Daniel Gooch

Bio: Daniel Gooch is an academic researcher from Open University. The author has contributed to research in topics: Smart city & Data literacy. The author has an hindex of 15, co-authored 48 publications receiving 1501 citations. Previous affiliations of Daniel Gooch include University of Bath & Institute of Education.

Communications of the ACM

Abstract: Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Creating an Understanding of Data Literacy for a Data-driven Society

Abstract: Society is become increasingly reliant on data, making it necessary to ensure that all citizens are equipped with the skills needed to be data literate. We argue that the foundations for a data literate society begin by acquiring key data literacy competences in school. However, as yet there is no clear definition of what these should be. This paper explores the different perspectives currently offered on both data and statistical literacy and then critically examines to what extent these address the data literacy needs of citizens in today’s society. We survey existing approaches to teaching data literacy in schools, to identify how data literacy is interpreted in practice. Based on these analyses, we propose a definition of data literacy that is focused on using data to understand real world phenomena. The contribution of this paper is the creation of a common foundation for teaching and learning data literacy skills.

Diversity for design: a framework for involving neurodiverse children in the technology design process

Abstract: The neurodiversity movement seeks to positively reframe certain neurological conditions, such as autism spectrum disorders (ASD) and dyslexia, by concentrating on their strengths. In recent years, neurodiverse children have increasingly been involved in the technology design process, but the design approaches adopted have focused mostly on overcoming difficulties of working with these children, leaving their strengths untapped. We present a new participatory design (PD) framework, Diversity for Design (D4D), which provides guidance for technology designers working with neurodiverse children in establishing PD methods that capitalize on children's strengths and also support potential difficulties. We present two case studies of use of the D4D framework, involving children with ASD and dyslexia, showing how it informed the development and refinement of PD methods tailored to these populations. In addition, we show how to apply the D4D framework to other neurodiverse populations.

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

Abstract: Many Smart City projects are beginning to consider the role of citizens. However, current methods for engaging urban populations in participatory design (PD) activities are somewhat limited. In this article, 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 PD 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.

Reimagining the role of citizens in smart city projects

Abstract: The technological focus of many Smart City projects relies on top-down innovations, ignoring the role that citizens can play in improving their local communities. In this paper we outline our approach to supporting citizens in playing an active role in urban innovation, from the crowdsourcing of initial ideas through to facilitating citizen involvement in the realization of community projects. This extends previous work in the field by exploring how to go beyond identifying issues and ideas to securing a commitment from citizens to assisting a project intended to address an identified issue.

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Abstract: Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end-users under a usage-based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter-networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter-networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.

Modelling strategic relationships for process reengineering

Abstract: Existing models for describing a process (such as a business process or a software development process) tend to focus on the "what" or the "how" of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing and approving a claim. In trying to improve or redesign a process, however, one also needs to have an understanding of the "why"--for example, why do physicians submit treatment plans to insurance companies before giving treatment? and why do claims managers seek medical opinions when assessing treatment plans? An understanding of the motivations and interests of process participants is often crucial to the successful redesign of processes. This thesis proposes a modelling framework i* (pronounced i-star) consisting of two modelling components. The Strategic Dependency (SD) model describes a process in terms of intentional dependency relationships among agents. Agents depended on each other for goals to be achieved, tasks to be performed, and resources to be furnished. Agents are intentional in that they have desires and wants, and strategic in that they are concerned about opportunities and vulnerabilities. The Strategic Rationale (SR) model describes the issues and concerns that agents have about existing processes and proposed alternatives, and how they might be addressed, in terms of a network of means-ends relationships. An agent's routines for carrying out a process can be analyzed for their ability, workability, viability and believability. Means-ends rules are used to suggest methods for addressing issues, related issues to be raised, and assumptions to be challenged. The models are represented in the conceptual modelling language Telos. The modelling concepts are axiomatically characterized. The utility of the framework is illustrated each of four application areas: requirements engineering, business process reengineering, organizational impacts analysis, and software process modelling. Advantage of i* over existing modelling techniques in each of these areas are described.

Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community?

Abstract: The process of increasing student exposure to computational thinking in K-12 is complex, requiring systemic change, teacher engagement, and development of signifi cant resources Collaboration with the computer science education community is vital to this effort

DeepStack: Expert-level artificial intelligence in heads-up no-limit poker

Abstract: Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect information. Poker, the quintessential game of imperfect information, is a long-standing challenge problem in artificial intelligence. We introduce DeepStack, an algorithm for imperfect-information settings. It combines recursive reasoning to handle information asymmetry, decomposition to focus computation on the relevant decision, and a form of intuition that is automatically learned from self-play using deep learning. In a study involving 44,000 hands of poker, DeepStack defeated, with statistical significance, professional poker players in heads-up no-limit Texas hold’em. The approach is theoretically sound and is shown to produce strategies that are more difficult to exploit than prior approaches.

Gamifying education: what is known, what is believed and what remains uncertain: a critical review

Abstract: Gamification of education is a developing approach for increasing learners’ motivation and engagement by incorporating game design elements in educational environments. With the growing popularity of gamification and yet mixed success of its application in educational contexts, the current review is aiming to shed a more realistic light on the research in this field by focusing on empirical evidence rather than on potentialities, beliefs or preferences. Accordingly, it critically examines the advancement in gamifying education. The discussion is structured around the used gamification mechanisms, the gamified subjects, the type of gamified learning activities, and the study goals, with an emphasis on the reliability and validity of the reported outcomes. To improve our understanding and offer a more realistic picture of the progress of gamification in education, consistent with the presented evidence, we examine both the outcomes reported in the papers and how they have been obtained. While the gamification in education is still a growing phenomenon, the review reveals that (i) insufficient evidence exists to support the long-term benefits of gamification in educational contexts; (ii) the practice of gamifying learning has outpaced researchers’ understanding of its mechanisms and methods; (iii) the knowledge of how to gamify an activity in accordance with the specifics of the educational context is still limited. The review highlights the need for systematically designed studies and rigorously tested approaches confirming the educational benefits of gamification, if gamified learning is to become a recognized instructional approach.