Download Advances in Personalized Web-Based Education by Konstantina Chrysafiadi, Maria Virvou PDF

By Konstantina Chrysafiadi, Maria Virvou

This e-book goals to supply very important information regarding adaptivity in computer-based and/or web-based academic platforms. so one can make the scholar modeling approach transparent, a literature assessment touching on pupil modeling options and methods in the past decade is gifted in a different bankruptcy. a singular scholar modeling strategy together with fuzzy common sense thoughts is gifted. Fuzzy good judgment is used to immediately version the training or forgetting means of a scholar. The offered novel scholar version is liable for monitoring cognitive country transitions of freshmen with recognize to their growth or non-progress. It maximizes the effectiveness of studying and contributes, considerably, to the variation of the training method to the educational speed of every person learner. hence the booklet presents very important info to researchers, educators and software program builders of computer-based academic software program starting from e-learning and cellular studying platforms to academic video games together with stand on my own academic purposes and clever tutoring systems.

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2012) and approach representation of knowledge by emphasizing the connections and the structure (Lin 2007). 3 Fuzzy Logic for Knowledge Representation 35 concepts and the various relations that exist between its ­concepts (Azadeh et al. 2012; Song et al. 2011; Stula et al. 2010). 9). In particular, A FCM consists of nodes (N1, N2, … Nn), which represent the important elements of the mapped system, and directed arcs, which represent the causal relationships between two nodes (Ni, Nj). The directed arcs are labeled with fuzzy values (fij) in the interval [−1, 1] that show the “strength of impact” of node Ni on node Nj.

The results of this literature review are very interesting and useful for the researchers, designers and developers of educational systems and student models. 7). 7 is not 100 %. The reason for this is the fact that a system can model more than one different student characteristics. Also, many researchers have interested in modeling student’s cognitive aspects other than knowledge. 8. 8 is not 100 %. The reason for this is the fact that two different student-modeling techniques can be combined and used in the same system.

8, due to the fact that student modeling of these features is a new field of research and there are not adequate related references in literature. Moreover, the ontology-based student model has not been developed enough, since the research interest in the particular student modeling approach has started to arise recently. Chapter 2 Fuzzy Logic in Student Modeling Abstract The significant development of the e-learning systems has changed the ways of teaching and learning. In nowadays, everyone can have access to e­ -learning systems from everywhere.

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