Robots are becoming an integral component of our society and have great potential in being utilized as an educational technology. To promote a deeper understanding of the area, we present a review of the field of robots in education. Several prior ventures in the area are discussed (post-2000) with the help of classification criteria. The dissecting criteria include domain of the learning activity, location of the activity, the role of the robot, types of robots and types of robotic behaviour. Our overview shows that robots are primarily used to provide language, science or technology education and that a robot can take on the role of a tutor, tool or peer in the learning activity. We also present open questions and challenges in the field that emerged from the overview. The results from our overview are of interest to not only researchers in the field of human-robot interaction but also administration in educational institutes who wish to understand the wider implications of adopting robots in education.

Background Many countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting. Objective The goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review. Methods This research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed. Results This study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps. Conclusions This article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.

In this article, we present an emotion and memory model for a social robot. The model allowed the robot to create a memory account of a child’s emotional events over four individual sessions. The robot then adapted its behaviour based on the developed memory. The model was applied on the NAO robot to teach vocabulary to children while playing the popular game ‘Snakes and Ladders’. We conducted an exploratory evaluation of our model with 24 children at a primary school for 2 weeks to verify its impact on children’s long-term social engagement and overall vocabulary learning. Our preliminary results showed that the behaviour generated based on our model was able to sustain social engagement. In addition, it also helped children to improve their vocabulary. We also evaluated the impact of the positive, negative and neutral emotional feedback of the NAO robot on children’s vocabulary learning. Three groups of children (eight per group) interacted with the robot on four separate occasions over a period of 2 weeks. Our results showed that the condition where the robot displayed positive emotional feedback had a significantly positive effect on the child’s vocabulary learning performance as compared to the two other conditions: negative feedback and neutral feedback.

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In this paper, we report on the design and evaluation of a tabletop game especially created for senior citizens. The game is intended to provide leisure and fun and is played with four players on an augmented tabletop. It evolved from existing games and rules that are popular and familiar amongst senior citizens. Several aspects that are part of the gaming experience, such as immersion, flow, affect and, challenge, were assessed experimentally. The gaming experience was measured relatively by subjectively comparing user reactions across two sessions, one using a conventional board game and another using a digital tabletop version of the same game. Our results indicate that senior citizens found the tabletop version of the game to be more immersive and absorbing. We also discuss some implications to tabletop game design that can be deduced from the qualitative feedback provided by our participants.