A Comparative Study of the Role of Examples in Microtask Crowdsourcing for Software Design

A Comparative Study of the Role of Examples in Microtask Crowdsourcing for Software Design

Author: Fernando Spanghero

Publisher:

Published: 2016

Total Pages: 99

ISBN-13: 9781369174342

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Crowdsourcing is gradually becoming an accepted form of work across different disciplines. Not surprisingly, it has attracted the attention of the software engineering community as well. Previous work started exploring the feasibility of crowdsourcing for software design by conducting experiments in which workers from Amazon Mechanical Turk were asked to engage in a set of software design tasks. It was found that, when workers are exposed to examples of previous designs, they generate overall lower quality contributions. The intuition is that, since these experiments displayed all previous contributions as examples to workers, the presence of low quality examples may have negatively influenced workers.This thesis compares the designs produced in the previous experiments to designs obtained in a new experiment in which examples were evaluated against pre-defined quality criteria before being displayed to workers. Only examples that were of sufficient quality were shared with workers, with the hope of stimulating them to provide higher quality designs.We report results from an analysis in which we compare the designs from the current and previous experiments in terms of quantity, diversity of ideas, quality, completeness, perceived task difficulty, and how often workers borrow elements from examples. The major findings are twofold. First, workers who were exposed to sufficient quality examples produced better quality work as compared to workers exposed to all examples. Second, the quality of the designs they produced still did not reach the quality of the designs produced by workers who were not exposed to examples at all.


Value Sensitive Design

Value Sensitive Design

Author: Batya Friedman

Publisher: MIT Press

Published: 2019-05-21

Total Pages: 258

ISBN-13: 0262039532

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Using our moral and technical imaginations to create responsible innovations: theory, method, and applications for value sensitive design. Implantable medical devices and human dignity. Private and secure access to information. Engineering projects that transform the Earth. Multigenerational information systems for international justice. How should designers, engineers, architects, policy makers, and others design such technology? Who should be involved and what values are implicated? In Value Sensitive Design, Batya Friedman and David Hendry describe how both moral and technical imagination can be brought to bear on the design of technology. With value sensitive design, under development for more than two decades, Friedman and Hendry bring together theory, methods, and applications for a design process that engages human values at every stage. After presenting the theoretical foundations of value sensitive design, which lead to a deep rethinking of technical design, Friedman and Hendry explain seventeen methods, including stakeholder analysis, value scenarios, and multilifespan timelines. Following this, experts from ten application domains report on value sensitive design practice. Finally, Friedman and Hendry explore such open questions as the need for deeper investigation of indirect stakeholders and further method development. This definitive account of the state of the art in value sensitive design is an essential resource for designers and researchers working in academia and industry, students in design and computer science, and anyone working at the intersection of technology and society.


Macro-task Crowdsourcing

Macro-task Crowdsourcing

Author: Vassillis-Javed Khan

Publisher:

Published: 2019

Total Pages:

ISBN-13: 9783030123352

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Crowdsourcing is an emerging paradigm that promises to transform several domains: creative work, business work, cultural cooperation, etc. Crowdsourcing reflects the close-knit interplay between the latest computer technologies, the rapidly changing work model of the 21st century, and the very nature of people. The interplay makes for an exciting but at the same time challenging new field to investigate under the lens of a diverse set of disciplines, ranging from the technical to the social and from the theoretical to the applied. Early research has focused on an aspect of crowdsourcing known as micro-tasking. Micro-tasks are simple tasks (like image annotations) that anyone could perform. An emerging area is how to utilize crowdsourcing to solve problems that go beyond simple tasks towards more complex ones, that require collaboration and creativity. In juxtaposition to micro-task crowdsourcing, this book investigates macro-task crowdsourcing and its potential.


