HCI Support Card: Creating and Using a Support Card for Education in Human-Computer Interaction

Support cards summarise a set of core information about a subject. The periodic table of chemical elements and the mathematical tables are well-known examples of support cards for didactic purposes. Technology professionals also use support cards for recalling information such as syntactic details of programming languages or harmonic colour palettes for designing user interfaces. While support cards have proved useful in many contexts, little is known about its didactic use in the Human-Computer Interaction (HCI) field. To fill this gap, this study proposes and evaluates a process for creating and using an HCI support card. The process considers the interdisciplinary nature of the field, covering the syllabus, curriculum, textbooks, and students' perception about HCI topics. The evaluation is based on case studies of creating and using a card during a semester in two undergraduate courses: Software Engineering and Information Systems. Results show that a support card can help students in following the lessons, remembering and integrating the different topics studied in the classroom. The card guides the students in building their cognitive maps, mind maps, and concept maps to study human-computer interaction. It fosters students' curiosity and permanent engagement with the HCI topics. The card usefulness goes beyond the HCI classroom, being also used by students in their professional activities and other academic disciplines, fostering an interdisciplinary application of HCI topics.Comment: Workshop on HCI Education (WEIHC '19

Considering Human Aspects on Strategies for Designing and Managing Distributed Human Computation

A human computation system can be viewed as a distributed system in which the processors are humans, called workers. Such systems harness the cognitive power of a group of workers connected to the Internet to execute relatively simple tasks, whose solutions, once grouped, solve a problem that systems equipped with only machines could not solve satisfactorily. Examples of such systems are Amazon Mechanical Turk and the Zooniverse platform. A human computation application comprises a group of tasks, each of them can be performed by one worker. Tasks might have dependencies among each other. In this study, we propose a theoretical framework to analyze such type of application from a distributed systems point of view. Our framework is established on three dimensions that represent different perspectives in which human computation applications can be approached: quality-of-service requirements, design and management strategies, and human aspects. By using this framework, we review human computation in the perspective of programmers seeking to improve the design of human computation applications and managers seeking to increase the effectiveness of human computation infrastructures in running such applications. In doing so, besides integrating and organizing what has been done in this direction, we also put into perspective the fact that the human aspects of the workers in such systems introduce new challenges in terms of, for example, task assignment, dependency management, and fault prevention and tolerance. We discuss how they are related to distributed systems and other areas of knowledge.Comment: 3 figures, 1 tabl

Citizen Science Terminology Matters: Exploring Key Terms

Much can be at stake depending on the choice of words used to describe citizen science, because terminology impacts how knowledge is developed. Citizen science is a quickly evolving field that is mobilizing people’s involvement in information development, social action and justice, and large-scale information gathering. Currently, a wide variety of terms and expressions are being used to refer to the concept of ‘citizen science’ and its practitioners. Here, we explore these terms to help provide guidance for the future growth of this field. We do this by reviewing the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology; discussing what citizen science is and reviewing related terms; and providing a collection of potential terms and definitions for ‘citizen science’ and people participating in citizen science projects. This collection of terms was generated primarily from the broad knowledge base and on-the-ground experience of the authors, by recognizing the potential issues associated with various terms. While our examples may not be systematic or exhaustive, they are intended to be suggestive and invitational of future consideration. In our collective experience with citizen science projects, no single term is appropriate for all contexts. In a given citizen science project, we suggest that terms should be chosen carefully and their usage explained; direct communication with participants about how terminology affects them and what they would prefer to be called also should occur. We further recommend that a more systematic study of terminology trends in citizen science be conducted

Computing by humans from the perspective of human engagement and credibility and task replication.

