Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 104-109).

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 78-80).

Inspired by the engaging effects in video games, gamification aims at motivating people to show desired behaviors in a variety of contexts. During the last years, gamification influenced the design of many software applications in the consumer as well as enterprise domain. In some cases, even whole businesses, such as Foursquare, owe their success to well-designed gamification mechanisms in their product. Gamification also attracted the interest of academics from fields, such as human-computer interaction, marketing, psychology, and software engineering. Scientific contributions comprise psychological theories and models to better understand the mechanisms behind successful gamification, case studies that measure the psychological and behavioral outcomes of gamification, methodologies for gamification projects, and technical concepts for platforms that support implementing gamification in an efficient manner. Given a new project, gamification experts can leverage the existing body of knowledge to reuse previous, or derive new gamification ideas. However, there is no one size fits all approach for creating engaging gamification designs. Gamification success always depends on a wide variety of factors defined by the characteristics of the audience, the gamified application, and the chosen gamification design. In contrast to researchers, gamification experts in the industry rarely have the necessary skills and resources to assess the success of their gamification design systematically. Therefore, it is essential to provide them with suitable support mechanisms, which help to assess and improve gamification designs continuously. Providing suitable and efficient gamification analytics support is the ultimate goal of this thesis. This work presents a study with gamification experts that identifies relevant requirements in the context of gamification analytics. Given the identified requirements and earlier work in the analytics domain, this thesis then derives a set of gamification analytics-related activities and uses them to extend an existing process model for gamification projects. The resulting model can be used by experts to plan and execute their gamification projects with analytics in mind. Next, this work identifies existing tools and assesses them with regards to their applicability in gamification projects. The results can help experts to make objective technology decisions. However, they also show that most tools have significant gaps towards the identified user requirements. Consequently, a technical concept for a suitable realization of gamification analytics is derived. It describes a loosely coupled analytics service that helps gamification experts to seamlessly collect and analyze gamification-related data while minimizing dependencies to IT experts. The concept is evaluated successfully via the implementation of a prototype and application in two real-world gamification projects. The results show that the presented gamification analytics concept is technically feasible, applicable to actual projects, and also valuable for the systematic monitoring of gamification success.

Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-05-23T16:15:28Z No. of bitstreams: 1 Leandro Ferreira D’Avila_.pdf: 2516496 bytes, checksum: ce577684d579d6f920b919aadf28bdb7 (MD5) / Made available in DSpace on 2017-05-23T16:15:28Z (GMT). No. of bitstreams: 1 Leandro Ferreira D’Avila_.pdf: 2516496 bytes, checksum: ce577684d579d6f920b919aadf28bdb7 (MD5) Previous issue date: 2017-02-22 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / PROSUP - Programa de Suporte à Pós-Gradução de Instituições de Ensino Particulares / Diariamente, desenvolvedores de software precisam se envolver com atividades de manutenção para adaptar aplicações existentes a novos cenários e necessidades, como por exemplo, novas funcionalidades, correções de defeitos e requerimentos legais. Entretanto, algumas questões organizacionais podem interferir nas atividades dos desenvolvedores impactando na qualidade e manutenabilidade do software produzido. Grande volume de documentação obsoleta, dificuldades na utilização desta documentação, dependências entre módulos de software e especialistas que deixam as empresas levando o conhecimento de determinados módulos e/ou sistemas são fatores determinantes para o sucesso dos projetos. Uma das formas de mitigar o impacto destas questões seria a disponibilização de informações úteis referentes aos módulos ou artefatos de software de forma qualitativa. A disponibilização destas informações propicia um melhor entendimento do desenvolvedor em relação aos aspectos que cercam o software e o seu ambiente. De acordo com a natureza das informações disponibilizadas, os desenvolvedores podem adquirir informações relevantes sobre o softwareem questão. Essa dissertação apresenta o SW-Context, um modelo que permite a combinação de diferentes informações relacionadas a artefatos de software, a fim de aprimorar a consciência situacional dos desenvolvedores nas atividades de desenvolvimento e manutenção. Desta forma, os principais desafios do modelo são: a definição de quais informações devem compor o contexto para software, o armazenamento estruturado destas informações em históricos de contextos e, finalmente, a análise e disponibilização destas informações de contexto, de forma que possam auxiliar a atividade de desenvolvimento e manutenção de software, utilizando o conceito SoftwareAnalytics. Foi implementado um protótipo contendo os principais conceitos do modelo proposto. Este protótipo utilizou as informações contextuais de aplicações reais de uma empresa de desenvolvimento de software e foi avaliado através de um estudo de caso, onde 12 desenvolvedores o utilizaram pelo período de um mês em suas atividades diárias. Ao final deste período, os desenvolvedores responderam um questionário que abordou a utilidade da ferramenta e a facilidade de uso percebida. A avaliação do modelo obteve respostas com percentuais satisfatórios tanto em relação à facilidade de uso percebida quanto à utilidade do sistema. Pode-se avaliar que a consolidação das informações contextuais em um local único e a disponibilização qualitativa das informações correlacionadas, através de dashboard, atingiu o objetivo de melhorar a consciência situacional dos desenvolvedores nas atividades de manutenção. / Developers need to deal recurrently with the maintenance activities on existing applications in order to adapt them to new scenarios and needs, for example, new features, bug fixing and legal changes. Besides that, developers often deal with organization factors with a potential impact on the success or failure of software development projects. Some of these organization factors are: large amount of old poorly documented software, many interdependencies between software modules and expert developers who left the company. A way to mitigate the impact of these factors on software correctness and maintainability can be providing useful information regarding the context of code or application under development using the analytics approach. The availability of this information provides a better understanding of the developer in relation to issues surrounding the software and its environment. SW-Context aims to allow a combination of different information related to software artifacts in order to improve the situational awareness of developers on development and maintenance activities. On this way, the main challenges of the model are: a definition of what information must compose software context, structured storage of the contextual information and, finally, the analysis and availability of this context information in a way to help the development and maintenance activities, using the Software Analytics concept. A prototype was implemented containing the main concepts of the proposed model. This prototype was prepared with the contextual information of actual applications under development by a software company and the prototype was evaluated through a case study, where 12 developers used it in their daily activities. By the end of this period, the developers responded a questionnaire, in which the usefulness and the ease of use were measured. The evaluation of the model obtained answers with percentage well placed both in relation to the ease of use as to the usefulness of the system. It can be considered that the consolidation of the contextual information in a single location and the availability of this correlated information in a graphical way, through a dashboard, reached the objective of improving the situational awareness of software developers in maintenance activities.

Neuroscientists are increasingly overwhelmed by new recordings of the nervous system. These recordings are significantly increasing in size due to new electrophysiological techniques, such as multi-electrode arrays. These techniques can simultaneously record the electrical activity (or spike trains) from thousands of neurons. These new datasets are larger than the traditional datasets recorded from single electrodes where fewer than ten spike trains are usually recorded. Consequently, new tools are now required to effectively analyse these new datasets. This thesis describes how techniques from the field of Visual Analytics can be applied to detect specific patterns in spike train data. These techniques are realised in a software tool called Neurigma. Neurigma is a collection of visual representations of spike train data that are unified to provide a coordinated representation of the data. The visual representations within Neurigma include: an interactive raster plot, an improved correlation grid, a novel representation called the correlation plot (which includes a novel coupling estimation algorithm), and a novel network diagram. These views provide insight into spike train data, and particularly, they identify correlated patterns, called functional connectivity. Within this thesis Neurigma is used to analyse synthetically generated datasets and experimental recordings. Three main findings are presented. First, propagating spiral patterns are identified within recordings from the neonatal mouse retina. Second, functional connectivity is identified within the cat visual cortex. Finally, the functional connectivity of a large synthetic dataset, of 1000 spike trains, is accurately classified into direct, indirect and common input coupling.