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Learning analytics and educational data mining has greatly supported the process of assessing and improving the quality of education. While learning analytics has a longer development cycle, educational data mining suffers from the inadequacy of data captured through learning processes. The data captured from examination process can be suitably extended to perform some descriptive and predictive analytics. This paper demonstrates the possibility of actionable analytics on the data collected from talent search examination process by adding to it some data pre-processing steps. The analytics provides some insight into the learner's characteristics and demonstrates how analytics on examination data can be a major support for bringing the quality in education field.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |