Sofia J. Hadjileontiadou

A fuzzy logic evaluating system to support Web-based collaboration using collaborative and metacognitive data

A fuzzy logic-based expert system, namely collaboration/reflection-fuzzy inference system (C/R-FIS,) is presented. By means of interconnected fuzzy inference systems (FIS), it automatically evaluates the collaborative activity, during asynchronous, written, Web-based collaboration. This information is used for the provision of enhanced support during the collaboration. The proposed model extents the evaluation system of a Web-based collaborative tool namely Lin2k, which served as a test-bed for the C/R-FIS experimental use. The results proved the potentiality of the proposed model to significantly contribute to the enhancement of the collaborative activity.

Intuitionistic Fuzzy Logic-Based Approach of Intrinsic Motivation in CSCL Settings during Illusionary Sense of Control

We examine if the provision of illusionary sense of control that resides in the collaborators is perceived as actual control and cause intrinsic motivation towards better work within a Computer Supported Collaborative Learning (CSCL) environment. On the basis of expert knowledge, indicators are set to support intelligent decision making upon the quality of the collaboration. The fuzzy logic translates knowledge from the qualitative to the quantitative plane. It supports a model of indicators on the basis of the expert knowledge that is expressed through linguistic descriptions. However, the qualitative nature of such decisions, entail some uncertainty and hesitancy during the modeling procedure of the specific knowledge. The Intuitionistic Fuzzy Logic (IFL) enables the capture and expression of this uncertainty and hesitancy while modeling the decision making upon the quality of the collaboration, thus it extends the fuzzy logic possibilities. The efficiency of an IFL-based approach is explored through a case-study targeting the increase in the quality of the collaborative performance. The approach leads to a more minimal design of the supporting mechanisms in CSCL settings.

Fuzzy Logic-Based Modeling in Collaborative and Blended Learning

In the last decade, e-learning was dynamically growing and challenged educational organizations, learning designers, researchers and educators, around the globe, to consider new ways of delivering education programs, with the aim to provide multiple opportunities for self-directed learning, collaborative and ubiquitous learning. The emerging, innovative on-line learning technologies are nowadays used by a wide variety of learners/ students with different goals, preferences, learning habits, knowledge background, skills and capabilities. Literature suggests that the most effective way to enhance individuals’ learning experiences is to provide them learning environments with high level of personalized characteristics. In this perspective, adaptive and collaborative e-learning systems are considered as the most important environments to promote personalization of learning and improve the overall effectiveness of e-learning activities, courses and programs. At the same time, learning is a very complex process, because many dynamically interrelated components are involved. Therefore, these components demand the consideration of numerous intervening factors, such as learner’s profile, their skills and attitudes, learning goals, pedagogical strategies and learning support, educational material used etc. In this context, the authors debated on and suggested the Fuzzy Logic (FL) perspective as an alternative method to design and provide new modeling insights in personalized learning experiences, in blended and collaborative learning environments that use various technologies (Learning Management Systems, Web 2.0, Semantic Web etc.) and pedagogical approaches. The main idea is to combine numerical and linguistic data to model the qualitative aspects of students’ learning experiences, cognitive and reasoning processes, interaction and collaboration activities that result in enhanced learning outcomes, without employing precise quantitative analysis. Therefore, this book Fuzzy Logic-Based Modeling in Collaborative and Blended Learning

On Modeling the Quality of Nutrition for Healthy Ageing Using Fuzzy Cognitive Maps

Modelling dietary intake of older adults can prevent nutritional deficiencies and diet-related diseases, improving their quality of life. Towards such direction, a Fuzzy Cognitive Map (FCM)-based modelling approach that models the interdependencies between the factors that affect the Quality of Nutrition (QoN) is presented here. The proposed FCM-QoN model uses a FCM with seven input-one output concepts, i.e., five food groups of the UK Eatwell Plate, Water (H2O), and older adult’s Emotional State (EmoS), outputting the QoN. The weights incorporated in the FCM structure were drawn from an experts’ panel, via a Fuzzy Logic-based knowledge representation process. Using various levels of analysis (causalities, static/feedback cycles), the role of EmoS and H2O in the QoN was identified, along with the one of Fruits/Vegetables and Protein affecting the sustainability of effective food combinations. In general, the FCM-QoN approach has the potential to explore different dietary scenarios, helping health professionals to promote healthy ageing and providing prognostic simulations for diseases effect (such as Parkinson’s) on dietary habits, as used in the H2020 i-Prognosis project (www.i-prognosis.eu).

