Exploring intrinsic and extrinsic motivations to participate in a crowdsourcing project to support blind and partially sighted students

There have been a number of crowdsourcing projects to support people with disabilities. However, there is little exploration of what motivates people to participate in such crowdsourcing projects. In this study we investigated how different motivational factors can affect the participation of people in a crowdsourcing project to support visually disabled students. We are developing “DescribeIT”, a crowdsourcing project to support blind and partially students by having sighted people describe images in digital learning resources. We investigated participants’ behavior of the DescribeIT project using three conditions: one intrinsic motivation condition and two extrinsic motivation conditions. The results showed that participants were significantly intrinsically motivated to participate in the DescribeIT project. In addition, participants’ intrinsic motivation dominated the effect of the two extrinsic motivational factors in the extrinsic conditions

Crowdsourcing Accessibility: Human-Powered Access Technologies

People with disabilities have always engaged the people around them in order to circumvent inaccessible situations, allowing them to live more independently and get things done in their everyday lives. Increasing connectivity is allowing this approach to be extended to wherever and whenever it is needed. Technology can leverage this human work force to accomplish tasks beyond the capabilities of computers, increasing how accessible the world is for people with disabilities. This article outlines the growth of online human support, outlines a number of projects in this space, and presents a set of challenges and opportunities for this work going forward

A qualitative enquiry into OpenStreetMap making

Based on a case study on the OpenStreetMap community, this paper provides a contextual and embodied understanding of the user-led, user-participatory and user-generated produsage phenomenon. It employs Grounded Theory, Social Worlds Theory, and qualitative methods to illuminate and explores the produsage processes of OpenStreetMap making, and how knowledge artefacts such as maps can be collectively and collaboratively produced by a community of people, who are situated in different places around the world but engaged with the same repertoire of mapping practices. The empirical data illustrate that OpenStreetMap itself acts as a boundary object that enables actors from different social worlds to co-produce the Map through interacting with each other and negotiating the meanings of mapping, the mapping data and the Map itself. The discourses also show that unlike traditional maps that black-box cartographic knowledge and offer a single dominant perspective of cities or places, OpenStreetMap is an embodied epistemic object that embraces different world views. The paper also explores how contributors build their identities as an OpenStreetMaper alongside some other identities they have. Understanding the identity-building process helps to understand mapping as an embodied activity with emotional, cognitive and social repertoires

It’s Not What You Say, It’s What You Do: The Motivation of The Crowd to Participate in a Crowdsourcing Project to Support Blind and Partially Sighted Students

There is a growing interest in crowdsourcing projects for socially responsible issues. One area of socially responsible crowdsourcing is to support people with disabilities. However, there is little exploration of what motivates people to participate in such projects. This programme of research investigated the motivators for students to participate in a socially responsible crowdsourcing project to support blind and partially sighted students by describing images found in digital learning resources. For this purpose a crowdsourcing project, DescribeIT, was developed. The first study explored what students thought would motivate them to participate in the project to compare with students’ actual behaviour in the following studies. Altruism and monetary rewards were the leading self-reported motivational factors, other factors such as being interested in accessibility were reported. Studies 2 to 6 investigated the effects of different intrinsic and extrinsic motivational factors on students’ participation in the DescribeIT project with students from the UK and Arab countries. Despite the promising results of the self-reports of motivations, UK students’ participation rates in Studies 2 to 4 was extremely low. However, paying UK students small amounts of money (Study 6) did motivate them to participate. Arab students (Study 5) were intrinsically motivated to participate in the DescribeIT project and showed a higher participation rate than UK students. Studies 7 and 9 investigated the quality of the image descriptions produced by crowd members of established crowdsourcing platforms in comparison to those produced by students. The results showed a comparable quality across descriptions produced by students and crowd members. Studies 8 and 9 investigated the effect of simplifying the image description task by changing it to an image tagging task and showed that making the task easier increased participation rate. Lastly, Study 10 investigated the effect of a face-to-face training session on image description quality. It also investigated the effect of quality control instructions on quality. The face-to-face training increased description quality, but different quality control instructions did not. The practical implications of this research for crowdsourcers in socially responsible crowdsourcing contexts, are that they need to consider the cultural backgrounds of their potential crowd, make the task easy to do, offer small payments if possible and train crowd members in order to produce good quality work. The theoretical implications are a greater understanding of the motivations of crowd members in socially responsible projects and the importance of measuring both self-reports of motivation and actual behaviour

