The goal of this workshop is to present an overview of ongoing research on Human–Computer Interaction (HCI) for teaching and learning. The workshop focuses on how emerging interaction paradigms, such as adaptive interfaces, multimodal interaction, and game-based learning, can support richer, more engaging, and more inclusive Technology-Enhanced Learning (TEL) experiences. The discussion will be structured around three central research directions that remain insufficiently explored: facilitating the design and evaluation of TEL systems that promote effective learning and quality of experience through innovative HCI approaches; adapting TEL systems to the complexity of educational environments; and modeling learners and users in TEL systems to account for their diversity, their preferences, and constraints. The ultimate goal of the workshop is to bring together researchers interested in discussing and converging on the future challenges and opportunities of the field.

edge intelligence | internet of autonomous unmanned vehicles | software systemsWith the development of the embedded systems, navigation, sensors, robots, and big data analytics, the automobile vehicles industry has been one major economic sector recently, and its economical and societal impacts continue to expand.To extend the capabilities of automobile vehicles, the Internet of Autonomous Unmanned Vehicles (IAUV) has been proposed to form a global network of sensors, robots and unmanned vehicles, improving cooperation between heterogeneous communication systems to provide reliable Internet services in civil applications such as environmental monitoring, video surveillance, network provisioning, wireless power transfer, and emergency or disaster assistance.However, these powerful applications always require the support from automobile, transportation, wireless communications, networking, resource management, intelligent computing, security, and robotics, and so on.Due to diverse and interdisciplinary nature of these challenges, architectures, algorithms and developmental software systems proposed by networking, robotics, transportation, cognitive and artificial intelligence research communities will need to be utilized.Fortunately, the abilities of IAUV systems can be greatly realized with high performance of low latency and high reliability by applying artificial intelligence-enabled computing, communication, edge service deployment and flexible resource schedule of unmanned vehicles, robots and sensors appropriate and ---------------

Gamification, commonly described as the use of game design elements in non-game contexts, is frequently adopted to enhance users' motivation, engagement, and happiness while supporting them in reaching different objectives, related to learning activities and behavioral changes. Despite being a widely used approach, several studies show that the final outcomes following gamification use are not always positive. To face this problem, we developed a tool called GamiDOC composed of different features aimed at facing the existing problems in the gameful systems design process and, at the same time, guiding designers and practitioners in the design and evaluation of gamified solutions. In this paper, we present the elements that make gameful systems design a challenging process, the state of the art in gamification design, and the issues that are still open in the design of gameful systems. Finally, we provide a detailed description of GamiDOC and why the tool stands as a valuable solution to guide users across all the stages of gameful systems design, development, and evaluation. Finally, we present a usability evaluation of GamiDOC and a use-case scenario.

Personalized learning methods have revolutionized education by allowing tailored teaching approaches to meet individual students’ needs. This approach, supported by educational technologies, aims to engage learners with diverse expertise levels by adapting content and methods accordingly. This demo introduces an End-User Development system that empowers teachers to create and define interactive behaviors of educational tools using Trigger-Action Programming (TAP). The system facilitates the creation of "vocabularies" specific to each learning subject and translates them into verbal primitives for trigger-action rule definition. These rules are then used in the customization of interfaces. This demo presents examples using a tangible device and a web-based educational game aimed to enrich education activities in elementary schools. Future directions include studying teachers’ appropriation of the use of TAP to customize learning material as well as adaptation in new domains and with different devices.

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.

In the post-digital world, educators are tasked with navigating a plethora of resources to build effective interventions for ever-changing skill requirements. Intelligent systems can assist them by recommending educational content, providing personalized learning experiences and automating time-consuming tasks, allowing educators to focus on creating engaging and interactive learning experiences. However, it is also important that educators are equipped to fruitfully engage with such systems in a way that enhances their pedagogy and teaching practices as far as help them to deal with societal challenges. The project ENCORE aims to support this shift by developing an intelligent system that selects quality Open Educational Resources (OERs) to support the pedagogical design and teaching around key skills affected by societal macro-trends, i.e. Green, Digital and Entrepreneurial (GDE) skills. The project has two phases: a data-driven phase using Natural Language Processing to match skills with relevant OERs and a qualitative/expert-driven phase for developing pedagogical guidelines and testing the system in real educational contexts. This paper describes the main tenets of the ENCORE project and the research actions taken to support learners and educators in using OERs and targeting skills most relevant to the new macro-trends of digitalization, climate change, and post-COVID economic recovery challenges.

