TY - GEN
T1 - Enhancing blended environments through fuzzy cognitive mapping of LMS users’ quality of interaction
T2 - 9th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2015 Held as Part of 17th International Conference on Human-Computer Interaction, HCI International 2015
AU - Dias, Sofia B.
AU - Hadjileontiadou, Sofia J.
AU - Diniz, José Alves
AU - Hadjileontiadis, Leontios J.
N1 - Funding Information:
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).
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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/).
AB - 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/).
KW - Blended learning scenarios
KW - Fuzzy Cognitive Maps (FCMs)
KW - I-Treasures
KW - Moodle learning management system
KW - Quality of Interaction (QoI)
KW - Rare and contemporary dance
UR - http://www.scopus.com/inward/record.url?scp=84947274226&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-20684-4_4
DO - 10.1007/978-3-319-20684-4_4
M3 - Conference contribution
AN - SCOPUS:84947274226
SN - 9783319206837
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 31
EP - 42
BT - Universal Access in Human-Computer Interaction
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
A2 - Stephanidis, Constantine
PB - Springer Verlag
Y2 - 2 August 2015 through 7 August 2015
ER -