AI literacy is an emerging research area that increasingly incorporates new forms of computational intelligence, creating opportunities to enrich human learning and interactive experiences. Our scoping review examines design interventions and discourses within AI literacy and games to identify and characterize the learning experiences that prior research has sought to support. Drawing from 45 papers, we identified and analyzed 48 unique design artifacts, including game‑based learning prototypes and gamified systems. We constructed a comprehensive matrix charting each artifact’s game or gamification approach, platform, AI literacy focus, game design elements, player requirements, modality, and open‑source availability, providing a detailed view of how AI literacy is represented across these systems. Building on this matrix, we identify nine design suggestions that illustrate how specific design choices shape learners’ knowledge, skills, and experiences with AI. Our work clarifies game‑based AI literacy interventions and offers actionable suggestions for designing future systems that effectively leverage games and gamification to support AI learning.

Gamification has been widely applied in educational contexts to enhance students' motivation and engagement. Its effectiveness has been shown to vary based on individual user preferences, such as age, gender, and player type. This study investigates the relationship between player types and user experience in StandByMe, a gamified educational platform designed to raise awareness about gender-based violence. A total of 61 high school students used the platform for about 35 minutes and completed a user experience questionnaire and the Hexad scale for player types. Results indicate that Free spirits reported higher motivation and overall user experience, while Achievers exhibited lower engagement, possibly due to a lack of clearly structured challenges. Socializers and Disruptors showed no significant relation with user experience. Additionally, demographic factors such as age and gender were related to participants' fun levels and perception of challenge. These findings highlight how users' player type predicts the user experience of a gameful system and should be considered during the design phase. Future research should explore adaptive gamification approaches and specific design modifications to enhance user experience across all player types, both within the StandByMe platform and, more broadly, in gameful systems for the education of sensitive topics.

Gamification is a widely embraced strategy in education, employed to enhance motivation and foster effective learning outcomes. However, its application to sensitive topics has been scarcely explored and remains a subject of debate. While gamification holds the potential to elevate engagement and motivation in the learning process, it also introduces certain limitations, such as the risk of trivializing the subject matter and diverting attention from the core content. This paper delves into an investigation, supported by both a literature review and a survey conducted among professionals, focusing on the implementation of gamification mechanisms in child sexual abuse education. By examining insights gathered from prior research and engaging with experts, the paper identifies key facets of gamification mechanisms in the design of educational interventions addressing child sexual abuse and related topics. The aim is to contribute to a nuanced understanding and effective utilization of gamification when addressing sensitive topics in education, offering preliminary guidelines for practitioners.

Gamification and tangible user interfaces have been shown to enhance pupils’ engagement and their learning experiences. This study presents an evaluation of a simple gamified version of a tangible Internet of Things device (SMARTER) to support math learning. Twenty-one elementary school children participated in a workshop, interacting with the system and providing feedback. Results indicate good usability and a positive attitude toward the system. Children generally liked all the aspects, although the focus on mathematics was slightly lower appreciated. The study highlights the potential of integrating tangible user interfaces and gamified systems to enhance pupils’ engagement in education.

Gender-based violence is widely recognized as a significant societal issue, necessitating a concerted effort to raise awareness about its manifestations and consequences. Serious games have been often used to address the topic, particularly among the younger population. On the other hand, the use of gamification (i.e., integrating game elements to enhance user engagement with the subject) to raise awareness of gender-based violence remains unexplored. To address this gap, we developed a gamified platform aimed at raising awareness of gender-based violence and in particular of the role of gender stereotypes, in young adults. This paper presents the findings of our preliminary mixed-methods evaluation and a comparison between two versions of the platform: one employing cooperative gamification, and the other one based on an individual game modality. While the quantitative results indicate that the current platform may not be sufficient to have a positive effect in participants’ awareness of gender-based violence and attitudes toward bystander behavior, qualitative analyses yield crucial insights into participants’ positive evaluation of the cooperative mode. These analyses provide valuable information for future developments of the platform, and contribute to the exploration of gamification applied to sensitive topics.

In the current Work in Progress we present the SmartGame, a gamified web-app designed to support children in learning math and connected to an already existing tangible IOT device called SMARTER. Through introducing a cooperative modality and the union of digital and tangible advancements in technology, we also aim to foster interpersonal relationships in children from primary school, who suffered a lack of social interactions in person due to the recent pandemic. In the current project, we will study different possibilities of cooperation within the SmartGame, along with the ways in which teachers can personalize the activities and the gamification design based on students’ needs. Finally, we will test the web-app usability, user experience, effectiveness in supporting students’ education, and outcomes in fostering interpersonal relationships.