Digital Labour Platforms and the Future of Work

Digital Labour Platforms and the Future of Work

Author: Janine Berg

Publisher:

Published: 2018

Total Pages: 168

ISBN-13:

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The emergence of online digital labour platforms has been one of the major transformations in the world of work over the past decade. This report provides one of the first comparative studies of working conditions on five major micro-task platforms that operate globally. It is based on an ILO survey covering 3,500 workers in 75 countries around the world and other qualitative surveys. The report analyses the working conditions on these micro-task platforms, including pay rates, work availability and intensity, social protection coverage and work-life balance. The report recommends 18 principles for ensuring decent work on digital labour platforms.


Human Factors in Global Software Engineering

Human Factors in Global Software Engineering

Author: Rehman, Mobashar

Publisher: IGI Global

Published: 2019-06-28

Total Pages: 381

ISBN-13: 1522594507

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More software engineers are likely to work in a globally distributed environment, which brings benefits that include quick and better software development, less manpower retention, scalability, and less software development cost and sharing of knowledge from the global pool of employees. However, these work environments also introduce a physical separation between team members and project leaders, which can create problems in communication and ultimately lead to the failure of the project. Human Factors in Global Software Engineering is a collection of innovative research focusing on the challenges, issues, and importance of human factors in global software engineering organizations in order to help these organizations better manage their manpower and provide an appropriate culture and technology in order to make their software development projects successful. While highlighting topics including agile software, knowledge management, and human-computer interaction, this book is ideally designed for project managers, administrators, business professionals, researchers, practitioners, students, and academicians.


Crowdsourced Data Management

Crowdsourced Data Management

Author: Adam Marcus

Publisher:

Published: 2015-11-18

Total Pages: 186

ISBN-13: 9781680830903

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Crowdsourced Data Management: Industry and Academic Perspectives aims to narrow the gap between academics and practitioners in this burgeoning field. It simultaneously introduces academics to real problems that practitioners encounter every day, and provides a survey of the state of the art for practitioners to incorporate into their designs.


Speed, Data, and Ecosystems

Speed, Data, and Ecosystems

Author: Jan Bosch

Publisher: CRC Press

Published: 2017-01-06

Total Pages: 369

ISBN-13: 1351982729

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As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.


Macrotask Crowdsourcing

Macrotask Crowdsourcing

Author: Vassillis-Javed Khan

Publisher: Springer

Published: 2019-08-06

Total Pages: 279

ISBN-13: 3030123340

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Crowdsourcing is an emerging paradigm that promises to transform several domains: creative work, business work, cultural cooperation, etc. Crowdsourcing reflects the close-knit interplay between the latest computer technologies, the rapidly changing work model of the 21st century, and the very nature of people. The interplay makes for an exciting but at the same time challenging new field to investigate under the lens of a diverse set of disciplines, ranging from the technical to the social and from the theoretical to the applied. Early research has focused on an aspect of crowdsourcing known as micro-tasking. Micro-tasks are simple tasks (like image annotations) that anyone could perform. An emerging area is how to utilize crowdsourcing to solve problems that go beyond simple tasks towards more complex ones, that require collaboration and creativity. In juxtaposition to micro-task crowdsourcing, this book investigates macro-task crowdsourcing and its potential.


Crowdsourced Data Management

Crowdsourced Data Management

Author: Guoliang Li

Publisher: Springer

Published: 2018-10-12

Total Pages: 169

ISBN-13: 9811078475

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This book provides an overview of crowdsourced data management. Covering all aspects including the workflow, algorithms and research potential, it particularly focuses on the latest techniques and recent advances. The authors identify three key aspects in determining the performance of crowdsourced data management: quality control, cost control and latency control. By surveying and synthesizing a wide spectrum of studies on crowdsourced data management, the book outlines important factors that need to be considered to improve crowdsourced data management. It also introduces a practical crowdsourced-database-system design and presents a number of crowdsourced operators. Self-contained and covering theory, algorithms, techniques and applications, it is a valuable reference resource for researchers and students new to crowdsourced data management with a basic knowledge of data structures and databases.


Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis

Author: National Research Council

Publisher: National Academies Press

Published: 2013-09-03

Total Pages: 191

ISBN-13: 0309287812

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Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.