In the evolving landscape of educational tools, Open Educational Resources (OERs) represent a wave of innovation and accessibility, offering open access materials to spread knowledge. However, their application faces several challenges, particularly in their usability and integration. The ENCORE project addresses these challenges by introducing a new workflow for the sharing and creation of OERs, which includes the collaboration on and definition of key technological components. A central feature of this approach is the development of a meta-model that standardizes OER structures, thereby improving their discoverability and ease of sharing. Additionally, the project proposes a Generative AI service designed to generate assessment activities based on these OERs. This integrated approach, combining the meta-model and workflow, seeks to seamlessly connect the discovery and use of resources, fostering an engaged and collaborative environment for OERs.

This Work in Progress paper introduces the design of an innovative educational system that leverages Artificial Intelligence (AI) to address challenges in physics education. The primary objective is to create a system that dynamically adapts to the individual needs and preferences of students while maintaining user-friendliness for teachers, allowing them to tailor their teaching methods. The emphasis is on fostering motivation and engagement, achieved through the implementation of a gamified virtual environment and a strong focus on personalization. Our aim is to develop a system capable of autonomously generating learning activities and constructing effective learning paths, all under the supervision and interaction of teachers. The generation of learning activities is guided by educational taxonomies that delineate and categorize the cognitive processes involved in these activities. The proposed educational system seeks to address challenges identified by Physics Education Research (PER), which offers valuable insights into how individuals learn physics and provides strategies to enhance the overall quality of physics education. Our specific focus revolves around two crucial aspects: concentrating on the conceptual understanding of physics concepts and processes, and fostering knowledge integration and coherence across various physics topics. These aspects are deemed essential for cultivating enduring knowledge and facilitating practical applications in the field of physics.

In the realm of conceptual and system design, mod-eling stands out as a pivotal activity, emphasizing the significance of mastering modeling languages such as the Unified Modeling Language (UML). Despite the existence of numerous interactive UML learning applications and the emergence of gamification-based alternatives designed to enhance learner engagement, a gap persists in providing an immersive learning environment ca-pable of significantly increasing interactivity during the learning process. Current approaches fall short in creating a sense of presence that could positively impact learning outcomes, and the full potential of gamification remains underexplored. To address this gap, this paper introduces an innovative so-lution-a gamification-based UML learning environment within Virtual Reality (VR), named GaMo Vr.This immersive platform is specifically tailored for practicing the creation of class diagrams in an interactive manner, incorporating mini games to support the learning process. The study conducted to evaluate GaMo Vrinvolved 16 participants and utilized the MEEGA360 question-naire. In comparison to a similar desktop application, the results of the evaluation revealed that GaMo Vrsignificantly enhanced learners' motivation, enjoyment, and engagement, along with a perceivable improvement in the overall learning outcome. This groundbreaking approach not only bridges the existing gap in UML learning applications but also harnesses the potential of VR and gamification to revolutionize the way modeling is taught and learned.

Abstract Modelling is an important activity in software development and it is essential that students learn the relevant skills. Modelling relies on dedicated tools and these can be complex to install, configure, and use—distracting students from learning key modelling concepts and creating accidental complexity for teachers. To address these challenges, we believe that modelling tools specifically aimed at use in teaching are required. Based on discussions at a working session organised at MODELS 2023 and the results from an internationally shared questionnaire, we report on requirements for such modelling tools for teaching. We also present examples of existing modelling tools for teaching and how they address some of the requirements identified.

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.