Modeling is an essential and challenging activity in any engineering environment. It implies some hard-to-train skills such as abstraction and communication. Teachers, project leaders, and tool vendors have a hard time teaching or training their students, co-workers, or users. Gamification refers to the exploitation of gaming mechanisms for serious purposes, like promoting behavioral changes, soliciting participation and engagement in activities, etc. We investigate the introduction of gaming mechanisms in modeling tasks with the primary goal of supporting learning/training. The result has been the realization of a gamified modeling environment named PapyGame. In this article, we present the approach adopted for PapyGame implementation, the details on the gamification elements involved, and the derived conceptual architecture required for applying gamification in any modeling environment. Moreover, to demonstrate the benefits of using PapyGame for learning/training modeling, a set of user experience evaluations have been conducted. Correspondingly, we report the obtained results together with a set of future challenges we consider as critical to make gamified modeling a more effective education/training approach.

Mobility plays a fundamental role in modern cities. How citizens experience the urban environment, access city core services, and participate in city life, strongly depends on its mobility organization and efficiency. The challenges that municipalities face are very ambitious: on the one hand, administrators must guarantee their citizens the right to mobility and to easily access local services; on the other hand, they need to minimize the economic, social, and environmental costs of the mobility system. Municipalities are increasingly facing problems of traffic congestion, road safety, energy dependency and air pollution, and therefore encouraging a shift towards sustainable mobility habits based on active mobility is of central importance. Active modes, such as cycling, should be particularly encouraged, especially for local recurrent journeys (e.g., home–to–school, home–to–work). In this context, addressing and mitigating commuter-generated traffic requires engaging public and private stakeholders through innovative and collaborative approaches that focus not only on supply (e.g., roads and vehicles) but also on transportation demand management. In this paper, we present and end-to-end solution, called Play&Go Corporate, for enabling urban cyclability and its concrete exploitation in the realization of a home-to-work sustainable mobility campaign (i.e., BIKE2 WORK) targeting employees of public and private companies. To evaluate the effectiveness of the proposed solution we developed two analyses: the first to carefully analyze the user experience and any behaviour change related to the BIKE2 WORK mobility campaign, and the second to demonstrate how exploiting the collected data we can potentially inform and guide the involved municipality (i.e., Ferrara, a city in Northern Italy) in improving urban cyclability.

The COVID-19 emergency has posed many challenges to the worldwide school system leading to school closures and massive adoption of distance education. These events affected not only the way education is delivered but also the overall school community’s wellbeing and cohesion. In this paper, we present a playful education platform originally designed to promote sustainable mobility in schools that has been adapted to support distance learning and community engagement during the health emergency. In the original version of the platform, the home-school distances traveled by students with sustainable means contributed to the advancement of the whole class in a collective virtual trip associated with playful learning material. Conversely, in a revised version of the platform adapted to the new context, students could advance in the virtual trip by reporting the good deeds performed at home. Findings from 161 questionnaires completed by teachers, families, and students, as well as results from online workshops with students, and the analysis of log files at the end of the school year revealed the opportunities and limitations of converting a playful activity conceived for being experienced in class into an online activity to be completed at home. The results show that the adapted version contributed to the school community cohesion and provided a positive experience to all its members, even though it was not able to completely overcome the generalized feeling of isolation. This paper contributes to understanding the social value of collaborative and playful digital activities that involve the entire school community, showing how technology can impact education and support communities in times of crisis.

Social connections shape our behaviour because of peer pressure and social contagion. This phenomenon is amplified in online networks by particularly influential individuals: influencers. Although this concept originated in social media, recent research shows how influencers can also exist in games and affect players' long-term retention. Prolonged retention caused by influencers could benefit gameful systems, especially if the system's goal is positive behavioural change. Retention is desirable because it can aid in internalizing new habits. Therefore, we investigated retention influencers' presence within a location-based persuasive gamified system (Play&Go) and their influence on other behaviours (i.e., the pursuit of a gamification goal), via social network analysis techniques. Results show how retention influencers exist in Play&Go and how studying different influence types (which push the systems' goals) may lead to different influencer groups. Our findings emphasize the importance of social mechanics in location-based gamification and discuss the value of understanding a player community to improve game design.

