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Lessons Learned About Designing and Conducting Studies From HRI Experts.

Published version
Peer-reviewed

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Authors

Fraune, Marlena R 
Leite, Iolanda 
Karatas, Nihan 
Amirova, Aida 
Legeleux, Amélie 

Abstract

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees' feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants' responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot's limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research.

Description

Keywords

human-robot interaction, methodology, qualitative, quantitative, replication, reproducibility, research, statistics

Journal Title

Front Robot AI

Conference Name

Journal ISSN

2296-9144
2296-9144

Volume Title

8

Publisher

Frontiers Media SA
Sponsorship
Engineering and Physical Sciences Research Council (EP/R030782/1)