Enhancing Blended Environments Through Fuzzy Cognitive Mapping of LMS Users’ Quality of Interaction: The Rare and Contemporary Dance Paradigms
Nowadays, higher education institutions (HEIs) are facing the need of constant monitoring of users’ interaction with Learning Management Systems (LMSs), in order to identify key areas for potential improvement. In fact, LMSs under blended (b-) learning mode can efficiently support online learning environments (OLEs) at HEIs. An important challenge would be to provide flexible solutions, where intelligent models could contribute, involving artificial intelligence and incertitude modelling, e.g., via Fuzzy Logic (FL). This study addresses the hypothesis that the structural characteristics of a Fuzzy Cognitive Map (FCM) can efficiently model the way LMS users interact with it, by estimating their Quality of Interaction (QoI) within a b-learning context. This work proposes the FCM-QoI model, consisting of 14 input-one output concepts, dependences and trends, considering one academic year of two dance disciplines (i.e., the Rare and Contemporary Dances) of the LMS Moodle use. The experimental results reveal that the proposed FCM-QoI model can provide concepts interconnection and causal dependencies representation of Moodle LMS users’ QoI, helping educators of HEIs to holistically visualize, understand and assess stakeholders’ needs. In general, the results presented here could shed light upon designing aspects of educational scenarios, but also to those involved in cultural preservation and exploitation initiatives, such as the i-Treasures project (http://i-treasures.eu/).
KeywordsBlended learning scenarios Moodle learning management system Fuzzy Cognitive Maps (FCMs) Quality of Interaction (QoI) Rare and contemporary dance i-Treasures
This work has received funding from the EU FP7-ICT-2011-9-ICT-2011.8.2, grant agreement N°600676: ‘i-Treasures’ Project (www.i-treasures.eu). Dr. Dias acknowledges the financial support by the Foundation for Science and Technology (FCT, Portugal) (Postdoctoral Grant SFRH/BPD/496004/20) and the Interdisciplinary Centre for the Study of Human Performance (CIPER, Portugal).
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