Providing mobility services effectively to residents and visitors is a complex socio-technical system task to city public managers. Smart mobility systems aim to support the efficient exploitation of city transport facilities and sustainable mobility within the urban environment. People need to travel quickly and conveniently between locations at different scales, ranging from a few blocks within a city to a journey across cities. At the same time, goods need to be timely delivered, considering both the users and the businesses' needs. Several cities indicated an interest in using Autonomous Vehicles (AV) for the “last-mile” mobility services in the last few years. With them, it seems to be easier to get people and goods around using fewer vehicles. In this context, Autonomous Shuttles (AS) are beginning to be thought of as a new mobility/delivery service into the city center where narrow streets are not easily served by traditional buses. They allow them to perform critical areas with minimal new infrastructure and reduce noise and pollution. The article analyses the state-of-art on autonomous shuttles by proposing four application scenarios targeting the last-mile delivery of goods, the tourist experiences, and the shared and integrated mobility. Furthermore, we contribute with the proposition of the Autonomous Shuttles-as-a service (ASaaS) concept as the key pillar for the realization of innovative and sustainable proximity mobility. Our research proposed new research challenges for ASaaS, and we discuss social implications and governance challenges that consider user engagement and sustainability. It also recommended extending new research to focus on simulation and machine learning techniques for last-mile mobility planning and explore the journeys tracking certification via artificial intelligence and blockchain-based techniques.

An effective, efficient, and ecological transport service needs a decision support system to inform the administrations, while intelligently assisting citizens' daily transportation choices. This work presents a full-fledged Gamification Platform to develop and run sustainable mobility campaigns promoting individual green mobility behaviors. We organize geolocalized and temporal information on users' tracked trips into a rich dataset that decision-makers can exploit to analyze citizens' daily transportation choices and balance the demand and the offer of the mobility ecosystem. Through the Gamification Platform, we define three different use case scenarios - i.e., mobility within the city, home-work mobility, and home-school mobility. We also evaluate the platform according to both gameful design guidelines and persuasive technology best practices. Our findings show how long-term retention and engagement can be achieved when the gameful system's design and maintenance are assisted by the Gamification Platform, merging both administrative requirements and users' needs towards an iteratively adaptive and personalized experience.

In social and online media, influencers have traditionally been understood as highly visible individuals. Recent outcomes suggest that people are likely to mimic influencers’ behavior, which can be exploited, for instance, in marketing strategies. Also in the Games User Research field, the interest in studying player social networks has emerged due to the heavy reliance on online influencers in marketing campaigns for games, as well as in keeping players engaged. Despite the inherent value of those individuals, it is still difficult to identify influencers, as the definition of influencers is a debated topic. Thus, how can we identify influencers, and are they indeed the individuals impacting others’ behavior? In this work, we focus on influence in retention to verify whether central players impacted others’ permanence in the game. We identified the central players in the social network built from the competitive player-vs-player (PvP) multiplayer (Crucible) matches in the online shooter Destiny. Then, we computed influence scores for each player evaluating the increase in similarity over time between two connected individuals. In this paper, we were able to show the first indications that the traditional metrics for influencers do not necessarily apply for games. On the contrary, we found that the group of central players was distinct from the group of influential players, defined as the individuals with the highest influence scores. Then, we provide an analysis of the two groups.

Players’ retainment can be fostered by investigating whether the game elements players are interacting with are to their liking and tailoring game dynamics to meet their preferences. Thus, adaptive gameplay is a widely interesting topic in both the Game User Research field and the game industry. Considering that explicit information on players’ preferences often lacks, alternative approaches are needed. This task becomes even more challenging when the gameplay data available is limited due to the simplicity of the system employed, as it occurs in gameful systems in contrast to complex entertainment games or serious games. In this work, we propose an algorithm that exploits user behaviors as an implicit component to compute players’ preferences by measuring their level of activity. The application domain is a persuasive gameful system, and the customizable game elements are single-player challenges. The proposed algorithm uses offline gameplay data to compute a preference score for every viable option. The outcomes are then compared against a ground truth calculated from players’ in-game choices. Our findings suggest that players’ behaviors can be used to inform the generation of tailored game elements.

When designing a serious game it is paramount to take into account that the players' performance may greatly vary. In many types of games the performance will impact the game experience, as it is related to a point acquisition mechanic. In specific contexts, such as multi-player non-competitive or collaborative games, the designer may desire to minimize this variability, reducing the difference in game progression between low-performing and high-performing players. In this paper we detail such a context: an educational serious game for sustainability addressed to classes of a primary school, where the low performance of a class may not be necessarily related to the children's effort. We thus present and evaluate a novel approach for the calibration of the game dynamics for achieving a more even player experience.

