%0 Conference Paper %1 10260886 %A Droste, Jakob %A Deters, Hannah %A Puglisi, Joshua %A Klünder, Jil %B 2023 IEEE 31st International Requirements Engineering Conference Workshops (REW) %D 2023 %K agile sysrelevantforl3s %P 129-135 %R 10.1109/REW57809.2023.00028 %T Designing End-User Personas for Explainability Requirements Using Mixed Methods Research %X With software systems becoming increasingly complex and opaque, explainability has become an emerging software quality aspect of our time. Raising explainability requirements for a large crowd of stakeholders can be a difficult task. At this point, it is unclear what factors have an impact on the subjective need for explanations. As researchers, we do not know whether end-users' explainability needs are specific for each system or if there are user types that have more generalized needs. Designing stakeholder personas has proven to be an effective method to elicit and communicate requirements. Indeed, personas have been established in both research and in applied scenarios such as software projects. Past work has created end-user personas for explainability requirements in the context of a specific system. The goal of this work is to design personas that do not only apply to explainability requirements of a certain software, but to explainability requirements in general. To this end, we conduct a mixed-methods user study consisting of an online survey and an interview study. Based on insights of 70 participants from the online survey, 10 of which were also interviewed, we design four end-user personas for general explainability requirements. We also validate the personas by doing use case walkthroughs with our participants. Our results indicate that it is possible to design end-user personas for general explainability requirements. These personas might be used in early software development stages to estimate end-users explainability needs before more specific requirements can be raised.

@inproceedings{10260886, abstract = {With software systems becoming increasingly complex and opaque, explainability has become an emerging software quality aspect of our time. Raising explainability requirements for a large crowd of stakeholders can be a difficult task. At this point, it is unclear what factors have an impact on the subjective need for explanations. As researchers, we do not know whether end-users' explainability needs are specific for each system or if there are user types that have more generalized needs. Designing stakeholder personas has proven to be an effective method to elicit and communicate requirements. Indeed, personas have been established in both research and in applied scenarios such as software projects. Past work has created end-user personas for explainability requirements in the context of a specific system. The goal of this work is to design personas that do not only apply to explainability requirements of a certain software, but to explainability requirements in general. To this end, we conduct a mixed-methods user study consisting of an online survey and an interview study. Based on insights of 70 participants from the online survey, 10 of which were also interviewed, we design four end-user personas for general explainability requirements. We also validate the personas by doing use case walkthroughs with our participants. Our results indicate that it is possible to design end-user personas for general explainability requirements. These personas might be used in early software development stages to estimate end-users explainability needs before more specific requirements can be raised.}, added-at = {2024-02-17T10:13:53.000+0100}, author = {Droste, Jakob and Deters, Hannah and Puglisi, Joshua and Klünder, Jil}, biburl = {https://www.bibsonomy.org/bibtex/2127da707775735a50fb70c9a5c772ebc/bibsonomyse}, booktitle = {2023 IEEE 31st International Requirements Engineering Conference Workshops (REW)}, doi = {10.1109/REW57809.2023.00028}, interhash = {607f57f0f4156e4b04fd98d85eaa60cb}, intrahash = {127da707775735a50fb70c9a5c772ebc}, issn = {2770-6834}, keywords = {agile sysrelevantforl3s}, month = {Sep.}, pages = {129-135}, timestamp = {2024-03-11T13:37:32.000+0100}, title = {Designing End-User Personas for Explainability Requirements Using Mixed Methods Research}, year = 2023 }