Lexical Alignment is a phenomenon often found in human–human conversations, where the interlocutors converge during a conversation to use the same terms and phrases for the same underlying concepts. Alignment (linguistic) is a mechanism used by humans for better communication between interlocutors at various levels of linguistic knowledge and features, and one of them is lexical. The existing literature suggests that alignment has a significant role in communication between humans, and is also beneficial in human–agent communication. Various methods have been proposed in the past to measure lexical alignment in human–human conversations, and also to implement them in conversational agents. In this research, we carry out an analysis of the existing methods to measure lexical alignment and also dissect methods to implement it in a conversational agent for personalizing human–agent interactions. We propose a new set of criteria that such methods should meet and discuss the possible improvements that can be made to existing methods.

Humans often use expressions with vague terms which play a fundamental role for effective communication. These expressions are successfully modeled with fuzzy technology, but they are not usually integrated yet with Natural Language Processing models and techniques. Large-scale pre-trained language models yield excellent results in many language tasks, but they have some drawbacks such as their lack of transparency and thorough temporal reasoning capabilities. Therefore, the use of such models may provoke inconsistent or incorrect dialogues in the context of conversational agents which were aimed at providing users of intelligent systems with interactive explanations. In this paper, we propose a model for fuzzy temporal reasoning to overcome some inconsistencies detected in pre-trained language models in a specific application domain of a conversational agent carefully designed for providing users with explanations which are endowed with a good balance between naturalness and fidelity. More precisely, starting from a knowledge graph that provides an intuitive representation of the entities and relations in the application domain, we describe how to map the temporal information onto a fuzzy temporal constraint network. This formalism allows to represent imprecise temporal information and provides mechanisms for checking consistency in conversations. In addition, as a proof of concept, we have developed TimeVersa, a conversational agent which integrates the proposed model into an application domain (i.e., a virtual assistant for tourists) that requires handling imprecise temporal constraints. We illustrate in a use case how the agent can identify temporal inconsistencies and answer queries related to temporal information properly. Results after a user study report that users' perception of consistency is significantly higher in a conversation with TimeVersa than in a similar conversation using the well-known GPT-3 Large Language Model, when vague temporal information is involved. The proposed approach is a step forward for developing conversational agents operating in application domains that require temporal reasoning under uncertainty.

Explainable Artificial Intelligence (XAI) focuses on research and technology that can explain an AI system’s functioning and its underlying methods, and also on making these explanations better through personalization. Our research study investigates a natural language personalization method called lexical alignment in understanding an explanation provided by a conversational agent. The study setup was online and navigated the participants through an interaction with a conversational agent. Participants faced either an agent designed to align its responses to those of the participants, a misaligned agent, or a control condition that did not involve any dialogue. The dialogue delivered an explanation based on a pre-defined set of causes and effects. The recall and understanding of the explanations was evaluated using a combination of Yes-No questions, a Cloze test (fill-in-the-blanks), and What-style questions. The analysis of the test scores revealed a significant advantage in information recall for those who interacted with an aligning agent against the participants who either interacted with a non-aligning agent or did not go through any dialogue. The Yes-No type questions that included probes on higher-order inferences (understanding) also reflected an advantage for the participants who had an aligned dialogue against both non-aligned and no dialogue conditions. The results overall suggest a positive effect of lexical alignment on understanding of explanations.

Abstract Promoting the social-emotional development of kindergartners is of special relevance as will lay the foundations for emotion regulation in later childhood and adulthood stages. Considering that tangible storytelling tables are already used for language and literacy skills in kindergarten, we addressed the problem of designing a storytelling intervention aimed at social-emotional development suitable in such a context by using an emotional laden story as content and embedding a guidance method that can be implemented with either a human or robot guide to enhance the learning setting. The study considered two guided storytelling activities (one traditional guided by the teacher, and one in which guidance was provided by a robot) and a control condition without additional guidance. The three conditions were compared in terms of kindergartners’ enactment process, an emotion recognition test and a story recall test. The results show that the guidance method properly supported emotion naming, children involvement and goal completion during the storytelling activity whereas the intervention supported the learning gain on emotion recognition. The study revealed that both robot and human guidance did not differ significantly in the performance tests but did outperform the control. In view of the results, this research is helpful for researchers and teachers to create in an informed way a range of environments in the kindergarten class based on storytelling tables, either with or without guidance, and with or without robot support. Future work may further investigate how specific interaction issues concerning robot embodiment (e.g., voice and behavioral cues to direct children’s attention) might enhance or not the children’s performance.

