System Usability Scale Analysis Toolkit

The System Usability Scale (SUS), developed by John Brooke, is the most widely-used questionnaire for measuring perceived usability. It consists of 10 Likert-scale questions, with responses ranging from Strongly disagree to Strongly agree. The results are aggregated into a single score ranging from 0 to 100, known as the SUS score. Multiple SUS scores can be used to represent an overall SUS study score. The SUS is straightforward to administer, has been validated through extensive applications over decades, is easy for participants to understand, is available in multiple languages and variants, and can be applied to any product/system that involves human interaction.

The SUS Analysis Toolkit is an open-source, web-based toolkit designed for the analysis, plotting, interpretation, and contextualization of single- and multivariable System Usability Scale (SUS) usability studies. It offers a comprehensive suite of tools based on insights and contextualization approaches derived from scientific literature. Therefore, we hope it enables researchers and practitioners to effortlessly calculate and visualize comparative, iterative, and single-variable SUS usability study datasets. Additionally, it provides utilities to interpret calculated scores, compare them against scores from meta-analyses, assess the conclusiveness of SUS scores, and analyze the impact of individual questions from the 10-item SUS questionnaire on overall study scores. The toolkit is particularly focused on generating publication-ready scientific figures and calculations for direct use in scientific publications and presentations. Moreover is provides utility to generate SUS questionnaires and also provide the full inferential statistics for iterative or comparative SUS studies.

There are currently no automated integrations with other tools available for the SUS Analysis Toolkit due to privacy concerns and the maintenance costs associated with supporting such integrations continuously. However, since the toolkit is open-source, users are encouraged to explore and create their own integrations. If there is enough demand we might consider this in future releases.

Yes, besides the initial usability study of the first iteration of the toolkit itself (see Blattgerste et al. 2022), there are several scientific publications that have utilized and cited the SUS Analysis Toolkit already. These publications provide insights into how the toolkit has been applied in various research contexts. For those examples, you can explore the citations of the toolkit on Google Scholar.

All parts of the SUS Analysis Toolkit are licensed under the MIT license and can be used, extended and redistributed for commercial and non-commercial use cases without attribtution. The ownership of generated calculations, interpretations, tables, and plots fully remain with the user of the tool. If you use this toolkit in the scientific context, we would appreciate an acknowledgement in form of a citation to our tool and recommend citing the primary sources for the insights utilized.