Computação por humanos (human computation) é um modelo de computação que se baseia na coordenação de seres humanos para resolver problemas para os quais o sistema cognitivo humano é mais rápido ou preciso que os atuais sistemas computacionais baseados em processadores digitais. Em sistemas de computação por humanos, ao invés de máquinas, os processadores que realizam as computações são seres humanos. Usar adequadamente o poder cognitivo provido por tais seres humanos é fundamental para o sucesso desse tipo de sistema. Entretanto, pouco se sabe sobre as características de oferta de poder cognitivo e de como o sistema pode utilizar essa oferta de forma otimizada. Este estudo visa avançar esse conhecimento. Como referencial teórico-conceitual, propõe-se uma articulação de teorias e conceitos sobre computação por humanos, engajamento, credibilidade e otimização de desempenho Considerando essa articulação, são propostas métricas para analisar a oferta de poder cognitivo em termos do engajamento e da credibilidade dos participantes. Como estudo de caso de estratégia de otimização de desempenho, propõe-se um algoritmo de replicação de tarefas que visa melhorar o uso do poder cognitivo levando em conta informações de credibilidade dos participantes. Por meio de análise de distribuições, correlações, regressões, classificação e agrupamento, os comportamentos de engajamento e credibilidade são caracterizados usando dados de seis sistemas reais. Entre os resultados obtidos, destacam-se diversos padrões comportamentais identificados na caracterização. Há duas classes de engajamento de participantes: os transientes, que atuam no sistema em apenas um dia e não retornam, e os regulares, que apresentam um engajamento mais duradouro. Os regulares são a minoria, mas são os mais importantes por agregarem maior tempo de computação ao sistema. Eles também não são homogêneos; subdividem-se em cinco grandes perfis,que podem ser rotulados como: empenhados, espasmódicos, persistentes, duradouros e moderados. A credibilidade dos participantes, por sua vez, pode ser medida usando várias métricas baseadas no nível de concordância entre eles. Tal credibilidade está negativamente correlacionada com a dificuldade das tarefas. Por fim, simulações do algoritmo de replicação proposto mostram que ele melhora o uso do poder cognitivo provido pelos participantes e permite tratar diversos compromissos entre diferentes requisitos de qualidade de serviço.Human computation is a computing approach that draws upon human cognitive abilities to solve computational tasks for which there are so far no satisfactory fully automated solutions. In human computation systems, the processors performing the computations are humans rather than machines. The effectiveness of this kind of system relies on its ability to optimize the use of the cognitive power provided by each human processor. However, little is known about how humans provide their cognitive power in these systems and how these systems can use such cognitive power properly. This study aims at advancing knowledge in this direction. To guide this study, we articulate a framework of theories and concepts about human computation, human engagement, human credibility, and the optimization of computational systems. Based on this theoretical-conceptual framework, we propose metrics to characterize the cognitive power available in a human computation system in terms of the engagement and the credibility of the participants. As case study of system optomization, we also propose a task replication algorithm that optimizes the use of the available cognitive power taking into account information about the credibility of participants. By using correlations, regressions, and clustering algorithms, we characterize the engagement and credibility of participants in data collected from six real systems. Several behavioral patterns are identified in such characterization. Participants can be divided into two broad classes of engagement: the transients, those who work in the system in just one day; and the regulars, those who exhibit a more lasting engagement. Regulars are the minority of participants, but they aggregate the larger amount of cognitive power to the system. They can be subdivided into five groups, labeled as: hardworking, spasmodic, persistent, lasting and moderate. The credibility of participants can be measured by using several different metrics based on the level of agreement among them. Regardless of the metric used, the credibility is negatively correlated with the degree of difficulty of the tasks. Results from simulation show that the proposedtaskreplicationalgorithmcanimprovetheabilityofthesystemtoproperlyusethe cognitive power provided by participants. It also allows one to address trade-offs between differentquality-of-servicerequirements.Cape

Evaluation of the impact of energy saving strategies on grid computing grids.

