This systematic review investigates how chatbots are evaluated and adopted in education; namely the methods used to assess their effectiveness, their communication modalities, and their benefits and challenges. Following the PRISMA reporting guidelines a comprehensive search was conducted across seven academic databases, covering studies published between 2014 and 2024, resulting in 124 empirical studies based on inclusion and exclusion criteria. Thematic analysis focused on evaluation criteria, advantages, and disadvantages, while data collection methods and communication modalities were analyzed descriptively. Eight key themes were identified in the assessment of educational chatbots, including technology acceptance, learning outcomes and usability. Surveys were the most common data collection method followed by interviews. Text modality dominated chatbot communication, while multimodal formats were rarely used. Reported benefits included 24/7 availability, personalized feedback, and improved motivation. However, challenges such as technical issues and academic integrity concerns were noted. Future research should explore longitudinal impacts and more inclusive assessment frameworks.

Auditory features like voice pitch and speech style significantly influence human-computer interaction, especially in driving where voice assistants provide real-time guidance. This study examined how two voice pitches (Alto and Bass) and two speech styles (Casual and Frozen) affected drivers’ cognitive and emotional responses. Eighty-four participants in a driving simulator received voice reminders from an assistant with varied auditory features while stress, heart rate variability, emotions, and task performance were recorded. Cognitive load was assessed using the NASA-TLX questionnaire. Results showed that the Frozen speech style combined with Alto pitch triggered higher stress and cognitive load, while speech style had a stronger effect than pitch on emotions. These insights aid in designing user-friendly voice assistants that reduce driver stress and improve safety. Future studies should investigate long-term effects and individual auditory differences.

There are current methodological and epistemological gaps and struggles between Human-Drone Interaction research and the field of design. We highlight five HDI design considerations and suggest a non-exhaustive list of design methods to approach them. We present an appeal to a more diverse and inclusive study of drones where current research can be balanced with a deeply qualitative and critical understanding of these flying robots through embracing design knowledge.

To be welcomed as assistant robots in our daily lives, robots must be liberated from their rigid, programmed logic and made more emotive and empathic to engage with people on their terms [1]. One of the key factors in designing and developing more human-like robots is to understand human emotions and behaviours regarding their pain empathy. This research focuses on the role of emotional touch (painful touch) in humanoid robots in the field of empathy.

In this paper, we propose a reinforcement learning (RL) mechanism for social robots to select an action based on users’ learning performance and social engagement. We applied this behavior selection mechanism to extend the emotion and memory model, which allows a robot to create a memory account of the user’s emotional events and adapt its behavior based on the developed memory. We evaluated the model in a vocabulary-learning task at a school during a children’s game involving robot interaction to see if the model results in maintaining engagement and improving vocabulary learning across the four different interaction sessions. Generally, we observed positive findings based on child vocabulary learning and sustaining social engagement during all sessions. Compared to the trends of a previous study, we observed a higher level of social engagement across sessions in terms of the duration of the user gaze toward the robot. For vocabulary retention, we saw similar trends in general but also showing high vocabulary retention across some sessions. The findings indicate the benefits of applying RL techniques that have a reward system based on multi-modal user signals or cues.

The field of human–computer interaction (HCI) is a growing area of research. However, its ascendancy and evolution is not understood in the Middle East and North Africa (MENA) region, which is knocking on the doors of innovation and technological advancements. In our analysis, we present a bibliometric and socioeconomic overview of the progress of HCI research in the MENA region. Using a pool of 10 premier venues in the discipline, we extracted 549 papers. We show that authors from high-income MENA countries are the most prolific in terms of both research output and first authorship and that authors from upper-middle-income countries are more likely to publish their work in journals. The topical focus of conducted research was also observed to vary as per the socioeconomic category to which a country belonged to. The USA emerged as the standout collaborative partner of the MENA region, and there was an observed lack of intra-MENA associations. We conclude with the assertion that additional efforts are warranted to promote collaborations amongst the region. Our work is one of the first attempts to quantitatively chart the development of HCI in the MENA region using the socioeconomic level of a country as an important predictor.

