  This work focuses on the context of software explainability, which is the
production of software capable of explaining to users the dynamics that govern
its internal functioning. User models that include information about their
requirements and their perceptions of explainability are fundamental when
building software with such capability. This study investigates the process of
creating personas that include information about users' explainability
perceptions and needs. The proposed approach is based on data collection with
questionnaires, modeling of empathy maps, grouping the maps, generating
personas from them and evaluation employing the Persona Perception Scale
method. In an empirical study, personas are created from 61 users' response
data to a questionnaire. The generated personas are evaluated by 60 users and
38 designers considering attributes of the Persona Perception Scale method. The
results include a set of 5 distinct personas that users rate as representative
of them at an average level of 3.7 out of 5, and designers rate as having
quality 3.5 out of 5. The median rate is 4 out of 5 in the majority of criteria
judged by users and designers. Both the personas and their creation and
evaluation approach are contributions of this study to the design of software
that satisfies the explainability requirement.
