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

Collective Intelligence and the Mapping of Accessible Ways in the City: a Systematic Literature Review

This paper has the objective of assessing how ICTs are being used to provide accessibility in urban mobility, with special interest to collective intelligence approaches. A systematic literature review (SLR) was performed, using several different criteria to filter down the 500+ academic papers that were originally obtained from a search for “accessible maps” to the 43 papers that finally remained in the corpus of the SLR. Among the findings, it was noticed that (i) few studies explored the motivations of users that actively contribute, providing information to feed maps, and they restricted themselves to exploring three techniques: gaming, monetary reward and ranking; (ii) social networks are rarely used as a source of data for building and updating maps; and (iii) the literature does not discuss any initiative that aims to support the needs of physically and visually impaired citizens at the same time

Mapping Accessible Paths in the City Using Collective Intelligence

New information and communication technologies (ICTs) have an increasingly stronger role in people\u27s lives, especially after the commoditization of smartphones. They affect many aspects of everyday life, including urban mobility. Some applications, including Waze, benefit from the collective intelligence (CI) of the crowds to gather the information they need to provide users with good advice on the routes to follow. But they are mainly focused on roads and streets, giving little information on the quality of sidewalks, which are essential to pedestrians, people on wheelchairs and blind people. With the intention to improve the mobility of citizens with special needs, we developed the prototype of an application that allows users themselves to update accessibility maps, tagging obstacles and also indicating the existence of resources that contribute to improve the mobility of people with special needs in urban spaces. Tests in a controlled environment helped to debug the application’s functionalities, before members of the intended target group of users were finally exposed to it. Results are promising, as users were able to include relevant data by themselves and seem motivated to keep doing so, due a sense of utility, social facilitation or simply due to altruism, as anticipated by the CI literature. One unexpected outcome was that impaired users are more excited about the potential the application has to give visibility to the challenges they face than with the actual improvement it can bring to their mobility

Collecting data for indoor mapping of the university of Münster via a location based game

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Nowadays the collection of spatial indoor mapping data presents a big challenge for both science and industry because there is not a cost-effective method yet for it as it is for outdoor mapping. Research is pointing out to crowdsourcing as means of address the challenge of massive indoor mapping based on the principle that people should be the main source of information. Therefore the crowd needs a tool that lets them do indoor mapping tasks as well as means of motivation. This project has as its main goal to study the impact of gamification as a motivation factor by implementing and evaluating it in a mobile application aimed for acquisition of indoor spatial data of the buildings of the University of Münster. For this purpose an already existing mobile application was modified to incorporate game elements, thus creating a new version of the app. Three game mechanics were added for the new version of the app: score, leaderboard and conquest map. Once both apps were ready (gamified and original non-gamified) an evaluation was carried out with 28 participants (14 male and 14 female) to assess the impact of game mechanics when users are performing indoor mapping tasks. As a result we may say that the most of participants preferred the gamified application over the non-gamified one, the study also shows that actually men favored the gamified app more than women

An investigation into the role of crowdsourcing in generating information for flood risk management

Flooding is a major global hazard whose management relies on an accurate understanding of its risks. Crowdsourcing represents a major opportunity for supporting flood risk management as members of the public are highly capable of producing useful flood information. This thesis explores a wide range of issues related to flood crowdsourcing using an interdisciplinary approach. Through an examination of 31 different projects a flood crowdsourcing typology was developed. This identified five key types of flood crowdsourcing: i) Incident Reporting, ii) Media Engagement, iii) Collaborative Mapping, iv) Online Volunteering and v) Passive VGI. These represent a wide range of initiatives with radically different aims, objectives, datasets and relationships with volunteers. Online Volunteering was explored in greater detail using Tomnod as a case study. This is a micro-tasking platform in which volunteers analyse satellite imagery to support disaster response. Volunteer motivations for participating on Tomnod were found to be largely altruistic. Demographics of participants were significant, with retirement, disability or long-term health problems identified as major drivers for participation. Many participants emphasised that effective communication between volunteers and the site owner is strongly linked to their appreciation of the platform. In addition, the feedback on the quality and impact of their contributions was found to be crucial in maintaining interest. Through an examination of their contributions, volunteers were found to be able to ascertain with a higher degree of accuracy, many features in satellite imagery which supervised image classification struggled to identify. This was more pronounced in poorer quality imagery where image classification had a very low accuracy. However, supervised classification was found to be far more systematic and succeeded in identifying impacts in many regions which were missed by volunteers. The efficacy of using crowdsourcing for flood risk management was explored further through the iterative development of a Collaborative Mapping web-platform called Floodcrowd. Through interviews and focus groups, stakeholders from the public and private sector expressed an interest in crowdsourcing as a tool for supporting flood risk management. Types of data which stakeholders are particularly interested in with regards to crowdsourcing differ between organisations. Yet, they typically include flood depths, photos, timeframes of events and historical background information. Through engagement activities, many citizens were found to be able and motivated to share such observations. Yet, motivations were strongly affected by the level of attention their contributions receive from authorities. This presents many opportunities as well as challenges for ensuring that the future of flood crowdsourcing improves flood risk management and does not damage stakeholder relationships with participants