The Global South is a reference to the underdeveloped regions of the world and though it is often synonymous with the marginalisation of people through living standards and access to resources, not everyone falls under this margin. The children in the margins in the Global South encompasses those with little or no access to modern communication, technologies and academic resources. This spectrum also includes children with learning and developmental disabilities, mental and physical health issues and hostile home or school environments. Marginalization in the Global South places a significant portion of the children at an elevated risks of inequality from lack of access, knowledge and training of ICTs to digital exclusion. Moreover, the recent global pandemic has exacerbated these challenges. This workshop aims at tracing research lines and questions around methodological and technological in designing tools to support children on the margins in the Global South.

We see three different roles (peer, tutee, tutor) for humanoid robots in education. The role of a monitor or an invigilator is understudied. Therefore, in this paper, we describe a method for the social robot to act as an invigilator. We implemented this method on the Nao robot. We conducted a study to compare an active invigilator robot v.s. a passive invigilator robot. The study aimed to understand the participant’s perception of the robot in the role of an invigilator. We found that the robot was highly rated as an invigilator regardless of the condition. Participants were generally satisfied with the use of the robot as an invigilator. Participants rated the active robot invigilator to be more human-like and responsive as compared to the passive one. The findings highlight the applicability of the role of a robot invigilator in education and call for a more careful investigation in the future.

Domestic robotic entities are on the rise, out of which, domestic drones are taking place in our society as one of the upcoming interactive technologies that we will see in our daily lives. In this paper, we scope for research literature that addresses the use of domestic drones within our environments to understand the current usage as well as identifying future research directions. After performing a search based collection of relevant papers in the ACM digital library (N=61 papers), we analysed the drone's application areas, their interaction modalities, the target users, and the level of autonomy of the proposed systems. The results show interesting trends in the modalities of interaction (visual projection combined with hand/foot gestures) as well as important research gaps such as child-drone interaction, and the use of drones for healthcare or education, given that currently most use cases for domestic drones are generic in nature.

Attention is an essential mental process that is important to achieve learning progress. We cannot get better in our academic learning unless we concentrate our attention on the person giving the educational material, such as the teacher or trainer. Children with Autism Spectrum Disorder (ASD) may have attention difficulties that can directly influence their academic skills. In recent years, robot intervention in autism therapy and assessment is becoming a popular research topic due to its role in enhancing children's attention more than a regular human therapist, as well as, the increasing number of autism children compared to the availability of professional therapists. Robot intervention helps in reducing therapy time and makes early therapeutics sessions easier and much promising. Many researches have been conducted to develop robot intervention techniques for ASD children, and some methods have already been used to assess autistic individuals' attention during the robot intervention sessions. Yet, the existing attention assessment methods are either very complex or simple with one measured interaction cue only. This paper presents a practical and low-cost automatic approach to assess autistic individuals' attention during robot intervention; addressing multiple interaction cues. Experimental results show that the proposed attention assessment system could accurately measure the child attention and enhance therapy progress. This automatic attention system can open a new era for utilizing technologies to monitor students' attentions in the class to enhance educational systems.

Depictions of robots and AIs in popular science fiction movies and shows have the potential to showcase visions of Human-Robot Interaction (HRI) to the general public and computer science researchers alike. In contrast, studies on the referral, usage, and appropriation of these portrayals by computer scientists in their research publications is an academic void at present. However, such investigations are critical to better understand the potential utility and latent shortcomings of science fiction robots for future HRI research, innovation, and education. To address this research gap, this study investigates the overall presence, nature, and frequency of referrals of 18 popular science fiction robots in the Association for Computing Machinery (ACM) Digital Library. These robots were either portrayed in various movies and subsequently inducted into the Robot Hall of Fame, created by Carnegie Mellon University in 2003, or were top-ranked in a user-curated Internet Movie Database (IMDB) list. To do so, we performed full-text search and retrieval queries of all 18 robots in the ACM Digital Library. In total, we identified 121 relevant mentions, across 102 individual publications, in a time span from 1973 to 2017. These 121 mentions were then qualitatively analysed to determine the nature of the robot mentions. Our results indicate that the robot attributes of voice or dialogue were emerging as a popularly mentioned element. In addition, we find that research papers of philosophical nature mention sci-fi robots more frequently than papers of technical or theoretical nature. We also observe that the dystopian element of science fiction is under-utilised, with the majority of robot mentions exhibiting neutral or utopian characteristics. In conclusion, we speculate on our results and present possible avenues of future HRI research on the topic.

