PhD thesis data: Exploring Human-Robot Futures through Participatory Design

This dataset comprises material related to a PhD thesis on how to equitably involve ordinary people in the design of robots and assistive technology.In Study 1, children with brittle bones and their families had direct contact with contemporary social robots and assistive technology and wrote short stories about how they might want such technologies to feature in their future. This dataset comprises:Study Documentation: Final versions of the documentation for Study 1, as accepted by IRAS (NHS ethics approval). It includes:Assent formConsent formsCultural probe diary templateParticipant information sheetsSemi-structured group discussion topic guidesSliding scale questionnaireSliding Scales Spreadsheet: This file tracks responses to a customised sliding scale regarding anonymised participants' attitudes towards robots after each session, including basic statistical analysis such as the standard deviation.Sliding Scales Responses - Graphs of Mean Averages and Individual Participant Response Trajectories: Graphs made of the response to the customised sliding scales administered in Study 1.Qualitative Data Summary: A summary of qualitative data (verbal utterances and authored short stories), including an overview of generated themes and sub-themes, with example code labels.Study 2 invited the general public to consider possible technology futures through interactive fiction, co-opting the Science Fiction Prototyping methodology for use in Participatory Design by incorporating interactivity. The data comprises:The original, more complex branching narrative of the 'Murder (Most(ly) Forgotten' storySpreadsheet with analysed story playthrough data