Power to the People: A Comprehensive Look at Crowdsourcing Initiatives in Cultural Institutions

Today, crowdsourcing has become an integrative approach to completing projects using the help of the general populous. These projects aid museum staff by processing large quantities of data, which otherwise could not be completed due to time and/or staff restraints. Through crowdsourcing, cultural institutions have the ability to outsource these tasks to volunteers, who can complete them at much faster rates. Although staff members are needed to validate and supervise these projects, crowdsourcing remains a useful tool in increasing public interactions and project efficiency. This thesis presents a thorough outline of what crowdsourcing is, how it is being utilized, and how volunteers can be motivated to participate. Case studies are presented, providing a comprehensive look into each of the six types of crowdsourcing. These studies include the Brooklyn Museum, September 11th Memorial and Museum, South Eastern Regional Network of Expertise and Collections, British Library, Peoria Historical Society, and Smithsonian Institution. Utilizing these critical examples, this paper presents several motivational theories of volunteer participation and outlines how this knowledge can be implemented to create a more successfully crowdsourced project

Succeeding with Smart People Initiatives: Difficulties and Preconditions for Smart City Initiatives that Target Citizens

Smart City is a paradigm for the development of urban spaces through the implementation of state-of-the-art ICT. There are two main approaches when developing Smart Cities: top-down and bottom-up. Based on the bottom-up approach, the concepts of Smart People and Smart Communities have emerged as dimensions of the Smart City, advocating for the engagement of citizens in Smart People initiatives. The aim of this research is both to find the types of Smart People initiatives and to identify their difficulties and preconditions for success. However, such initiatives that aim to (1) leverage the citizens intellectually and (2) use citizens as a source of input for ideas and innovation, are understudied. Therefore, this research proposes a concentrated framework of Smart People initiatives from an extensive literature review. On one hand, this framework contributes with a common ground and vocabulary that facilitates the dialogue within and between practitioners and academia. On the other hand, the identification of difficulties and preconditions guides the academia and practitioners in how to successfully account for citizens in the Smart City. From the literature review and the conduct of case studies of five European cities, participation came out as the key difficulty across both types of Smart People initiatives and cases, closely followed by awareness, motivation and complexity

SmartWheels: Detecting urban features for wheelchair users’ navigation

People with mobility impairments have heterogeneous needs and abilities while moving in an urban environment and hence they require personalized navigation instructions. Providing these instructions requires the knowledge of urban features like curb ramps, steps or other obstacles along the way. Since these urban features are not available from maps and change in time, crowdsourcing this information from end-users is a scalable and promising solution. However, it is inconvenient for wheelchair users to input data while on the move. Hence, an automatic crowdsourcing mechanism is needed. In this contribution we present SmartWheels, a solution to detect urban features by analyzing inertial sensors data produced by wheelchair movements. Activity recognition techniques are used to process the sensors data stream. SmartWheels is evaluated on data collected from 17 real wheelchair users navigating in a controlled environment (10 users) and in-the-wild (7 users). Experimental results show that SmartWheels is a viable solution to detect urban features, in particular by applying specific strategies based on the confidence assigned to predictions by the classifier

StarBorn : Towards making in-situ land cover data generation fun with a location-based game

University Research Priority Program: Language and Space, University of ZurichPeer reviewedPublisher PD