Usability Evaluation Approach of Educational Resources Software Using Mixed Intelligent Optimization

Jiaze Sun

doi:10.1155/2017/2926904

Abstract

Aiming at the problems of strong subjectivity and uncertain fuzziness of attribute weights in the software usability evaluation approach, an evaluation approach based on mixed intelligent optimization was proposed, which combines subjective and objective methods to measure software usability for educational resources software. Firstly, the usability evaluation index system of educational resources software was established, and the basic probability assignment was generated by the interval method from the historical sample data. Then the weight optimization problem was adapted to the smooth optimization problem by the maximum entropy function method, and the hybrid social cognitive optimization (HSCO) algorithm was introduced to solve the optimal weights of evidence. Finally, the software usability level was fused by DS evidence theory. The experimental results show that the educational resources software usability evaluation approach can objectively and truly reflect the usability of the software. It provides an efficient way to evaluate the usability of the software.

Highlights

In the era of user-centered product design, a good user experience is the direct way to keep the user’s viscosity, for the usability is an important software feature
This paper proposes a usability evaluation index system for assessing the availability of educational resources software, which combines the characteristics of educational resources software and target user characteristics
To verify the effect of proposed software usability evaluation model for educational resources software, we used the proposed hybrid intelligent optimization model to evaluate the usability of the convenient educational resources management platform, which was developed by our software team in 2015

Summary

Introduction

In the era of user-centered product design, a good user experience is the direct way to keep the user’s viscosity, for the usability is an important software feature. Based on subjective evaluation by experts and users, these traditional methods adopt the method of analytic hierarchy process (AHP) and the weighted average to evaluate the software usability. When DS evidence theory is applied for MADM problems, there are two main key problems [16]: basic probability assignment (BPA) generation and attribute weight optimization problems. In literature [21], the basic probability assignment (BPA) is generated based on the distance between interval numbers to improve belief Markov chain model. Aimed at the shortage of the weighted method in determining the weights of evidence theory, literature [24] uses particle swarm algorithm combining historical data value to obtain the optimal weights in the weighted information fusion problem, but the particle swarm optimization (PSO) algorithm is easy to premature and cannot guarantee the global convergence. (3) To obtain better fusion effect, the hybrid social cognitive optimization algorithm is used to optimize the different weights of evidence, in which global convergence is guaranteed

Dempster-Shafer Theory

Usability Evaluation Model of Educational Resources Software

Application Analyses

Conclusion