In this paper, we present a Child-Robot Interaction (CRI) study that applies our emotion and memory model on the social robot in the wild in a mathematics learning scenario. The rationale to conduct this study was to explore the effects of our model on children's engagement and learning in a real-life scenario and also to further emphasise the value of our model. We conducted an exploratory long-term CRI study, where the robot used the personalisation mechanism based on our emotion and memory model to understand its effects in terms of improving children's learning and sustaining social engagement on the Mathematics task in a long-term interaction. Our results showed that in a condition, where our model was implemented on the social robot, children showed the higher level of social engagement. Additionally, their learning performance based on calculating area and perimeter of regular and irregular shapes was also better in terms of their test scores.

In this paper, we present our early findings on the utilization of a social robot during the formal interview process. We implemented a mechanism that enabled the robot to ask context-aware questions based on the data based on the resume or linked-in profile of the applicant. Later, we conducted an exploratory between-subject evaluation with 8 adult participants to find the difference in the duration of applicants responses given to the NAO robot and to the human interviewer. Our results didn't find the significant difference in terms of participant responses to human and robotic interviewers.

The HAI conference is the premier discussion venue on the topic of Human Agent Interaction. In this paper we present our findings from the scientometric analysis of full papers from the HAI conference since its inception to date. We extracted various bibliometric measures and qualitatively coded our sample of 107 full papers over the 4 years of the conference. Our results show that the conference has not really grown rapidly and attracts papers from predominantly Asian Pacific regions. User studies were the common research methodology undertaken in HAI papers and humanoid robots are the popular agent of choice. Domains such as Education and Health were surprisingly underrepresented whereas communication was the focus of almost half of the papers. We also report on a mini comparison with the ICSR and IVA conference as a bench-marking strategy, which provides us with some reflections on how the HAI conference can be moved forward. In conclusion, we speculate on our findings and provide some insights to the organizers and steering committee of the HAI conference.

One of the known challenges in Children–Robot Interaction (cHRI) is to sustain children’s engagement during long-term interactions with robots. Researchers have hypothesized that robots that can adapt to children’s affective states and can also learn from the environment can result in sustaining engagement during cHRI. Recently, researchers have conducted a range of studies where robots portray different social capabilities and have shown that it has positively influenced children’s engagement. However, despite an immense body of research on implementation of different adaptive social robots, a pivotal question remains unanswered: Which adaptations portrayed by a robot can result in maintaining long-term social engagement during cHRI? In other words, what are the appropriate and effective adaptations portrayed by a robot that will sustain social engagement for an extended number of interactions? In this article, we report on a study conducted with three groups of children who played a snakes and ladders game with the NAO robot to address the aforementioned question. The NAO performed 1) game-based adaptations, 2) emotion-based adaptations, and 3) memory-based adaptation. Our results showed that emotion-based adaptations were found out to be most effective, followed by memory-based adaptations. Game adaptation didn’t result in sustaining long-term social engagement.

One of the known challenges in Children Robot Interaction (cHRI) is to sustain children's engagement for long-term interactions with robots. Researchers have hypothesised that robots that can adapt to children's affective states, and can also learn from the environment, resulting in sustained engagement during cHRI. In this paper, we report on a study conducted with three groups of children who played a snakes and ladders game with the NAO robot. The NAO performed 1) Game based adaptations, 2) Emotion based adaptations and 3) Memory based adaptation. The purpose of this study was to find which particular condition resulted in maintaining engagement over a certain period of time. Our results show that adaptations performed by the robot, in general, were able to maintain long-term engagement. However, we did not find any significant effect of one adaptation over another on engagement, social presence and perceived support.

Science fiction media has had a long lasting influence on the progression of interactive technology, however recently contradictions are emerging in the development of the two disciplines. Therefore, in this exploratory position paper we report on the insights attained through a day long workshop amongst scientists and researchers on how the collaboration between science fiction and Human Computer Interaction (HCI) can be advanced. Discussions in the workshop focused on detailing the relationship between HCI and science fiction. In conclusion, as our main contribution an action plan and agenda is presented for facilitating deeper influences amongst the two disciplines.

In order to establish a long-term relationship between a robot and a child, robots need to learn from the environment, adapt to specific user needs and display behaviours and roles accordingly. Literature shows that certain robot behaviours could negatively impact child's learning and performance. Therefore, the purpose of the present study is to not only understand teacher's opinion on the existing effective social behaviours and roles but also to understand novel behaviours that can positively influence children performance in a language learning setting. In this paper, we present our results based on interviews conducted with 8 language teachers to get their opinion on how a robot can efficiently perform behaviour adaptation to influence learning and achieve long-term engagement. We also present results on future directions extracted from the interviews with teachers.

