New Algorithm for Evaluation of Online Courses Based on Quality Matters Rubric Using Fuzzy Soft Expert Sets

Int. J. Interact. Mob. Technol. Pub Date : 2024-02-27 DOI:10.3991/ijim.v18i04.42525

Anas Abukaraki, Tawfiq Alrawashdeh, I. A. Alshalabi, Moha'med Al-Jaafreh, M. Alksasbeh, Abdulhameed Alenezi, Mohammad Al-Kaseasbeh

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Abstract

The field of instructional technology has experienced significant growth in recent times. Due to the rapid shift towards online courses, the technology-based learning system is facing challenges in ensuring quality and assurance. The aim of this study was to develop online course evaluation tools by proposing a new algorithm to assess the success of the provided online courses and address quality assurance issues. The proposed algorithm is based on quality matters (QM) attributes and the use of fuzzy soft expert sets (FSESs). One key advantage of the proposed algorithm is that it incorporates experts’ opinions, which significantly contributes to achieving the study objective. The proposed algorithm was successfully implemented using the ASP.NET programming language. It resulted in the development of an EOC-FSES prototype system. The experimental evaluation of the prototype system confirms that it requires low effort and achieves high levels of performance, satisfaction, and behavioral intention to use. This paper includes several recommendations and suggestions.

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使用模糊软专家集基于质量事项评分标准评估在线课程的新算法

近来，教学技术领域取得了长足的发展。由于快速转向在线课程，基于技术的学习系统在确保质量和保证方面面临挑战。本研究的目的是通过提出一种新算法来开发在线课程评估工具，以评估所提供的在线课程是否成功，并解决质量保证问题。建议的算法基于质量问题（QM）属性和模糊软专家集（FSES）的使用。所提算法的一个主要优点是它结合了专家的意见，这大大有助于实现研究目标。拟议算法使用 ASP.NET 编程语言成功实现。最终开发出了 EOC-FSES 原型系统。对原型系统的实验评估证实，该系统只需少量工作，就能实现较高水平的性能、满意度和使用行为意向。本文包括若干建议和意见。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Int. J. Interact. Mob. Technol.

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