scholarly journals NEW MCEQLS TFN METHOD FOR EVALUATING QUALITY AND REUSABILITY OF LEARNING OBJECTS

2013 ◽  
Vol 19 (4) ◽  
pp. 706-723 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Silvija Serikovienė
Keyword(s):  
Decision Analysis ◽  
Fuzzy Numbers ◽  
Quality Criteria ◽  
Learning Objects ◽  
Multiple Criteria ◽  
Quality Model ◽  
Research Results ◽  
Analysis Process ◽  
Multiple Criteria Evaluation ◽  
Learning Software

The aim of the paper is to present a new simple to use and efficient MCEQLS (Multiple Criteria Evaluation of the Quality of Learning Software) TFN (Trapezoidal Fuzzy Numbers) method for the expert evaluation of the quality and reusability of learning objects (LOs). MCEQLS and TFN methods are analysed, improved, and practically applied to present the decision analysis process for selecting LOs suitable to reuse in different pedagogical situations and in different education systems. The research results are implemented in eQNet – a three-year strategic pan-European project focused on reusability of LOs. A novel method of consecutive application of Fuzzy Numbers theory to establish the weights of LOs quality criteria and MCEQLS approach to establish final evaluation results are explored in more detail. A number of multiple criteria decision analysis principles are applied to create a comprehensive quality model (criteria system) for evaluating the quality and reusability of LOs. Several practical examples of LOs evaluated against the proposed MCEQLS TFN method are presented in the paper. The research results have shown that the proposed method is quite objective, exact, simple to use, and efficient for selecting qualitative reusable LOs alternatives in the market.

Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects

2013 ◽  
pp. 136-150
Author(s):  
Eugenijus Kurilovas ◽  
Irina Vinogradova ◽  
Silvija Serikoviene
Keyword(s):  
Decision Analysis ◽  
Quality Criteria ◽  
Learning Objects ◽  
Scientific Models ◽  
Expert Evaluation ◽  
Quality Of Learning ◽  
Technological Quality ◽  
Optimisation Methods ◽  
Quality Optimisation

This paper analyses and presents the new scientific models and methods for the expert evaluation of quality of learning objects (LOs) paying special attention to LOs reusability level. Currently all existing approaches in the area are quite subjective and depend only on the experience of the decision-makers. The authors analyse several scientific methods and principles to minimise the subjectivity level in the expert evaluation of LOs quality. They are: (a) the principles of multi-criteria decision analysis for identification of quality criteria, (b) technological quality criteria classification principle, (c) fuzzy group decision making theory to obtain evaluation measures, (d) normalisation of the weights of criteria, and (e) scalarisation method for LOs quality optimisation. The authors demonstrate that the complex application of these approaches could significantly improve the quality of the expert evaluation of LOs and noticeably reduce the level of the expert evaluation subjectivity. The paper also presents the example of practical application of these approaches for evaluation of LOs for Mathematics subject.

Technological Evaluation and Optimization of E-Learning Systems Components

2011 ◽  
pp. 150-173 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Valentina Dagiene
Keyword(s):  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Learning Objects ◽  
Learning Systems ◽  
Main Research ◽  
Evaluation Models ◽  
E Learning ◽  
Multiple Criteria Evaluation ◽  
Technological Evaluation ◽  
Learning Software

The main research objective of the chapter is to provide an analysis of the technological quality evaluation models and make a proposal for a method suitable for the multiple criteria evaluation (decision making) and optimization of the components of e-learning systems (i.e. learning software), including Learning Objects, Learning Object Repositories, and Virtual Learning Environments. Both the learning software ‘internal quality’ and ‘quality in use’ technological evaluation criteria are analyzed in the chapter and are incorporated into comprehensive quality evaluation models. The learning software quality evaluation criteria are further investigated in terms of their optimal parameters, and an additive utility function based on experts’ judgements, including multicriteria evaluation, numerical ratings, and weights, is applied to optimize the learning software according to particular learners’ needs.