Towards a pragmatic modeling of learner's complex system by reflecting Boulding's typology at the affective computing space

This work reflects Bouldings Typology (BT) of the learners complex system at the space of affective computing. From this perspective, the learners emotional state is interweaved with the structural elements of his/her learning functioning (both internal and external) when placed within an educational setting. The advent of new technological achievements in the accurate acquisition of the learners affective state allows for the redesign of the ICT-based educational settings, taking into account a bilateral approach of the learners system that involves both cognitive and emotional processes, as reflected in the Valence/Arousal space. Justification of the crucial role of learners affective state in the design of an ICT-based educational setting is provided with the implications derived from an experimental case-study, referring to emotional responses to IADS-based sound stimuli presented to three age-dependent learner-groups. The proposed affective parameters define an enriched BT that could serve as a basis for structuring a new model, closer to the pragmatic nature of the learners system.

FISCMAP: A fuzzy logic-based quality of concept mapping modelling approach fostering reflective feedback

This study introduces a new model, namely FISCMAP, that explores the fuzzy logic constructs within a computer-based concept mapping environment, involving modeling techniques as vehicles to improve the intelligence of an online learning environment. From this perspective, eight CmapTool measurements are considered to form inputs to a five-level fuzzy inference system equipped with 115 experts fuzzy rules. The CmapTool data were drawn from a b-learning environment related to a Masters course offered by a Higher Education Institution, involving 20 Masters students. Experimental results have shown that the use of the proposed FISCMAP scheme for the evaluation of users Quality of Concept Map (QoCM), by considering constructive CM variables (metrics), can increase the accuracy and validity of the intelligent system under consideration.

On modeling children's non-verbal interactions during computer mediated music composition: a case study in primary school peers

The proposed paper aims to model the non-verbal interactions that occur during a computer-mediated music composition process between pupils in primary school within a collaborative framework. The socio-cultural approach, drawn from Vygotskys theoretical context, is being further developed and some of its aspects are outlined and used as a framework to further understand the collaborative processes that occur during collaborative learning. The latter is achieved by identifying effective peers verbal and non-verbal interactions in a collaborative computer-based music composition environment (CCMCE).The present paper aims to explore and model childrens patterns of body language signs which contribute to measure peers active and passive collaborative learning in CCMCE. Experimental results from a case study in a primary state school in Greece promise to yield important cues for peers thinking, concentration and mental processing that will be useful to anyone engaged in examining childrens computer-mediated collaborative interactions.

Osteoporotic spinal burst fracture in a young adult as first presentation of systemic mastocytosis.

Osteoporotic vertebral fractures are uncommon in young adults and usually indicate an underlying disease. Systemic mastocytosis is a myeloproliferative neoplasm, which can be associated with osteoporosis. A previously healthy 30-year-old man presented with an L4 burst fracture after lifting a heavy object. He was operated with laminectomy and posterior lumbar instrumentation. During surgery, abnormally soft bone was noted. Postoperatively, osteoporosis was confirmed with measurement of bone mineral density. Further investigation revealed elevated serum tryptase levels while bone marrow biopsy findings showed systemic mastocytosis. He was also tested positive for D816V KIT mutation. Treatment with biphosphonates and interferon was initiated. No extraskeletal involvement was noted up to the last checkup, 18 months after the first presentation. Abrupt vertebral fractures in apparently healthy young individuals should raise the suspicion of an underlying pathology. Prompt identification and treatment of systemic mastocytosis is crucial in order to avoid unexpected sequelae.

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/).

