Description

Blended learning, which represents the interweaving of traditional teaching in the classroom with implementation in the online environment, is also becoming present in higher education. Learning management systems, in which e-learning takes place, store each student's interaction with the system in log files. Simultaneously with this data, various collections of educational data are kept on the student in electronic form, and surveys are also increasingly implemented in the online environment. Analyzing and mining educational data collected in various databases in order to understand the learning process and extract information that would help decisions to improve the educational process, the scientific field is called learning analytics. The purpose of the survey in the field of educational data was to improve Understanding the learning process in blended learning in higher education with the aim of identifying factors that have a significant impact on the student's work in the online classroom and during activities Identify those that can be linked to ultimate success. The empirical part presents two common approaches of learning analytics performed with freely available software tools. The calculations are based on various databases of students of the Faculty of Administration. By mining educational data, we investigated the predictive performance of different models predicting the final performance of the student based on his activity in the online classroom and predispositions (learning approach, previous performance).

Resources

Name	Format	Description	Link
	21		https://www.adp.fdv.uni-lj.si/opisi/aku19
	33		http://www.adp.fdv.uni-lj.si/podatki/aku19/aku19_vp4_sl_v1_r1.pdf
	55		https://www.adp.fdv.uni-lj.si/opisi/dostop/
	21		https://www.adp.fdv.uni-lj.si/uporabi/kako

Learning analytics of blended learning in higher education, 2019

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