SIGNED DISTANCED-BASED TOPSIS METHOD FOR MULTIPLE CRITERIA DECISION ANALYSIS BASED ON GENERALIZED INTERVAL-VALUED FUZZY NUMBERS

2011 ◽  
Vol 10 (06) ◽  
pp. 1131-1159 ◽  
Author(s):  
TING-YU CHEN
Keyword(s):  
Decision Analysis ◽  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Multiple Criteria Decision Analysis ◽  
Topsis Method ◽  
Order Preference ◽  
Priority Order ◽  
Interval Valued

The theory of interval valued fuzzy sets is very valuable for modeling impressions of decision makers. In addition, it gives ability to quantify the ambiguous nature of subjective judgments in an easy way. In this paper, by extending the technique for order preference by similarity to ideal solution (TOPSIS), it is proposed a useful method based on generalized interval valued trapezoidal fuzzy numbers (GITrFNs) for solving multiple criteria decision analysis (MCDA) problems. In view of complexity in handling sophisticated data of GITrFNs, this paper employs the concept of signed distances to establish a simple and effective MCDA method based on the main structure of TOPSIS. An algorithm based on TOPSIS method is established to determine the priority order of given alternatives by using properties of signed distances. Finally, the feasibility of the proposed method is illustrated by a practical example of supplier selection.

scholarly journals Application of learning scenarios quality evaluation methods

2011 ◽  
Vol 52 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Inga Žilinskienė
Keyword(s):  
Quality Evaluation ◽  
Evaluation Methods ◽  
Multiple Criteria ◽  
Multiple Criteria Analysis ◽  
Quality Model ◽  
Research Results ◽  
Quality Of Learning ◽  
Learning Scenarios

The paper is aimed to analyse the problems of evaluation of quality of learning scenarios. Multiple criteria analysis principles are applied to form learning scenarios quality model. Several alternativesof learning scenarios that are widely used in Europe are analysed in the paper. These alternatives are evaluated with the help of the created quality model and application of triangular and trapezoidalfuzzy numbers methods. Research results show that both these methods are applicable in practice while evaluating quality of learning scenarios alternatives, and their application shows in principlesimilar results while comparing different alternatives of learning scenarios. 

scholarly journals Evaluation of multiple criteria quality of mathematics learning objects in eQNet project

2010 ◽  
Vol 51 ◽  
Author(s):  
Silvija Sėrikovienė ◽  
Eugenijus Kurilovas
Keyword(s):  
Mathematics Learning ◽  
Quality Criteria ◽  
Learning Objects ◽  
Multiple Criteria ◽  
Digital Learning ◽  
Criteria Weights ◽  
Technological Quality ◽  
Digital Learning Objects ◽  
Fuzzy Group Decision Making

The paper is aimed to analyse the application of several scientific approaches, methods, and principles for evaluation of quality of digital learning objects (LOs) for Mathematics subject. The authors analyse the following approaches to minimise subjectivity level in expert evaluation of LOs quality, namely: (1) principles of multiple criteria decision analysis for identification of quality criteria, (2) technological quality criteria classification principle, (3) fuzzy group decision making theory toobtain evaluation measures, (4) normalisation requirement for criteria weights, and (5) scalarisation method for LOs quality evaluation. The applied approaches have been used practically for evaluation of LOs while implementing European Lifelong Learning programme’s eQNet project in Lithuanian comprehensive schools in winter and spring 2010.

On e-Textbooks Quality Model and Evaluation Methodology

2013 ◽  
Vol 4 (3) ◽  
pp. 66-78 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Silvija Serikoviene
Keyword(s):  
Quality Evaluation ◽  
Evaluation Method ◽  
Quality Criteria ◽  
Learning Objects ◽  
Evaluation Methodology ◽  
Educational Institutions ◽  
Learning Material ◽  
Quality Model ◽  
Policy Makers ◽  
Relevant Education

The paper aims to analyse and propose e-textbooks and other learning objects (LOs) quality evaluation methodology, i.e., quality model, and simple and effective expert evaluation methods, thus improving solution of educational tasks using informatics engineering methods. Qualitative learning material is one of the main factors of learning quality. Therefore, evaluation of e-textbooks and other LOs quality is one of the most relevant education problems. The problem is relevant for all participants of the educational sector – for educational institutions (e.g. schools) that have to select qualitative learning material for their needs, for education policy makers who need clear quality criteria while implementing e-textbooks and other LOs tenders, for authors of learning material (e.g. publishers) who need to know quality requirements to create e-textbooks and other LOs etc. It is obvious that some e-textbooks and other LOs could be very qualitative against some quality criteria, and the others – against the other criteria, and vice versa. Therefore, e-textbooks and other LOs quality evaluation is a typical case where one should apply multiple criteria decision analysis (MCDA) theory. In the work, MCDA principles are applied to create an objective rank of LOs alternatives according to their quality, and to evaluate each alternative’s quality against ”ideal” quality. In the work, e-textbooks and other LOs reusability and quality criteria system (i.e. model) is presented, as well as created expert quality evaluation method based on fuzzy numbers theory.