In this paper, we present our idea about applying an adaptive social mobile agent in a game based scenario to support foreign language vocabulary learning. We hypothesize that through implementing an adaptive agent, we may mitigate the problem of a loss in child engagement or may also prolong the time a child takes to lose interest. We then present details on architecture and implementation of an adaptive social mobile agent.

In this paper we present a survey based approach towards the design of a mobile application meant to function as an electronic version of a child health book for use in Sri Lanka. Through the use of persuasive technology the application aims to inculcate positive behavioural changes in Sri Lankan parents in order to facilitate the well being of their children. We report on a survey conducted with parents living in urban areas in Colombo which led to the formulation of design guidelines for the application. The application was then evaluated with a set of parents. Results from both the survey and application show that parents held great importance to the privacy and security of their child's data. Some aspects of the paper based health book were deemed to be at times unclear; such as the developmental checks. In general parents were positive about the prospects of an electronic health book. We conclude our paper with future directions of the digital health book.

In this paper, we will be introducing, advocating and emphasising the role of an adaptive mobile agent in a game based scenario for supporting foreign language vocabulary learning. We will also be discussing our motivation to design a game for foreign language word learning. We will then be presenting an idea of a possible game design and also discuss the role of an adaptive agent in this game.

In this paper the nexus between fictional and real robots in Human Robot Interaction (HRI) is explored. We claim that design guidelines for HRI must not be borrowed from fiction blindly, as contradictions between the two may emerge with respect to what is desired by the human user. To understand human perception of robots appearing in movies we analyse viewing statistics and qualitative comments of a set of YouTube videos comprising of fictional and real robots. Analysis of the viewing statistics showed that real robots are more popular. Furthermore, analysis of the comments showed that two real robots (Nao and Shakey) generated significantly more positive comments and significantly more attributions of usage in human society as compared to the two fictional robots (AstroBoy and HAL9000). Based on the sample of robots considered in this research, our results reveal that contrary to expectation humans are more exposed to real robots and are more preferred, and we conclude by reasserting the contradiction that emerges between real and fictional robots.

In this paper we introduce and evaluate a concept of a drone agent that can support us to keep the environment clean. The drone has four main functions: (1) find a waste item, (2) persuade the user to pick up the item, (3) lead the user to the nearest trash bin, (4) communicate with the user when the job is done. We prototyped three types of persuasion effects with the drone (Visual, Audio, and Visual+Audio) and evaluated them through an online study with eighty two participants. The results reveal that interest in the drone technology varied significantly between developed and developing countries, with individuals in developing countries having higher ratings for drone related persuasion, compliance, pleasantness and sensibility; gender differences also emerged. Finally, evaluation results led to many design recommendations that will increase the functionality and attractiveness and usage potential of the proposed technology.

We observe that in comparison to other media; online videos are a powerful outreach instrument for Computing technologies in general and specifically for Human Robot Interaction (HRI). Our experience in creating demos, scenarios and educational videos (we present two anecdotal accounts of educational HRI videos) leads us to believe that such modalities can have large pedagogical value if they are designed and conveyed appropriately. We also found that the rapid hand drawing (exemplified through fast frames in video) is an interesting technique to propagate science facts around social media. We also discuss the prospects of utilising standard MOOC's as a medium to teach HRI and thereby present a proposal of a (nano-MOOC). Furthermore, we also discuss the main challenge of being able to promote retention through HRI pedagogical material as there may be a tendency of withdrawal to deeply technical content. In conclusion, we present guidelines to promote the uptake of HRI across not only educational institutes but also the general public.

Meetings are an integral part of the work place and society in general. Research in Computer Supported Cooperative Work attempts to facilitate and make the process of meetings more effective. Our vision is that the incorporation of social robots in such human-human collaborative settings can assist and improve the effectiveness of a meeting. In this paper we present an empirical study in which pairs of participants collaborate in a meeting scenario with a Nao humanoid robot. Using a within-subjects design, we manipulated the robot's role within the meeting as being either “active” versus “passive”/“service-oriented”. Our results show that the more active robot was deemed as more more alive and social, had the participants more emotionally involved and caused more verbal engagement from the participants as compared to a passive service robot. In conclusion, we speculate on the inclusion of a collaborative robot as a meeting partner.

