An Associative Based Approach to Analyzing an Online Learning Environment
Author(s) -
Bahareh Azarnoush,
Jennifer Bekki,
Bianca L. Bernstein,
George C. Runger
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--19168
Subject(s) - computer science , session (web analytics) , world wide web , set (abstract data type) , web page , artificial intelligence , programming language
Recent years have shown an increase in both in the number and use of online educational learning environments. Correspondingly, there is a greater availability of rich data sets that describe both the learners themselves and their interactions with the online learning environment. In this paper, we demonstrate the use of a data mining tool, association analysis, to analyze this data. We demonstrate its applicability in understanding how learners use a particular online learning environment and for the identification of learner interactions with the environments that are associated with particular learning outcomes. The methodology is first described and then is demonstrated as a case study through its application to the CareerWISE online learning environment.
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