Education



Better Together: Disaggregating Mobile Services for Emergent Users

MobileHCI '17: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services





My Contribution

Longitudinal Deployment

Iterative design

Qualitative research

Participatory design

Problem

Mainstream mobile interactions are focused around individual devices, with any collaboration happening via ‘the cloud’. We carried out design workshops with emergent users, revealing opportunities for novel collocated collaborative interactions among various available Android devices

Motivation

In this experiment we presented Better Together – a framework for disaggregating services, splitting interaction elements over separate mobiles. This distribution supports both sharing of resources (such as screen real-estate, or mobile data); and, the scaffolding of inclusive interaction in mixed groups (e.g., regarding literacy or prior technology exposure). We developed two prototypes to explore the concept, trailing the first—collocated group based shopping list making—with emergent users in South Africa and India. We deployed the second probe, which splits YouTube into its constituent parts across separate mobiles, in a longitudinal study with users in Kenya, South Africa, and India. We describe the concept and design process and report on the design’s suitability for emergent users based on our results.

Process-

This work, which has been conducted over the course of a year and a half, involves a diverse mix of participatory design, in-situ idea and scenario generation, summit engagement and prototype refinement. A more detailed discussion of the participatory and summit methodologies

        PROTOTYPE 1: SHOPPING TOGETHER                                       PROTOTYPE 2 : WATCHING TOGETHER
       


Longitudianal Deployment

We deployed the Better Together YouTube prototype in three resource-constrained locations over a period of five-weeks. Our goal was to explore how well the component disaggregation approach worked in a more natural, everyday environment, and whether participants saw value in its ability to share resources. We recruited 48 users from areas in and around, Mumbai, Langa and Nairobi (16 in each location). Participants from these regions took part in friendship groups of four people, with groups from a range of different social, educational and technological backgrounds. We specifically recruited participants from Mumbai and Langa who could be classed as “emergent,” whereas in Nairobi we selected participants who were less emergent, but still resource-constrained in terms of their internet access and disposable income. In order to be eligible to take part in the study, all participants had to own their own Android phone (i.e., we did not hand out devices). As a trade-off between participant privacy and depth of analysis, the app was set up to report each time a video was played, but no other information was automatically collected.