The explanatory capacity of interpretable fuzzy rule-based classifiers is usually limited to offering explanations for the predicted class only. A lack of potentially useful explanations for non-predicted alternatives can be overcome by designing methods for the so-called counterfactual reasoning. Nevertheless, state-of-the-art methods for counterfactual explanation generation require special attention to human evaluation aspects, as the final decision upon the classification under consideration is left for the end user. In this paper, we first introduce novel methods for qualitative and quantitative counterfactual explanation generation. Then, we carry out a comparative analysis of qualitative explanation generation methods operating on (combinations of) linguistic terms as well as a quantitative method suggesting precise changes in feature values. Then, we propose a new metric for assessing the perceived complexity of the generated explanations. Further, we design and carry out two human evaluation experiments to assess the explanatory power of the aforementioned methods. As a major result, we show that the estimated explanation complexity correlates well with the informativeness, relevance, and readability of explanations perceived by the targeted study participants. This fact opens the door to using the new automatic complexity metric for guiding multi-objective evolutionary explainable fuzzy modeling in the near future.

Under the umbrella of smart toys, a myriad of interactive systems have addressed a variety of scenarios considering entertainment, education, sustainability, social and environmental learning through play. Tangibles and small toy robots prevail; but interaction technology based on wearables, conversational interfaces or augmented reality may also be part of this landscape to implement smart toys that are both social and/or connected. In the second edition of this workshop, we set a special focus on challenges associated to opening smart toys to different degrees of ”connectedness”, and reflecting on concerns regarding data privacy and ethics when smart toys are reframed to function in a connected way. After the pandemic, social isolation forced us to change the way we interact with each other. We are convinced that smart technologies can open new avenues for promoting social connectedness enabling more interactive playing and learning activities.

Data-driven classification algorithms have proven highly effective in a range of complex tasks. However, their output is sometimes questioned, as the reasoning behind it may remain unclear due to a high number of poorly interpretable parameters used during training. Evidence-based (factual) explanations for single classifications answer the question why a particular class is selected in terms of the given observations. On the contrary, counterfactual explanations pay attention to why the rest of classes are not selected. Accordingly, we hypothesize that providing classifiers with a combination of both factual and counterfactual explanations is likely to make them more trustworthy. In order to investigate how such explanations can be produced, we introduce a new method to generate factual and counterfactual explanations for the output of pretrained decision trees and fuzzy rule-based classifiers. Experimental results show that unification of factual and counterfactual explanations under the paradigm of fuzzy inference systems proves promising for explaining the reasoning of classification algorithms.

Background: A software sustainability model is commonly defined in terms of social, economic, technical and environmental dimensions. A key challenge is its characterization regarding sustainability requirements and their dependencies since it depends on, and varies with, the type of software system, and changes in operational contexts. Aims: With the purpose of facilitating the definition of a context-dependent software sustainability model, we introduce nichesourcing as a type of distributed problem-solving paradigm, named crowdsourcing. Method: First a set of nichesourcing requirements were identified, and an existing nichesourcing methodology, originally used in the cultural heritage domain was analyzed with respect to its applicability in Software Engineering. Results: As a result, we propose an adapted methodology for nichesourcing the knowledge on sustainability requirements and their dependencies. Strengths and challenges for crowdsourced software engineering are also identified.

The design of Tangible User Interfaces (TUIs) has often involved children. Nowadays, the term co-creation is gaining momentum and extending the already established role of children as co-designers. In this sense children become creators of new personalized experiences not only during the design process but also when using the final interactive products. Such dynamic opens new possibilities reshaping the role and the development of tangibles by providing users "building blocks" for creative experimentations. This workshop aims at bringing together researchers and practitioners from relevant disciplines and expertise to reflect on the co-creation approach, and on the possibilities that it opens for the development of innovative tools that place the users in the center of the creative process. Contributions to this workshop may address diverse aspects related to co-creation from different perspectives. The ultimate aim of the workshop is to discuss the research challenges and the pedagogical issues that need to be addressed when designing TUIs for co-creation.

In our ongoing research, we argue that storytelling activities can be used as creative tasks to stimulate creativity in children, one of the so-called 21st century skills. In this paper, we lay the foundations for our project on digitally supported storytelling, by gathering the viewpoints on storytelling and creativity expressed by local primary school teachers and reviewing methods reported in the literature. We report the main characteristics and features to consider in creative storytelling activities, and present our current work on a distributed storytelling interface for supporting children's creative skills development that meets the practical requirements found in the literature and expressed by the teachers.

