Exploring Accessibility and Companionship in Boardgames via Alexa

The inaccessibility of rulebooks hinders the rule learning experience of boardgame players who are blind or low vision (BLV). We explore the design of conversational agents (CAs) to support players' learning needs and provide companionship by conducting two qualitative studies. In study 1, 14 boardgame players who are BLV first identified their rule learning challenges and co-designed desired social and functional characteristics of CAs to combat these challenges. Based on these findings, we developed a CA using Amazon Alexa and 9 players who are BLV evaluated our CA in study 2. Our findings generated five design principles for CAs to support boardgame rule learning: conciseness, ease of navigation, customization, supplementary features, and social characteristics. These principles guide designers and researchers in exploring the novel design space. Our research also demonstrates the feasibility of our method for conducting accessible remote co-design and evaluation with participants who are BLV.

Name thesis:degree_name

Master of Computer Science (M.C.S.)

Level thesis:degree_level

Master's

Discipline thesis:degree_discipline

Computer Science

Grantor dc:publisher

Carleton University

Year dc:date.issued

2023

Author dc:creator

• Karim, Saman

Statement dc:rights

• Copyright © 2023 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2023-15403

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/42694