JOURNAL ARTICLE

Development of educational software for stainless steel selection and evaluating usability using the System Usability Scale (SUS).

  • Published In: International Journal of Mechanical Engineering Education, 2025, v. 53, n. 4. P. 957 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nery, Macclarck Pessoa; dos Santos Neto, Severiano José; Alves, Roberty Santos; Santana, João Vitor dos Santos; Griza, Sandro; Martins, Carlos Otávio Damas 3 of 3

Abstract

This article focuses on the development and usability evaluation of educational software designed to assist in the selection of stainless steels, emphasizing fatigue, corrosion-fatigue, and stress corrosion cracking (SCC) in engineering education. Developed in Java using object-oriented programming, the software includes didactic content, alloy-specific data, and a fatigue strength calculator, targeting Brazilian Mechanical and Materials Engineering students. Usability was assessed using the System Usability Scale (SUS), a reliable tool for measuring user satisfaction, yielding a score of 84, which indicates good usability compared to other educational technologies. User feedback highlighted the need to reduce excessive text, improve interface design, and expand the material database, informing potential future enhancements. The study demonstrates the integration of information technology and engineering education to improve learning tools in material selection.

Additional Information

  • Source:International Journal of Mechanical Engineering Education. 2025/10, Vol. 53, Issue 4, p957
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2025
  • ISSN:0306-4190
  • DOI:10.1177/03064190241266978
  • Accession Number:187648360
  • Copyright Statement:Copyright of International Journal of Mechanical Engineering Education is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.