Multimodal journey planners are used worldwide to support travelers in planning and executing their journeys. Generated travel plans usually involve local mobility service providers, consider some travelers’ preferences, and provide travelers information about the routes’ current status and expected delays. However, those planners cannot fully consider the special situations of individual cities when providing travel planning services. Specifically, authorities of different cities might define customizable regulations or constraints of movements in the cities (e.g., due to construction works or pandemics). Moreover, with the transformation of traditional cities into smart cities, travel planners could leverage advanced monitoring features. Finally, most planners do not consider relevant information impacting travel plans, for instance, information that might be provided by travelers (e.g., a crowded square) or by mobility service providers (e.g., changing the timetable of a bus). To address the aforementioned shortcomings, in this paper, we propose ROUTE, a framework for customizable smart mobility planners that better serve the needs of travelers, local authorities, and mobility service providers in the dynamic ecosystem of smart cities. ROUTE is composed of an architecture, a process, and a prototype developed to validate the feasibility of the framework. Experiments’ results show that the framework scales well in both centralized and distributed deployment settings.

Digital Twins are becoming more and more popular in a variety of industries as a way to manage complex systems. As digital twins become more sophisticated, the need for effective training and learning systems becomes more important. Teachers, project leaders, and tool vendors have a hard time teaching or training their students, co-workers, or users. In this article we propose a new way to train users in using digital twins proposing them a gamified and virtual environment. We present an overall architecture and discuss its practical realization. We propose a set of future challenges we consider as critical in order to make our intuition an enabler for a more effective learning/training approach.

The increasing growing need for optimization of transportation in a sustainable and green environment is fundamental for the future of mobility. Companies, governments, and non-governmental institutions are trying to find new ways to contribute to this challenge. In particular, the approach is to improve the efficiency and the quality of the movement of diversification of an integrated way of transportation of people and goods. Many people may need to be at some location at some point in time, or many goods may need to be transported to nearby destinations with the same packaging conditions. The main goal of this Special Issue was to integrate the most recent advances in transportation that connect the hybrid point of view. In particular, key contributions integrate several interesting topics related to earning algorithms for the integration of passengers and goods, gamification techniques, semantic data, blockchain, and edge computing. Other topics in urban mobility, railway, and highways were considered, and hot topics on shared autonomous vehicles (SAVs) brought huge value. Moreover, the Internet of Things (IoT) opens the doors for new development in Vehicle to Everything (V2X), which are crucial for the development of new services that generate business and social impact in the future of a diversified way of the integration of passengers and goods mobility.

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.

The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This article proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.

An increasing interest is growing around the idea of microservices and the promise of improving scalability when compared to monolithic systems. Several companies are evaluating pros and cons of a complex migration. In particular, financial institutions are positioned in a difficult situation due to the economic climate and the appearance of agile competitors that can navigate in a more flexible legal framework and started their business since day one with more agile architectures and without being bounded to outdated technological standard. In this paper, we present a real world case study in order to demonstrate how scalability is positively affected by re-implementing a monolithic architecture (MA) into a microservices architecture (MSA). The case study is based on theFX Coresystem, a mission critical system of Danske Bank, the largest bank in Denmark and one of the leading financial institutions in Northern Europe. The technical problem that has been addressed and solved in this paper is the identification of a repeatable migration process that can be used to convert a real world Monolithic architecture into a Microservices architecture in the specific setting of financial domain, typically characterized by legacy systems and batch-based processing on heterogeneous data sources.

Abstract In 2017 and 2018, two events were held—in Marburg, Germany, and San Vigilio di Marebbe, Italy, respectively—focusing on an analysis of the state of research, state of practice, and state of the art in model-driven engineering (MDE). The events brought together experts from industry, academia, and the open-source community to assess what has changed in research in MDE over the last 10 years, what challenges remain, and what new challenges have arisen. This article reports on the results of those meetings, and presents a set of grand challenges that emerged from discussions and synthesis. These challenges could lead to research initiatives for the community going forward.

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.

