RECENT SOFT COMPUTING APPROACHES IN DIGITAL LEARNING OBJECT EVALUATION
Author(s): Florin Popentiu -Vladicescu,Grigore Albeanu / Language(s): English
/ Issue: 02/2012
Keywords: Digital learning objects; multi-criteria decision-making; intuitionistic fuzzy approaches
Digital learning objects are powerful units for building learning, education or training
materials based on ICT recent developments. Not only text and photos, but also audio, video, and
simulation units are used to build high quality e-lessons (available online), or blended learning
resources. There are a large plethora of types of digital resources used in e-Learning content
development, and for every category a particular set of criteria are used by experts (mainly e-education
experts) to recommend some optimum configuration. Content quality (including presentation design),
standards compliance (mainly for portability reason), learning goal alignment (accreditation goals),
accessibility and interaction usability, and reusability are common criteria for every type of digital
learning object. Specific aspects concerning text (font size/colour), images (resolution, multilevel
approaches, animation), audio (resolution), video (resolution), and the general presentation including
the quality of characters' voice are necessary to be taken into consideration in order to select the best
quality digital learning objects in order to obtain an attractive, motivational, and efficient (not only for
the teacher, but most important for the student) meeting with valuable pieces of knowledge for life. This
paper describes the usage of some soft computing techniques for the evaluation of DLOs, including
intuitionistic fuzzy multi-criteria approaches. Firstly, the multi-criteria decision-making methods are
briefly reviewed combining the general decision-making process. There are many approaches in soft
computing decision-making: neural networks, evolutionary optimisation, fuzzy computing, etc. The
multi-criteria approaches under consideration are based on fuzzy and intuitionistic fuzzy numbers
(triangular, trapezoidal, etc), distance evaluation, and multi-criteria decision strategies. Final
considerations on applying such methodologies for digital learning objects' evaluation are presented.
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