User-centered design applied to non-human animals is showing to be a promising research line known as Animal Computer Interaction (ACI), aimed at improving animals' wellbeing using technology. Within this research line, intelligent systems for animal entertainment could have remarkable benefits for their mental and physical wellbeing, while providing new ways of communication and amusement between humans and animals. In order to create user-centered interactive intelligent systems for animals, we first need to understand how they spontaneously interact with technology, and develop suitable mechanisms to adapt to the animals' observed interactions and preferences. Therefore, this paper describes a pioneer study on cats' preferences and behaviors with different technological devices. It also presents the design and evaluation of a promising depth-based tracking system for the detection of cats' body parts and postures. The contributions of this work lay foundations towards providing a framework for the development of future intelligent systems for animal entertainment.

Touch displays moving autonomously, i.e., being self-actuated, are starting to be part of system prototypes reported in the literature. In the future, user interactions with such prototypes may take place while the display is moving. However, since current prototypes do not yet require this type of interaction, there is a lack of empirical evidence reporting issues related to touch input in such conditions. This leads us to propose two basic questions: Can we request users to deliver touch gestures during the actuation? Which aspects should we take into account when having touch input in these moving devices? In order to start to answer these questions, we report in this paper a first study to get an insight into how people perform and feel it when they have to carry out touch input on a self-actuated tablet. The preliminary results show that the self-actuated tablet does not necessarily need to be still during touch interaction, and that single-touch gestures based on drag or tap are preferable over others. Furthermore, the results also revealed an issue with tap gestures because of the movement of the tablet.

The direct manipulation interaction style of multitouch technology makes it an ideal mechanism for implementing learning activities for prekindergarten children. This is feasible because recent studies have shown that users in this early age range are able to perform a complete set of basic multitouch gestures. However, it is still unknown whether applications based on this interaction style can use effective communication strategies that enable these very young users to understand the multitouch nature of the interactive content that is presented to them in their everyday educational applications. This understanding is particularly important in collaborative dialogic learning scenarios in which several children may participate under the supervision of an adult instructor and in which they need to discover interactive content. In order to answer this question, this work evaluates three approaches to communicate different touch gestures to prekindergarten users. The results obtained show, firstly, that it is possible to effectively communicate these gestures using visual cues; secondly, that animated semiotic approaches are more effective and learnable than iconic approaches and, finally, that gender differences exist in some gestures due to visual–spatial cognition development differences.

Entertainment technology increases children's engagement in educational activities designed to develop abilities ranging from collaborative problem-solving and cognitive attention to self-esteem. However, little research has been done on designing educational and entertaining interactive technology for kindergarten children (up to 5 years old). Furthermore, most of the work in this area has considered traditional input devices such as the mouse and keyboard, which are not suitable for these very young children. More recently, other more intuitive means of interaction (touch and tangible interfaces) and advanced educational artifacts such as robots have emerged. In this work we therefore present a joint collaboration between technologists and kindergarten instructors to design and evaluate a technological platform using a mobile robot for kindergarten instruction, as well as an intuitive and user-friendly tangible user interface. The results obtained suggest the platform is not only usable by kindergarten children, but it also allows them to be fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity. In addition, the instructors reported that the system was well accepted and praised its versatility in use as a supporting tool for their everyday classroom activities.

Digital games for animals within Animal Computer Interaction are usually single-device oriented, however richer interactions could be delivered by considering multimodal environments and expanding the number of technological elements involved. In these playful ecosystems, animals could be either alone or accompanied by human beings, but in both cases the system should react properly to the interactions of all the players, creating more engaging and natural games. Technologically-mediated playful scenarios for animals will therefore require contextual information about the game participants, such as their location or body posture, in order to suitably adapt the system reactions. This paper presents a depth-based tracking system for cats capable of detecting their location, body posture and field of view. The proposed system could also be extended to locate and detect human gestures and track small robots, becoming a promising component in the creation of intelligent interspecies playful environments.