Grades computacionais entre-pares são infraestruturas de computação que utilizam ciclos ociosos de recursos computacionais de diferentes domínios administrativos. Geralmente, a demanda por recursos nessas grades ocorre em rajadas. Durante uma rajada de demanda, muitos recursos da grade são necessários. Porém, em outros momentos, os recursos permanecem ociosos por longos períodos. Manter os recursos ociosos quando não estão em uso nem pela grade nem pelo usuário local não é eficiente em termos de consumo de energia. Uma maneira de reduzir a energia consumida pelos recursos nesses períodos é colocálos em um modo de dormência, em que eles consomem menos energia. Nesta dissertação, avaliamos duas estratégias de dormência: Sobreaviso e Hibernação. No contexto de grades computacionais, essas estratégias apresentam um compromisso entre o benefício da economia de energia dos recursos, de um lado, e de outro lado os custos associados em termos do aumento no tempo de resposta das aplicações e do impacto no tempo de vida dos recursos. O aumento no tempo de resposta advém do tempo necessário para acordar o recurso quando surge uma nova demanda da grade. O impacto na vida útil do recurso ocorre em razão das partidas e paradas das rotações do disco rígido quando as estratégias de dormência são utilizadas. Nossa avaliação utiliza um modelo simulado para tratar esse compromisso. Avaliamos após quando tempo de inatividade (TI) as estratégias de dormência devem ser utilizadas e como escolher quais recursos acordar quando surgir uma demanda menor que a quantidade de recursos adormecidos. Nos cenários avaliados, Sobreaviso resultou em uma economia de energia equivalente a Hibernação, mas em um menor impacto no tempo de resposta. Além disso, Sobreaviso pode ser utilizado tão logo a máquina se torne inativa, não sendo necessário aguardar um TI. Isso permite aumentar a economia de energia sem gerar atrasos consideráveis no tempo de resposta. Os resultados mostram que utilizar uma estratégia de escolha que considera a eficiência energética dos recursos permite um aumento na economia de energia. Por fim, encontramos que o uso das estratégias de dormência pela grade resulta em menos partidas e paradas dos discos rígidos do que as que ocorreriam se o usuário local, ao invés de disponibilizar sua máquina para a grade, adotasse uma estratégia que a colocasse em um estado de dormência, sempre que ela ficasse ociosa.Peer-to-peer opportunistic grids are distributed computing infrastructures that harvest the idle computing cycles of computing resources geographically distributed. In these grids, the demand for resources is typically bursty. During bursts of resource demand, many grid resources are required, but on other times they remain idle for long periods. If the resources are kept powered on even when they are neither processing their owners workload nor grid jobs, their exploitation is not efficient in terms of energy consumption. One way to reduce the energy consumed in these idleness periods is to place the computers that comprise the grid in a “sleeping” mode which consumes less energy. In this work, we evaluated two sleeping strategies, namely: standby and hibernate. In grid computing, these strategies show a tradeoff between the benefit of energy saving and the associated costs in terms of increasing the job makespan and the effects in hard disks’ lifetime. The overhead in the makespan due to the time taken to wake up the resource when a new task arrives. The effect in hard disks’ lifetime is due to starting and stopping of the hard drives revolutions when sleeping strategies are used. In this work, we use a simulated model in order to evaluate this tradeoff. We also evaluated the minimum amount of machine idle time after which a sleeping strategy should be applied and how to choose which machine should be woken up, if several options are available. Our results show that both Standby and Hibernate strategies can present great energy savings. However, Standby presents lower impact on the job’s makespan. Furthermore, we have identified that sleeping strategies can be used as soon as the machine becomes idle, i.e., it is not necessary to wait any time in idle state. Regarding the strategies to chose machines, the ones that consider the machine energy efficiency increase the energy saving. Finally, we found that the use of sleeping strategies by peer-to-peer grids result in fewer hard disk transitions than would occur if the local user, instead of donate your machine to the grid, to adopt a strategy to place it in a sleeping mode, when it was idle.CNP

Task Redundancy Strategy Based on Volunteers’ Credibility for Volunteer Thinking Projects

In this paper, we propose a task redundancy strategy based on measures of accuracy of volunteers. Simulation results show that our strategy reduces the number of generated task replicas compared to the pessimistic and moderate strategies. It also generates similar or less task replicas compared to the optimistic strategy

Citizen science from the Iberoamerican perspective: an overview, and insights by the RICAP network

Encounters in Citizen Science - European Citizen Science Association (ECSA), 6-11 September 2020, Trieste, Italy.-- 1 page, figuresCS study and practice in Iberoamerica and theCaribbean is widespread and diverse. Weidentified 30+ search terms that embody CS inthe region. A search in bibliographicaldatabases resulted in 200,000+ publications,mostly concentrated in 7 countries. Out of 685documented CS experiences in 9 countries,81% focus on biodiversity, ecology andenvironment, and natural resourcemanagement; 73% are local or subnational.Further research is urgent to include othercountries. Also, to understand diverse goalsdriving CS in the region, e.g., informingdecisions to improve livelihoods and conserve;educating youth for social change; (c)addressing epistemic violencePeer reviewe