Gamification is increasingly used to build solutions for driving the behaviour of target users' populations. Gameful systems are typically exploited to keep users' involvement in certain activities and/or to modify an initial behaviour through game-like elements, such as awarding points, submitting challenges and/or fostering competition and cooperation with other players. Gamification mechanisms are well-defined and composed of different ingredients that have to be correctly amalgamated together; among these we find single/multi-player challenges targeted to reach a certain goal and providing an adequate award for compensation. Since the current approaches are largely based on hand-coding/tuning, when the game grows in its complexity, keeping track of all the mechanisms and maintaining the implementation can become error-prone and tedious activities. In this paper, we describe a multi-level modelling approach for the definition of gamification mechanisms, from their design to their deployment and runtime adaptation. The approach is implemented by means of JetBrains MPS, a text-based meta-modelling framework, and validated using two gameful systems in the Education and Mobility domains.

In this paper, we present a playful digital activity for primary school classrooms that promotes sustainable and active mobility by leveraging the daily journey to school into a collaborative educational experience. In the class game, stretches of distance travelled in a sustainable way by each child contributes to the advancement of the whole school on a collective virtual trip. During the trip, several virtual stops are associated with the discovery of playful learning material. The approach has been evaluated in a primary school with 87 pupils and 6 teachers actively involved in the learning activity for 12 continuous weeks. The findings from the questionnaires with parents and the interviews with teachers show a positive effect in terms of children's behavioural change as well as educational value. Indications on the use of class and school collaborative gamification activities for supporting sustainable behavioural change are discussed.

According to a recent UN report, continuing population growth and urbanization are expected to increase the world’s urban population by 2.5 billion people by 2050, with 2.9 billion extra vehicles. This massive growth in both population and number of vehicles, together with urban transformation and a trend toward mega cities, creates greater and more challenges for achieving smart transportation goals in smart cities. Therefore, new and more integrated modes of transportation, and environment friendly solutions are required to accommodate the rising demands of high liveability in smarter cities that offer safe, secure, affordable, reliable and sustainable transportation in old and new markets alike.

UAV-based systems are systems that are composed of a team of drones, various devices (like movable cameras, sensors), and human agents, which collaborate each other to accomplish defined missions. Since humans are constituent part of these systems, UAV-based systems are both mission-critical and safety-critical. Moreover, these systems are requested to operate in potentially unpredictable and unknown environments. A model of the environment describing, e.g. obstacles, no-fly zones, wind and weather conditions might be available, however, the assumption that such model is both correct and complete is often wrong. In this paper, we describe a novel approach for managing the run-time adaptation of UAV-based systems. Our approach is based on a generic collective adaptation engine that addresses collective adaptation problems in a decentralized fashion, operates at run-time, and enables the addition of new entities at any time. Moreover, our approach dynamically understands which parts of the system should be selected to solve an adaptation issue. The feasibility and scalability of the approach have been empirically evaluated in the context of a private company surveillance scenario.

A key challenge posed by the Internet of Services is that applications need to cope with a continuously changing environment, both in terms of the context in which they operate and of the services, users and providers involved. Differently from applications where traditional change detection and adaptation mechanisms can be used, the Internet of Services requires systems that are adaptive by design. In this paper we present a design for adaptation framework supporting the modeling, development and operation of service based applications operating in highly dynamic environments. The approach exploits advanced techniques for dynamic and incremental service composition, allowing to effectively deal with changes occurring at different levels in the system. An implementation of the proposed solution is presented and evaluated on a real-world scenario from the Smart Urban Mobility domain.

The idea to build systems based on services, by reusing and combining software made available independently via different technologies and channels and dynamically organizing them into coherent processes, has a very well recognized potential. Achieving this potential stands crucially on the ability to recognize and exploit the context in which such applications operate, in terms of the available services, of the actual setup at run-time, and of the interaction with human actors. Changing contexts require run-time reaction, by adapting the ongoing overall process enacted by the service-based system to unexpected deviations. Continuous context-aware adaptation is hencefore a strong requirement in this setting. In this paper, we propose a service delivery platform designed for the continuous context-aware adaptation of service-based systems, based on the idea of monitoring the underlying context via a hierarchical model, and using the context to drive the choice and execution of adaptive pervasive flows. We describe the approach through an example from the smart cities e-mobility domain.

Data-flow requirements is an important aspect of service composition. Although several approaches have been proposed to specify data-flow requirements, they cannot be efficiently exploited in dynamic setting, for example, where the composition participants (i.e., component services) need to be dynamically replaced. In this paper, we propose a new modeling methodology for data-flow requirements, in which we explicitly distinguish a data model of a composite service from data models of component services. We show that following our methodology, a composition can be adjusted to various dynamic changes with significantly less effort. We implement our solution using planning techniques and make its basic evaluation on a scenario from the travel domain.

