TY - GEN
T1 - FuzzyQoI-Based Estimation of the Quality of Interaction in Online Learning Amid Covid-19
T2 - 2nd International Conference on Technology and Innovation in Learning, Teaching and Education, TECH-EDU 2020
AU - Dias, Sofia B.
AU - Hadjileontiadou, Sofia J.
AU - Alves Diniz, J.
AU - Hadjileontiadis, Leontios J.
N1 - Funding Information:
The authors would like to thank the eLearning Administrators of AUTH for their assistance in LMS Moodle access.
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - In the beginning of 2020, the coronavirus (Covid-19) pandemic has raised significant challenges for the Higher Education Institutions (HEIs) worldwide. Due to Covid-19 outbreak, HEIs were forced to close due to social lockdown, placing online teaching-learning environments/modalities to the foreground of the educational settings. In an effort to examine how this ‘new normal’ has affected users’ Quality of Interaction (QoI) within the Learning Management System (LMS) Moodle, a modeling approach based on fuzzy logic (FuzzyQoI), was used here and applied to LMS Moodle data, drawn from an undergraduate discipline, offered by a public Greek HEI during the Covid-19 period. The results have shown the ability of the FuzzyQoI model to express the time-depended dynamics of the users’ QoI and associate it with the societal effects of Covid-19. Clearly, these findings shed light upon the way users interact with a LMS online learning when societal disruptors, such as Covid-19, come in to play, informing HEIs’ policy makers for monitoring and re-examining online (teaching-learning) practices.
AB - In the beginning of 2020, the coronavirus (Covid-19) pandemic has raised significant challenges for the Higher Education Institutions (HEIs) worldwide. Due to Covid-19 outbreak, HEIs were forced to close due to social lockdown, placing online teaching-learning environments/modalities to the foreground of the educational settings. In an effort to examine how this ‘new normal’ has affected users’ Quality of Interaction (QoI) within the Learning Management System (LMS) Moodle, a modeling approach based on fuzzy logic (FuzzyQoI), was used here and applied to LMS Moodle data, drawn from an undergraduate discipline, offered by a public Greek HEI during the Covid-19 period. The results have shown the ability of the FuzzyQoI model to express the time-depended dynamics of the users’ QoI and associate it with the societal effects of Covid-19. Clearly, these findings shed light upon the way users interact with a LMS online learning when societal disruptors, such as Covid-19, come in to play, informing HEIs’ policy makers for monitoring and re-examining online (teaching-learning) practices.
KW - Covid-19
KW - Fuzzy logic
KW - FuzzyQoI
KW - Higher education institutions
KW - Moodle learning management systems
KW - Online learning
KW - Quality of interaction
KW - Societal disruptors
UR - http://www.scopus.com/inward/record.url?scp=85105926189&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-73988-1_19
DO - 10.1007/978-3-030-73988-1_19
M3 - Conference contribution
AN - SCOPUS:85105926189
SN - 9783030739874
T3 - Communications in Computer and Information Science
SP - 249
EP - 262
BT - Technology and Innovation in Learning, Teaching and Education - Second International Conference, TECH-EDU 2020, Proceedings
A2 - Reis, Arsénio
A2 - Barroso, João
A2 - Lopes, J. Bernardino
A2 - Mikropoulos, Tassos
A2 - Fan, Chih-Wen
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 2 December 2020 through 4 December 2020
ER -