The advent of wearables (e.g., smartwatches, smartglasses, and digital jewelry) anticipates the need for text entry methods on very small devices. We conduct fundamental research on this topic using 3 qwerty-based soft keyboards for 3 different screen sizes, motivated by the extensive training that users have with qwerty keyboards. In addition to ZoomBoard (a soft keyboard for diminutive screens), we propose a callout-based soft keyboard and ZShift, a novel extension of the Shift pointing technique. We conducted a comprehensive user study followed by extensive analyses on performance, usability, and short-term learning. Our results show that different small screen sizes demand different types of assistance. In general, manufacturers can benefit from these findings by selecting an appropriate qwerty soft keyboard for their devices. Ultimately, this work provides designers, researchers, and practitioners with new understanding of qwerty soft keyboard design space and its scalability for tiny touchscreens.

This demonstration accompanies a paper accepted at MobileHCI'14. Back-of-device (BoD) authentication has shown to be significantly more secure than standard front-facing approaches, being BoD Shapes the most representative method found in the literature. With the aim of getting a better understanding and improving its usage, we developed BoD Taps as a novel alternative. Our experiments revealed that BoD Taps and BoD Shapes perform equally good at unlocking the device, but BoD Taps allows users to enter passwords about twice faster. Moreover, BoD Taps was perceived as being more usable and less frustrating than BoD Shapes. This demonstration showcases both authentication methods in action, aimed at comparing and discussing their features and potential improvements.

Previous work in the literature has shown that back-of-device (BoD) authentication is significantly more secure than standard front-facing approaches. However, the only BoD method available to date (Bod Shapes) is difficult to perform, especially with one hand. In this paper we propose Bod Taps, a novel approach that simplifies BoD authentication while improving its usage. A controlled evaluation with 12 users revealed that Bod Taps and Bod Shapes perform equally good at unlocking the device, but Bod Taps allows users to enter passwords about twice faster than Bod Shapes. Moreover, Bod Taps is perceived as being more usable and less frustrating than Bod Shapes, either using one or two hands.

The Ant Colony Optimization (ACO) has been a very resourceful metaheuristic over the past decade and it has been successfully used to approximately solve many static NP-Hard problems. There is a limit, however, of its applicability in the field of p2p networks; derived from the fact that such networks have the potential to evolve constantly and at a high pace, rendering the already-established results useless. In this paper we approach the problem by proposing a generic knowledge diffusion mechanism that extends the classical ACO paradigm to better deal with the p2p's dynamic nature. Focusing initially on the appearance of new resources in the network we have shown that it is possible to increase the efficiency of ant routing by a significant margin.

Creativity is a relevant characteristic for people's development as it facilitates the generation of new ideas and innovation processes. Although technology has played an important role on creativity stimulation, it still needs to be explored for a better understanding and support in the context of information and communication technologies. In this paper a basic creativity assessment model is presented and an empirical study has been conducted whose aim is to get insight into whether an interactive surface as base technology for collaborative creative tasks is promising in terms of both collaboration and creativity traits. In the study two tabletop-based platforms (a digitally-augmented, and a physical-only without computer mediation) were involved to solve a problem consisting of creating Rube-Goldberg machines. From these experiments, we have observed that in terms of creativity traits, interactive surfaces seem promising as groups working in the digital platform showed significantly more performance in fluency of thinking, were more motivated, and novelty was found near to significance. Also some issues related to collaboration and interaction were analyzed. In particular, the co-operation, the retrial fine adjustment, and the dominance showed that the properties of an interactive surface tabletop suits better for facilitating the sharing of objects and participation in conditions of co-operation by co-located participants.

Departing from creative learning foundations, this paper discusses on the suitability of interactive tables as a grounding technology to support creative learning for several reasons: support for social learning, because the subjects share a physical space as in traditional non-digital technologies, communication during the creative, experimental and reflexive process is direct and not computer-mediated, and subjects can carry out the task in parallel on the same surface. Considering reflection, discussion and creation processes in a loop, an experiment with teenagers has been conducted comparing a digital-based against a pure tangible tabletop in a task of creating entities consisting of blocks and joint elements. This preliminary study, designed to obtain initial insights about whether the grounding technology may become a promising tool to support creative learning, explores some aspects such as productivity, complexity of designs and concurrent co-manipulation. The results showed that subjects were more productive in terms of the number of solutions obtained using the non computer-mediated approach. However using the digital tabletop approach subjects design, on average, more complex or elaborate solutions in terms of the number of involved bodies and joints. Finally, an important finding was that teams established more frequently concurrent cooperation schemes in the digital tabletop condition by sharing more effectively the creation space.

Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.