MCEQLS Approach in Multi-Criteria Evaluation of Quality of Learning Repositories

2013 ◽  
pp. 96-117 ◽  
Author(s):  
Eugenijus Kurilovas
Keyword(s):  
User Interfaces ◽  
Large Scale ◽  
Optimization Methods ◽  
Multiple Criteria ◽  
Quality Model ◽  
Multi Criteria Evaluation ◽  
Quality Of Learning ◽  
Learning Software ◽  
Evaluation Of Learning

This chapter analyzes the quality of XML learning object repositories. Special attention is paid to the models and methods to evaluate the quality of learning repositories. Multiple criteria decision analysis and optimization methods are explored to be applied for evaluating the quality of learning repositories. This chapter also presents the results of several large-scale projects co-funded by EU research programs that have been implemented in the area of learning repositories. Learning repositories’ technological quality model (system of criteria) and novel comprehensive model for evaluating the quality of user interfaces of learning repositories are presented in more detail. The general MCEQLS (Multiple Criteria Evaluation of Learning Software) approach is presented in this chapter. It is shown that the MCEQLS approach is suitable for evaluating the quality of learning repositories. The author believes that research results presented in the chapter will be useful for all educational stakeholder groups interested in developing learning repositories.

scholarly journals An Interval-Valued Pythagorean Fuzzy Compromise Approach with Correlation-Based Closeness Indices for Multiple-Criteria Decision Analysis of Bridge Construction Methods

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-29 ◽  
Author(s):  
Ting-Yu Chen
Keyword(s):  
Decision Analysis ◽  
Correlation Coefficients ◽  
Multiple Criteria ◽  
Multiple Criteria Decision Analysis ◽  
Bridge Construction ◽  
Construction Methods ◽  
New Concepts ◽  
Decision Making Processes ◽  
Multiple Criteria Evaluation ◽  
Interval Valued

The purpose of this paper is to develop a novel compromise approach using correlation-based closeness indices for addressing multiple-criteria decision analysis (MCDA) problems of bridge construction methods under complex uncertainty based on interval-valued Pythagorean fuzzy (IVPF) sets. The assessment of bridge construction methods requires the consideration of multiple alternatives and conflicting tangible and intangible criteria in intricate and varied circumstances. The concept of IVPF sets is capable of handling imprecise and ambiguous information and managing complex uncertainty in real-world applications. Inspired by useful ideas concerning information energies, correlations, and correlation coefficients, this paper constructs new concepts of correlation-based closeness indices for IVPF characteristics and investigates their desirable properties. These indices can be utilized to achieve anchored judgments in decision-making processes and to reflect a certain balance between connections with positive and negative ideal points of reference. Moreover, these indices can fully consider the amount of information associated with higher degrees of uncertainty and effectively fuse imprecise and ambiguous evaluative ratings to construct a meaningful comparison approach. By using the correlation-based closeness index, this paper establishes effective algorithmic procedures of the proposed IVPF compromise approach for conducting multiple-criteria evaluation tasks within IVPF environments. The proposed methodology is implemented in a practical problem of selecting a suitable bridge construction method to demonstrate its feasibility and applicability. The practicality and effectiveness of the proposed methodology are verified through a comparative analysis with well-known compromise methods and other relevant nonstandard fuzzy models.

Application of Multiple Criteria Decision Analysis and Optimisation Methods in Evaluation of Quality of Learning Objects

2011 ◽  
Vol 1 (4) ◽  
pp. 62-76 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Irina Vinogradova ◽  
Silvija Serikoviene
Keyword(s):  
Decision Analysis ◽  
Quality Criteria ◽  
Learning Objects ◽  
Scientific Models ◽  
Expert Evaluation ◽  
Quality Of Learning ◽  
Optimisation Methods ◽  
Quality Optimisation ◽  
Fuzzy Group Decision Making

This paper analyses and presents the new scientific models and methods for the expert evaluation of quality of learning objects (LOs) paying special attention to LOs reusability level. Currently all existing approaches in the area are quite subjective and depend only on the experience of the decision-makers. The authors analyse several scientific methods and principles to minimise the subjectivity level in the expert evaluation of LOs quality. They are: (a) the principles of multi-criteria decision analysis for identification of quality criteria, (b) technological quality criteria classification principle, (c) fuzzy group decision making theory to obtain evaluation measures, (d) normalisation of the weights of criteria, and (e) scalarisation method for LOs quality optimisation. The authors demonstrate that the complex application of these approaches could significantly improve the quality of the expert evaluation of LOs and noticeably reduce the level of the expert evaluation subjectivity. The paper also presents the example of practical application of these approaches for evaluation of LOs for Mathematics subject.

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