Modern software systems are becoming more and more socio-technical systems composed of distributed and heterogeneous agents from a mixture of people, their environment, and software components. These systems operate under continuous perturbations due to the unpredicted behaviors of people and the occurrence of exogenous changes in the environment. In this article, we introduce a notion of ensembles for which, systems with collective adaptability can be built as an emergent aggregation of autonomous and self-adaptive agents. Building upon this notion of ensemble, we present a distributed adaptation approach for systems composed by ensembles: collections of agents with their respective roles and goals. In these systems, adaptation is triggered by the run-time occurrence of an extraordinary circumstance, called issue. It is handled by an issue resolution process that involves agents affected by the issue to collaboratively adapt with minimal impact on their own preferences. Central to our approach is the implementation of a collective adaptation engine (CAE) able to solve issues in a collective fashion. The approach is instantiated in the context of a smart mobility scenario through which its main features are illustrated. To demonstrate the approach in action and evaluate it, we exploit the DeMOCAS framework, simulating the operation of an urban mobility scenario. We have executed a set of experiments with the goal to show how the CAE performs in terms of feasibility and scalability. With this approach, we are able to demonstrate how collective adaptation opens up new possibilities for tackling urban mobility challenges making it more sustainable respect to selfish and competitive behaviours.

Multimodal journey planners have been introduced with the goal to provide travellers with itineraries involving two or more means of transportation to go from one location to another within a city. Most of them take into account user preferences, their habits and are able to notify travellers with real time traffic information, delays, schedules update, etc.. To make urban mobility more sustainable, the journey planners of the future must include: (1) techniques to generate journey alternatives that take into account not only user preferences and needs but also specific city challenges and local mobility operators resources; (2) agile development approaches to make the update of the models and information used by the journey planners a self-adaptive task; (3) techniques for the continuous journeys monitoring able to understand when a current journey is no longer valid and to propose alternatives. In this paper we present the experiences matured during the development of a complete solution for mobility planning based on model-driven engineering techniques. Mobility challenges, resources and remarks are modelled by corresponding languages, which in turn support the automated derivation of a smart journey planner. By means of the introduced automation, it has been possible to reduce the complexity of encoding journey planning policies and to make journey planners more flexible and responsive with respect to adaptation needs.

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.

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.

Requirements analysis is an important phase in a software project. Automatic evaluation of natural language (NL) requirements documents has been proposed as a means to improve the quality of the system under development. QuARS Express is an automatic analyzer of natural language (NL) requirements able to manage complex and structured requirement documents containing metadata, and to produce an analysis report rich of information that points out linguistic defects and indications about the writing style of NL requirements.

Composition of Web services is much studied to support business-to-business and enterprise application integration in e-commerce. Current Web service composition approaches range from practical languages aspiring to become standards (like BPEL, WS-CDL, OWL-S and WSMO) to theoretical models (like automata, Petri nets and process algebras). In this paper we compare these approaches w.r.t. a selected set of characteristics (like trust, security and performance) and we advocate the use of formal models, and their tool support, to increase one's confidence in web service compositions. This paper can assist web service composition designers and developers to deliver lasting solutions, in concordance with the technology's critical needs.

Service-oriented computing (SOC) is a promising means to integrate heterogeneous systems. Services from different providers can be integrated into a composite service regardless of their locations, platforms, and/or execution speeds to implement complex business processes. In this paper we propose an approach for the services composition that takes into account the QoS that the composite system must satisfy. After that we design the service selection algorithm used to construct the optimal composite service with the objective to maximize the values of the well-defined QoS characteristics. In this paper we are interested on the data-intensive applications where the QoS attributes are very important for the reliability and performance of these systems.

Nowadays common practice indicates that the requirement engineering (RE) process critically influences the success of the system development life cycle. Several commercial tools allow to classify, archive and manage requirements and then to print out reports and requirement documents. QuARS (Quality Analyzer for Requirements Specifications) is an automatic analyzer of such requirement documents, developed by ISTI-CNR, that can be adopted to evaluate the document quality by linguistic point of view. This paper presents how a requirement management tool, an automatic document generator, and QuARS can be integrated to define an RE automation support. The case study investigates and highlights the efficacy and the role of such proposed support in the Siemens C.N.X. development process.