2,022 research outputs found
Recent and upcoming BCI progress: overview, analysis, and recommendations
Brain–computer interfaces (BCIs) are finally moving out of the laboratory and beginning to gain acceptance in real-world situations. As BCIs gain attention with broader groups of users, including persons with different disabilities and healthy users, numerous practical questions gain importance. What are the most practical ways to detect and analyze brain activity in field settings? Which devices and applications are most useful for different people? How can we make BCIs more natural and sensitive, and how can BCI technologies improve usability? What are some general trends and issues, such as combining different BCIs or assessing and comparing performance? This book chapter provides an overview of the different sections of this book, providing a summary of how authors address these and other questions. We also present some predictions and recommendations that ensue from our experience from discussing these and other issues with our authors and other researchers and developers within the BCI community. We conclude that, although some directions are hard to predict, the field is definitely growing and changing rapidly, and will continue doing so in the next several years
On data-driven systems analyzing, supporting and enhancing users’ interaction and experience
[EN]The research areas of Human-Computer Interaction and Software Architectures have
been traditionally treated separately, but in the literature, many authors made efforts to
merge them to build better software systems. One of the common gaps between software
engineering and usability is the lack of strategies to apply usability principles in the initial
design of software architectures. Including these principles since the early phases of software
design would help to avoid later architectural changes to include user experience
requirements. The combination of both fields (software architectures and Human-Computer
Interaction) would contribute to building better interactive software that should include the
best from both the systems and user-centered designs. In that combination, the software
architectures should enclose the fundamental structure and ideas of the system to offer the
desired quality based on sound design decisions.
Moreover, the information kept within a system is an opportunity to extract knowledge
about the system itself, its components, the software included, the users or the interaction
occurring inside. The knowledge gained from the information generated in a software
environment can be used to improve the system itself, its software, the users’ experience, and
the results. So, the combination of the areas of Knowledge Discovery and Human-Computer
Interaction offers ideal conditions to address Human-Computer-Interaction-related
challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge
Discovery in computational intelligence, and the combination of both can raise the support
of human intelligence with machine intelligence to discover new insights in a world crowded
of data.
This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven
software architectures (using Knowledge Discovery techniques) can help to improve the users'
interaction and experience within an interactive system. Specifically, it deals with how to
improve the human-computer interaction processes of different kind of stakeholders to
improve different aspects such as the user experience or the easiness to accomplish a specific
task.
Several research actions and experiments support this investigation. These research
actions included performing a systematic literature review and mapping of the literature that
was aimed at finding how the software architectures in the literature have been used to
support, analyze or enhance the human-computer interaction. Also, the actions included work
on four different research scenarios that presented common challenges in the Human-
Computer Interaction knowledge area. The case studies that fit into the scenarios selected
were chosen based on the Human-Computer Interaction challenges they present, and on the
authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss
and learn, a system that includes very large web forms, and an environment where
programmers develop code in the context of quantum computing. The development of the
experiences involved the review of more than 2700 papers (only in the literature review
phase), the analysis of the interaction of 6000 users in four different contexts or the analysis
of 500,000 quantum computing programs.
As outcomes from the experiences, some solutions are presented regarding the minimal
software artifacts to include in software architectures, the behavior they should exhibit, the
features desired in the extended software architecture, some analytic workflows and
approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction
and experience.
The results achieved led to the conclusion that, despite this is not a standard practice in
the literature, the software environments should embrace Knowledge Discovery and datadriven
principles to analyze and respond appropriately to the users’ needs and improve or
support the interaction. To adopt Knowledge Discovery and data-driven principles, the
software environments need to extend their software architectures to cover also the challenges
related to Human-Computer Interaction. Finally, to tackle the current challenges related to
the users’ interaction and experience and aiming to automate the software response to users’
actions, desires, and behaviors, the interactive systems should also include intelligent
behaviors through embracing the Artificial Intelligence procedures and techniques
Experimental Studies in Learning Technology and Child–Computer Interaction
This book is about the ways in which experiments can be employed in the context of research on learning technologies and child–computer interaction (CCI). It is directed at researchers, supporting them to employ experimental studies while increasing their quality and rigor. The book provides a complete and comprehensive description on how to design, implement, and report experiments, with a focus on and examples from CCI and learning technology research. The topics covered include an introduction to CCI and learning technologies as interdisciplinary fields of research, how to design educational interfaces and visualizations that support experimental studies, the advantages and disadvantages of a variety of experiments, methodological decisions in designing and conducting experiments (e.g. devising hypotheses and selecting measures), and the reporting of results. As well, a brief introduction on how contemporary advances in data science, artificial intelligence, and sensor data have impacted learning technology and CCI research is presented. The book details three important issues that a learning technology and CCI researcher needs to be aware of: the importance of the context, ethical considerations, and working with children. The motivation behind and emphasis of this book is helping prospective CCI and learning technology researchers (a) to evaluate the circumstances that favor (or do not favor) the use of experiments, (b) to make the necessary methodological decisions about the type and features of the experiment, (c) to design the necessary “artifacts” (e.g., prototype systems, interfaces, materials, and procedures), (d) to operationalize and conduct experimental procedures to minimize potential bias, and (e) to report the results of their studies for successful dissemination in top-tier venues (such as journals and conferences). This book is an open access publication
Seven Years after the Manifesto: Literature Review and Research Directions for Technologies in Animal Computer Interaction
As technologies diversify and become embedded in everyday lives, the technologies we expose to animals, and the new technologies being developed for animals within the field of Animal Computer Interaction (ACI) are increasing. As we approach seven years since the ACI manifesto, which grounded the field within Human Computer Interaction and Computer Science, this thematic literature review looks at the technologies developed for (non-human) animals. Technologies that are analysed include tangible and physical, haptic and wearable, olfactory, screen technology and tracking systems. The conversation explores what exactly ACI is whilst questioning what it means to be animal by considering the impact and loop between machine and animal interactivity. The findings of this review are expected to form the first grounding foundation of ACI technologies informing future research in animal computing as well as suggesting future areas for exploratio
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