We propose a comprehensive framework for adaptivity of service-based applications, which exploits the concept of process fragments as a way to model reusable process knowledge and to allow for the dynamic, incremental, context-aware composition of such fragments into adaptable service-based applications. The framework provides a set of adaptation mechanisms that, combined through adaptation strategies, are able to solve complex adaptation problems. An implementation of the proposed solution is presented and evaluated on a real world scenario from the logistics domain.

Adaptivity is a key feature of service-based systems to fully exploit the advantages offered by the service paradigm. In this paper we present a comprehensive framework that can be used to define and support highly adaptable context-aware service-based business processes. In our approach, all the adaptation-related tasks, from detecting an adaptation problem to finding a solution and applying it to a running process instance, are performed automatically at run time. We also show how the framework has been implemented and applied to a real-world scenario from the logistics domain.

A critical aspect for pervasive computing is the possibility to discover and use process knowledge at run time depending on the specific context. This can be achieved by using an underlying service-based application and exploiting its features in terms of dynamic service discovery, selection, and composition. Pervasive process fragments represent a service-based tool that allows to model incomplete and contextual knowledge. We provide a solution to automatically compose such fragments into complete processes, according to a specific context and specific goals. We compute the solution by encoding process knowledge, domain knowledge and goals into an AI planning problem. We evaluate our approach on different scenarios stress testing the main characteristics of pervasive process fragments.

In this paper we introduce a new modeling tool for constraint handling in the area of workflow technology. The constraint handlers can be used to improve the quality of business processes but without changing already existing business logic. Todays workflow languages provide no possibility to model constraints and the actions in case the constraints get violated explicitly. Fault and event handling mechanisms to react to events not expected in normal executions are only provided by the BPEL language. Using BPEL as workflow language we integrate the constraint handling extension without changing any existing semantics in a smart way. In our approach we use this fault and event handling mechanisms to extend the BPEL language with a constraint handling mechanism. By integrating this constraint handling tool into the BPEL language we provide an approach for quality driven process modeling with the BPEL language.

Several approaches have been proposed to tackle the selection of distributed processes described as semantic Web services. However, their practical applicability in real composition scenarios is still an open question. Addressing this problem requires on the one hand to deal with services described as stateful business processes and, on the other hand, to consider complex selection requirements concerning both the service interface and its behavior. In fact, in most existing approaches the selection is performed on the basis of the ldquofunctionalrdquo description of a service, i.e. in terms of its inputs, outputs, preconditions and effects. In this paper, we present our approach for the process-level service selection and evaluate it on a real world scenario that entails a high level of complexity: the eBay Web Services,the Amazon E-Commerce Services and the e-payment service offered by PayPal. The approach is based on a representation of services at the process level that is based on BPEL and WSDL specifications and that extends these standard specifications with minimal semantic annotations that permit to perform an efficient and yet useful, semantic reasoning for the process-level selection of Web services.

Several works address the problem of the automated composition of stateful services, e.g., specified in WS-BPEL. However, the key problem of their practical applicability in real composition scenarios is still open. Addressing this problem requires to provide an easy and affordable way to specify behaviors of component services and composition requirements, as well as composition techniques that are powerful enough to scale to scenarios of realistic size. In this paper we provide a first step towards addressing this problem by evaluating the feasibility and efficiency of a state-of-the art approach to automating the composition task on a real scenario that entails a high level of complexity: the Amazon e-commerce services and an e-payment service offered by an important Italian banking Group (Monte dei Paschi di Siena). We show the feasibility of the specification of composition requirements and of the automated generation of complex executable WS-BPEL processes, and analyze the possibility of reducing the effort in the composition task.

One of the fundamental Ideas of Weh services and service oriented architecture is the possibility to develop new applications by composing existing services that are available on the Web. Several approaches have been proposed to tackle the problem of Web service composition, but little effort has been devoted so far to the problem of modeling the requirements of the composition. However, it is clear that the possibility to express requirements specifying complex interactions patterns among the component services is an essential step to cope with a wide range of composition problems. In this paper we present a new model which addresses one of the key aspects of composition requirements, namely the dataflow among the component services. We develop graphical notations and a formal theory for the new model and we integrate it within an existing automated composition framework

In this paper we propose a technique for the automated synthesis of new composite Web services. Given a set of abstract BPEL4WS descriptions of component services, and a composition requirement, we automatically generate an executable BPEL4WS process that, once deployed, is able to interact with the components to satisfy the requirement. We implement the proposed approach exploiting efficient synthesis techniques, and experiment with some case studies taken from real world applications and with a parameterized domain. We show that the technique can scale up to cases in, which the manual development of BPEL4WS composite services is not trivial and is time consuming.