Speech Recognition has not fully permeated in our interaction with devices. Therefore we advocate a speech recognition friendly artificial language (ROILA) that initially was shown to outperform English, however under constraints. ROILA is intended to be used to talk to robots and therefore in this paper we present an experimental study where the recognition of ROILA is compared to English when speech is input using a robot's microphones and both when the robot's head is moving and stationary. Our results show that there was no significant difference between ROILA and English but that the type of microphone and robot's head movement had a significant effect. In conclusion we suggest implications for Human Robot (Speech) Interaction.

In our research we present a speech recognition friendly artificial language that is specially designed and implemented for humans to talk to robots. We call this language Robot Interaction Language (ROILA). In this paper, we describe our current work with ROILA that utilizes the Nao humanoid robot. Our current demo implementation will allow users to interact with the Nao robot without the usage of any external laptops or microphones. Therefore the purpose of our demo is two-fold: 1) to demonstrate ``live" that ROILA has improved recognition accuracy over English and 2) to demonstrate that users can interact with the Nao robot in ROILA without the use of any external devices.

In this study we have tried to determine if the cultural background of children has an influence on how they interact with robots. Children of different age groups and cultures played a card guessing game with a robot (iCat). By using perception tests to evaluate the children's emotional response it was revealed that children from South Asia (Pakistani) were much more expressive than European children (Dutch) and younger children were more expressive than the older ones in the context of child robot interaction.

The possibility of improving speech recognition accuracy within human computer and robot interaction by having users interact in a constrained natural language or an artificial language has been explored. However, what has not been evaluated yet is the user acceptance of such forms of interaction. In this paper we discuss two separate but similar studies which were aimed at assessing the usability of constrained and artificial languages in contrast to natural languages. The interaction context was implemented in a game played between children and the iCat robot. We subjectively measured various variables related to gaming experience and interacting in the new languages. Our results reveal that there were no significant differences in the user experience across the two interaction mediums in comparison to natural languages.

This paper outlines the design requirements of a GPS car navigation system for the elderly and the young by proposing a set of new guidelines for designing such systems. Our study revealed that younger drivers had a more positive user experience as compared to the elderly drivers. This paper also identifies a number of advanced features that a routing system should have for satisfying both the elderly and younger drivers on road. In conclusion, we will discuss the key design recommendations that were derived from the study.

In this paper we present an application that helps to motivate the elderly in maintaining an independent healthy life style. With this application elderly people don't need to memorize the details --- they will be informed round the clock about their diet and exercise schedules-freeing their memory for something else. The application was designed and implemented in a participatory manner. The early results from the evaluation show that the application has potential in enabling the elderly to maintain a healthy life style.

This paper discusses a design case, which explores the potential of psychophysiological measures as an input technique for social gaming applications intended for children. aMAZEd is an example of a tabletop mixed reality game that supports social interaction between players through and around the game. It is clear that sensing technology used to obtain psychophysiological measures needs to be improved and there is still a range of solutions that need to be explored. However, our experience shows that psychophysiological input appeals to children and can be a fun element of games supporting social interaction among players.

Robots can exhibit life like behavior, but are according to traditional definitions not alive. Current robot users are confronted with an ambiguous entity and it is important to understand the users perception of these robots. This study analyses if a robot's intelligence and its agreeableness influence its perceived animacy. The robot's animacy was measured, amongst other measurements, by the users' hesitation to switch it off. The results show that participants hesitated three times as long to switch off an agreeable and intelligent robot as compared to a non agreeable and unintelligent robot. The robots' intelligence had a significant influence on its perceived animacy. Our results suggest that interactive robots should be intelligent and exhibit an agreeable attitude to maximize its perceived animacy.

Robots are being introduced in our society but their social status is still unclear. A critical issue is if the robot's exhibition of intelligent life-like behavior leads to the users' perception of animacy. The ultimate test for the life-likeness of a robot is to kill it. We therefore conducted an experiment in which the robot's intelligence and the participants' gender were the independent variables and the users' destructive behavior of the robot the dependent variables. Several practical and methodological problems compromised the acquired data, but we can conclude that the robot's intelligence had a significant influence on the users' destructive behavior. We discuss the encountered problems and the possible application of this animacy measuring method.