The Roles of Familiarity Design in Active Ageing

TL;DR

This paper explores how familiarity design in interactive systems can enhance active aging by improving elderly users' satisfaction and adoption, supported by empirical studies and a novel crowdsourcing algorithm.

Contribution

It introduces a multi-pronged approach to incorporate familiarity into technology design for the elderly and develops CrowdAsm, a crowdsourcing algorithm for team assembly.

Findings

Familiarity in design significantly increases elderly users' satisfaction.

Familiarity-based systems improve adoption rates among the elderly.

CrowdAsm achieves near-optimal profit in collaborative crowdsourcing.

Abstract

The elderly often struggle when interacting with technologies. This is because the software and hardware components of the technologies are not familiar to the elderly's mental model. This is a lack of empirical studies about how the concept of familiarity can be infused into the design of interactive technology systems to bridge the digital divide preventing today's elderly people from actively engaging with such technologies. In this paper, a multi pronged approach is utilized. We investigate the Effects of Familiarity in Design on the Adoption of Wellness Games by the Elderly, familiarity in productive ageing, familiarity in efficient collaborative crowdsourcing, productive ageing through familiarity based Intelligent Personalized Crowdsourcing and familiarity based Agent Augmented Inter-generational Crowdsourcing. The results show that familiarity in design improves the perceived satisfaction and adoption likelihood significantly among the elderly users. These results can potentially benefit intelligent interface agent design when such agents need to interact with elderly users. A Crowdsourcing algorithm, CrowdAsm is developed. By using CrowdAsm we are able to dynamically assemble teams of workers considering the budgets, the availability of workers with the required skills and their track records to complete crowdsourcing tasks requiring collaboration among workers with heterogeneous skills. Theoretical analysis has shown that CrowdAsm can achieve close to optimal profit for a collaborative crowdsourcing system if workers follow the recommendations.