1,721,084 research outputs found
Enabling Domain Experts to Develop Usable Software Artifacts
No full textEnd-user development techniques are recently becoming a fundamental added value of information systems, since they allow system adaptation to the evolving needs of a company’s users. To adequately manage the life cycle and code quality of software created through end-user development activities, end-user software engineering literature proposes a variety of methods. However, the underlying assumption is that end users carry out end-user development activities to adapt or develop software artifacts for their personal use. For this reason, the usability of the software artifacts resulting from the end user’s work becomes a secondary issue. But, this is not true for multi-tiered proxy design problems, where the usability of software artifacts created by domain experts for other people is instead a fundamental issue. In this paper, we analyze the approaches presented in literature that address this kind of problem, and propose a preliminary solution based on meta-design and meta-modeling
Integrating ChatGPT with Blockly for End-User Development of Robot Tasks
Full text linkThis paper presents an End-User Development environment for collaborative robot programming, which integrates Open AI ChatGPT with Google Blockly. Within this environment, a user, who is neither expert in robotics nor in computer programming, can define the items characterizing the application domain (e.g., objects, actions, and locations) and define pick-and-place tasks involving these items. Task definition can be achieved with a combination of natural language and block-based interaction, which exploits the computational capabilities of ChatGPT and the graphical interaction features offered by Blockly, to check the correctness of generated robot programs and modify them through direct manipulation
Empowering Worker-Robot Collaboration: Leveraging LLMs for Extracting and Visualizing Robot Task Metrics
No full textIn the context of Industry 5.0, which is characterized by a close integration between digital technology, industrial production, and human-centered design, collaborative robots emerge as key players. These robots are no longer isolated machines but an integral part of an interconnected ecosystem, where the fluidity of data plays a crucial role. Collaborative robots facilitate flexibility, efficiency, and safety in operations. However, this also introduces novel programming and data management challenges. A distinctive feature of collaborative robots is their ability to be programmed and used by non-expert users. This democratization of access to robotics offers significant advantages but also requires careful design of tools and interfaces to enable easy access to the data generated by the robots. In this context, the user interface assumes a pivotal role in ensuring that even those lacking programming expertise can fully benefit from the capabilities of collaborative robots and the da..
Digital Twins in Human-Computer Interaction: A Systematic Review
No full textWith the spreading of Industry 4.0, cyber-physical systems, and tools for augmented and virtual reality, Digital Twin (DT) is gaining momentum in several areas of Computer Science and Engineering. This paper presents a systematic literature review that investigates the way DTs are described in Human-Computer Interaction (HCI) scientific literature. The study includes 23 papers selected through a systematic search on the 21 most ranked journals and conferences in the HCI area. As a result of this work, it appears clear that the way humans interact with DTs is a topic still far from being widely studied. A set of hints for future research about the relationship between HCI and DT constitute the main outcome of this paper
Routine Creation in Multi-User Contexts: Improving the Quality of Life through Conflict Resolution
Full text linkExploring the Reciprocal Influence of Artificial Intelligence and End-User Development
Full text linkThis paper explores the reciprocal influence between Artificial Intelligence (AI) features of modern systems and End-User Development (EUD) activities aimed at adapting systems’ behavior to users’ needs and preferences. To improve the quality of life of people who are called on to use AI-infused systems and customize them, new methods and techniques for EUD should be studied. EUD could be of help in exploiting AI algorithms to collect information about users and to offer them advanced interaction modalities. The paper explores these possibilities through the analysis of two application domains where the effective combination of AI and EUD might play a crucial role in the future
A Meta-Design Approach to Collaborative Robotics to Achieve Sustainability Goals
No full textThis paper analyzes how collaborative robots can contribute to achieving some of the United Nations’ Sustainability Development Goals and reflects on the advantages that a meta-design approach could bring to robot deployment in real settings. The paper highlights how true sustainability not only depends on technological innovation but also on considerations that pertain to the social sphere of the intervention, like the specific domain, the workplace, and the user community, which require infrastructures for customization, sharing, and collaboration
EUDability: A new construct at the intersection of End-User Development and Computational Thinking
No full textThe sustainable and digital future of work may imply a dramatic equilibrium change between social factors and technological ones. We argue that providing suitable tools to support End-User Development (EUD) in the workplace could represent a way to cope with such future changes. The contributions of this paper include the analysis and characterization of the most used EUD techniques and their crossover with a new conveyed model of Computational Thinking. The synthesis between these aspects is made explicit in the construct of EUDability, which is designed to capture the quality dimensions of EUD systems suitable to work scenarios where better roles and better tools for individuals may be shaped. EUDability has to do with identifying and assessing the difficulties of EUD techniques on one side and the Computational Thinking skills held by individuals on the other side. (c) 2022 Elsevier Inc. All rights reserved
A Systematic Review on Pill and Medication Dispensers from a Human-Centered Perspective
Full text linkAs medication adherence represents a critical challenge in healthcare, pill and medication dispensers have gained increasing attention as potential solutions to promote adherence and improve patient outcomes. Following the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) methodology, we carried out a systematic literature review on papers indexed in Scopus and PubMed, which present solutions for pill or medication dispensers. Given the importance of user acceptance for these solutions, the research questions of the survey are driven by a human-centered perspective. We first provide an overview of the different solutions, classifying them according to their stage of development. We then analyze each solution considering its hardware/software architecture. Finally, we review the characteristics of user interfaces designed for interacting with pill and medication dispensers and analyze the involvement of different types of users in dispenser management. On the basis of this analysis, we draw findings and indications for future research that are aimed to provide insights to healthcare professionals, researchers, and designers who are interested in developing and using pill and medication dispensers
A User-in-the-loop Digital Twin for Energy Consumption Prediction in Smart Homes
No full textThis paper describes a digital twin of smart homes able to predict future energy consumption and help the user make better decisions about the activation of smart appliances and the scheduling of automations comprising different appliances' activations. To deal with the problem of time series forecasting for energy consumption prediction, a deep learning approach based on Long-Short Term Memory has been adopted, and a grid search has been used to identify the values of hyperparameters with the best prediction accuracy. Proper information visualization and interaction features have been then implemented in the digital twin interface to explain to the user the predicted consumption data and the reasons underlying warnings and suggestions provided by the system. In this way, the digital twin becomes a system based on artificial intelligence that exhibits an explainable behavior, which allows the user to make decisions about smart home management in a more conscious and sustainable way
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