Learning analytics of blended learning in higher education, 2019
13. 05. 2022
Authors of Research: Damijana Keržič, Faculty of
Public Administration, University of Ljubljana
Year of Research: 2019
Keywords: blended
learning, organizational performance, student performance, learning analytics
Blended learning is becoming ubiquitous in higher
education. It combines traditional face-to-face teaching and online learning
that typically takes place in learning management systems which store all
student interactions with the system in their log files. In addition to this
data, education institutions store various electronic student datasets and
survey responses. Learning analytics involves collection, analysis and mining
of education data to better understand the learning process and obtain
information that can inform decision-making with regard to enhancing student
success. The purpose of the research is to improve the understanding of the
blended learning process in higher education with the aim of identifying the
factors that significantly influence student work in the online classroom, and
determining activities that are most associated with student final performance.
The empirical part presents two frequent learning analytics approaches carried
out with open source software. The calculations were based on education data
from various sources of the Faculty of Public Administration. Education data
mining examined the predictive effectiveness of various models of predicting
student final (non)performance based on their activity in the online classroom
and predispositions (learning approach, previous performance).
Keržič, D. (2022). Learning analytics of blended learning
in higher education, 2019 [Data file]. Ljubljana: Univerza v Ljubljani =
University of Ljubljana, Slovenian Social Science Data Archives (ADP). ADP -
IDNo: AKU19. https://doi.org/10.17898/ADP_AKU19_V1
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