April 20, 2017

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

By Konstantina Chrysafiadi, Maria Virvou

This ebook goals to supply vital information regarding adaptivity in computer-based and/or web-based academic structures. for you to make the coed modeling technique transparent, a literature overview pertaining to pupil modeling ideas and methods up to now decade is gifted in a different bankruptcy. a singular scholar modeling strategy together with fuzzy good judgment suggestions is gifted. Fuzzy common sense is used to instantly version the educational or forgetting means of a pupil. The awarded novel pupil version is answerable for monitoring cognitive country transitions of newcomers with admire to their growth or non-progress. It maximizes the effectiveness of studying and contributes, considerably, to the difference of the educational strategy to the training velocity of every person learner. hence the publication presents vital details to researchers, educators and software program builders of computer-based academic software program starting from e-learning and cellular studying structures to academic video games together with stand by myself academic purposes and clever tutoring systems.

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InfoMap’s perturbation student model involves 31 types of addition errors and 51 types of subtraction errors (Lu et al. 2005). The student model of both systems allows the reasoning of students’ errors and helps the system to expand the explanation during the feedback to the students. Moreover, Baschera and Gross (2010) have represented through the perturbation approach the student’s strength and weaknesses, in order to allow for appropriate remediation actions to adapt to students’ needs. A perturbation student model for detecting the student’s errors has been used in AUTO-COLLEGE (Tourtoglou and Virvou 2012).

The percentage of increase or decrease of the knowledge level of a domain concept that occurs due to changes on the knowledge level of another concept related with this domain concept is defined by experts of the knowledge domain. 38 2 Fuzzy Logic in Student Modeling Therefore, a FR-CN that is used to represent the knowledge domain of the learning material is a 6-tuple (C, ORD, PART, IMPACT, KL, f), where: • C = {C1, C2, … Cn} is the set of concepts of the knowledge domain. • ORD: (Ci, Cj) → {0, 1} is a matrix, which denotes that the concept Ci is delivered to the learner before the concept Cj (the value of the corresponding matrix’s cell—line i, column j—is 1).

In this way, a new approach of domain knowledge representation derives. That new approach is called Fuzzy Related-Concept Network (FR-CN). 1 Knowledge Domain Representation Using a Fuzzy Related-Concept Network A Fuzzy Related-Concepts Network is a network of concepts, which depicts, also, the knowledge dependencies that exist between the domain concepts of the learning material. Therefore, it illustrates so the structure of the learning material, as the concepts’ knowledge dependencies. Particularly, it represents the fact that the knowledge level of a domain concept is increased when the knowledge level of a related topic improves, as well as the fact that the knowledge level of a domain concept is decreased when the knowledge level of a depended topic is not satisfactory.

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