A causal loop approach to uncover interrelationship of student online interaction and engagement and their contributing factors
Author(s) -
Afrooz Purarjomandlangrudi,
David Chen
Publication year - 2019
Publication title -
research in learning technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 26
eISSN - 2156-7077
pISSN - 2156-7069
DOI - 10.25304/rlt.v27.2058
Subject(s) - set (abstract data type) , thematic analysis , causal loop diagram , online discussion , online learning , causal model , computer science , online participation , loop (graph theory) , psychology , mathematics education , qualitative research , world wide web , the internet , sociology , system dynamics , artificial intelligence , medicine , social science , pathology , programming language , mathematics , combinatorics
Advances in technology reinforce the imperative to obtain further insight into the factors that impact online interaction in online environments. Even though past researchers have extracted factors impacting student online interaction and engagement, there is a lack of research that uncovers the dynamics of these relationships and investigates the impact of a comprehensive set of factors on student online interaction at the same time. Thus, this paper seeks to fill this gap by employing a causal loop approach to uncover the interrelationships of these factors that contribute to a positive impact on students’ learning outcomes, and to evaluate satisfaction and engagement in online courses by focussing on students’ online interaction. To this end, a rich qualitative data set was obtained from an online focus group consisting of students from a large online course, and a thematic analysis was conducted resulting in identifying different factors that played a role in the topic under study. More importantly, causal loop modelling was used to model these factors and their causal interrelationships.
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