Exploring the Potential of Computer-Based Concept Mapping Under Self-and Collaborative Mode Within Emerging Learning Environments

According to Novak (2010), a concept map (CM) is a (hierarchical) network comprised of concept terms (nodes) and directed lines linking pair of nodes; at the same time, CMs provide a window into students’ mind, reflecting students’ knowledge structures. Seen as an educational tool, the CM encourages students to organize and make explicit their knowledge. CMs are considered effective as teaching and learning tools that assist the development of conceptual knowledge, allowing visual observation of relationships and connections between multiple areas and pieces of information (Novak & Gowin, 1984). Moreover, the ability to recognize connections between different pieces of information or aspects of a problem facilitates problem-based learning (PBL) (Schaal, 2010). The latter assists the development of higher-order thinking skills, helping students to become independent, self-directed learners who appropriately respond to situations in a logical and reasonable manner (Savery & Duffy, 1995). Taking into account the previous approaches, a CM can be studied from different perspectives, for instance: The creator/s perspective. The construction of a CM can be performed either in individual or in collaborative mode. Several studies have investigated the use/potential of CMs as supporting processes of self-knowledge management (Conceicao, Desnoyers, & Baldor, 2008; Tergan, 2005; Tergan, Keller, Graber, & Neumann, 2006; Vodovozov & Raud, 2015). Other authors, on the other hand, have explored the potential of collaborative CMs to facilitate knowledge construction as a study/collaborative tool (Gao, Thomson, & Shen, 2013; Koc, 2012; Lee, 2013; Lin, Wong, & Shao, 2012; Molinari, 2015; Rafaeli & Kent, 2015). Although originally developed to assist individual learners, collaborative use of CMs emphasizes brainstorming among group members, leading to visualization of new ideas and synthesis of unique concepts (Novak, 2010), requiring communication/negotiation processes, which guide learners to grow in their conceptual understanding (Kwon & Cifuentes, 2009). The quality perspective. The quality of a CM (QoCM) can be defined through quantitative/qualitative metrics in different spaces, e.g., on the basis of the correct propositions that it includes, and/or on the characteristics that concern its construct as a network or even its construction procedure. Upon the evaluation of such qualities, appropriate feedback could be provided. In general, the CM quality refers to the amount, depth, and breadth of information and the number of connections made among different items included in it (Gurupur, Jain, & Rudraraju, 2015). The technology perspective. Concept mapping has been described as a technique that can increase student’s learning in the traditional classroom (Alvarez-Montero, Saenz-Perez, & Vaquero-Sanchez, 2015; Novak & Canas, 2008). However, several studies have clearly demonstrated the efficacy of computer and/or online concept mapping tools/techniques in supporting the learning process (Kwon & Cifuentes, 2007; Omar, 2015). The teaching-learning environment perspective. The technological possibilities added flexibility that allows the integration of the CM in blended (b-) learning experiences (Adams Becker et al., 2017). These include face-to-face (F2F) and online modalities that are formed through the mediation of Information and Communications Technologies (ICTs), rather than being completely online or F2F (Michinov & Michinov, 2008). So far, limited efforts have been made to understand the development and use of theory in the particular domain of b-learning research (Drysdale, Graham, Spring, & Halverson, 2013; Graham, 2013). The concept of b-learning is embedded in the idea that learning is not just a onetime episode but also a continuous/dynamic learning process. Blending different delivery modes/tools can be seen as an imaginative solution in educational contexts, since it has the potential to balance out and optimize the learning development (Dias, Diniz, & Hadjileontiadis, 2014). The computer-based learning environments (CBLEs) that can be integrated in b-learning assist individuals in learning, using multiple representations of information for a specific educational purpose (Ifenthaler, 2012). CBLEs frequently confront learners with a number of support devices (also referred as tools) in order to enhance learning, to help learners in their learning, and to provide a learning opportunity (Collazo, Elen, & Clarebout, 2015; Garcia-Alvarez, Suarez Alvarez, & Quiroga Garcia, 2014). However, according to Bates and Sangra (2011): “Teachers must decide which tools are most likely to suit the particular teaching approach” (pp. 44–46).