education:
ONTASK
Ontask aims to improve students’ academic experience through the on-time delivery of personalized feedback throughout course participation.
THREADZ
Threadz is a discussion visualization tool that develops network visualizations such as graphs and statistics to allow you to ‘see’ who is communicating with whom in your course.
Higher Education Projects in Learning Analytics
In recent years there has been a big push for learning institutions to interpret students data with the information received so that instructions can be personalized to meet learner needs. Retention and support for students 'at risk' are some of the first places where learning analytics are applied. (Hover over the icons below to read more)
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