Authors:
Sofia B. Dias
1
;
Sofia J. Hadjileontiadou
2
;
José A. Diniz
1
and
Leontios J. Hadjileontiaids
3
Affiliations:
1
University of Lisbon, Portugal
;
2
Hellenic Open University, Greece
;
3
Aristotle University of Thessaloniki, Greece
Keyword(s):
Cloud Learning Environment, Fuzzy Logic/Ontologies, Hybrid Modelling, i-Treasures, Online Learning Environment (OLE), Quality of Collaboration (QoC), Quality of Interaction (QoI), Semantic Web 3.0.
Related
Ontology
Subjects/Areas/Topics:
Blended Learning
;
Collaborative Learning
;
Computer-Supported Education
;
Information Technologies Supporting Learning
;
Learning/Teaching Methodologies and Assessment
;
Metrics and Performance Measurement
;
Social Context and Learning Environments
Abstract:
As a decision support tool, a hybrid modelling can offer the ability to better understand the dynamics of a
particular ecosystem. This paper proposes a hybrid approach that may serve as a means to synthesize/represent
knowledge obtained from the data, in order to explore online learning environment (OLE) states, based on
different scenarios. The potentiality of the quality of collaboration (QoC) within an Internet-based computer-supported
collaborative learning environment and the quality of interaction (QoI) with a learning management
system (LMS), both involving fuzzy logic-based modeling, as vehicles to improve the personalization and
intelligence of an OLE is explored. In this approach, a novel framework could be established, when bridging
the fields of blended- and collaborative-learning into an enhanced educational environment. The combined
measures (i.e., QoC, QoI) can form the basis for a more realistic approach of OLEs within the concept of
semantic Web and the asso
ciated Web 3.0 features, as they effectively capture the behaviour of the
stakeholders involved in the context of Higher Education. Finally, a potential case study of the examined
hybrid modelling (FuzzyQoC/I), referring to the “i-Treasures” European FP7 Programme, is discussed, to
explore its functionality/applicability under pragmatic learning scenarios, serving as a proof of concept.
(More)