A Labeling Task Design for Supporting Algorithmic Needs: Facilitating Worker Diversity and Reducing AI Bias

Studies on supervised machine learning (ML) recommend involving workers from various backgrounds in training dataset labeling to reduce algorithmic bias. Moreover, sophisticated tasks for categorizing objects in images are necessary to improve ML performance, further complicating micro-tasks. This study aims to develop a task design incorporating the fair participation of people, regardless of their specific backgrounds or task's difficulty. By collaborating with 75 labelers from diverse backgrounds for 3 months, we analyzed workers' log-data and relevant narratives to identify the task's hurdles and helpers. The findings revealed that workers' decision-making tendencies varied depending on their backgrounds. We found that the community that positively helps workers and the machine's feedback perceived by workers could make people easily engaged in works. Hence, ML's bias could be expectedly mitigated. Based on these findings, we suggest an extended human-in-the-loop approach that connects labelers, machines, and communities rather than isolating individual workers.Comment: 45 pages, 4 figure

Disability, Locative Media, and Complex Ubiquity

The current phase of network societies has generated an intensification of pervasive, ubiquitous digital technologies and cultures of uses, with emergent, complex social functions, and politics. In this chapter, we explore a fascinating, instructive example of the actualization of such ubiquity-effects — the case of locative media technologies designed for and by people with disabilities. In the meeting of disability and locative media technology, we find an apposite, challenging example of ubiquity — its associated, emergent social practices, what their cultural implications are, and how design makes sense of this. We discuss these dynamics of complex ubiquity and disability through two case studies: way-finding locative technology, smartphones and apps; and Google Glass.Australian Research Counci

Citizen Social Science: New and Established Approaches to Participation in Social Research

Podeu consultar el llibre complet a: http://hdl.handle.net/2445/173349This chapter explores the ways in which the roles of citizens and researchers play out in the social sciences. This is expressed by numerous overlapping and related terms, such as co-production and participatory action research, to name but two, and by the different social topics that citizen social science draws attention to. The key question this chapter seeks to explore is what does naming citizen social science as such bring to the fields of citizen science and the social sciences? The chapter explores the different epistemic foundations of citizen social science and outlines the development and provenance of citizen social science in its broadest sense, reflecting on how it is currently practised. It draws on different examples from the experiences and work of the authors and notes the boundaries and overlaps with citizen science. The chapter also highlights some of the key issues that citizen social science gives rise to, emphasising that while citizen social science is a relatively new term, its underlying approaches and epistemic foundations are at least partially established in the social sciences

Amplifying Quiet Voices: Challenges and Opportunities for Participatory Design at an Urban Scale

Many Smart City projects are beginning to consider the role of citizens. However, current methods for engaging urban populations in participatory design activities are somewhat limited. In this paper, we describe an approach taken to empower socially disadvantaged citizens, using a variety of both social and technological tools, in a smart city project. Through analysing the nature of citizens’ concerns and proposed solutions, we explore the benefits of our approach, arguing that engaging citizens can uncover hyper-local concerns that provide a foundation for finding solutions to address citizen concerns. By reflecting on our approach, we identify four key challenges to utilising participatory design at an urban scale; balancing scale with the personal, who has control of the process, who is participating and integrating citizen-led work with local authorities. By addressing these challenges, we will be able to truly engage citizens as collaborators in co-designing their city