A large-scale volunteer computing system is a type of distributed system in which contributors volunteer their computing resources, such as personal computers or mobile devices, to contribute to a larger computing effort. Volunteer resources are connected over the Internet and together form a powerful computing system capable of providing a service without depending on a service provider. Volunteer network resource allocation is the process of assigning computing tasks or services to a network of volunteer resources. The allocation process includes identifying the needed resources, selecting appropriate volunteers, and assigning tasks or services based on their capabilities. Volunteer computing systems consist of a large number of heterogeneous resources - in terms of processing power, storage, and availability - belonging to different authorities - users or organizations - and exhibiting uncertain behavior in terms of connection, disconnection, capacity, and failure. All of this makes resource allocation a challenging task in terms of ensuring a minimum quality of service, requiring complex algorithms and optimization techniques to ensure that services are efficiently allocated while respecting the constraints of the available resource. This paper introduces the Network-Aware Resource Allocation mechanism, which leverages the location, connectivity, and network latency of volunteer nodes to minimize the time a service runs with degraded quality of service and aims to deal with the energy consumption resulting from data replication requirements. This resource allocation mechanism applies to both the initial deployment of the service in the network and to the reallocation of nodes in the event that one of the allocated nodes fails or becomes unavailable. Our method has been validated in a simulation environment of a realistic volunteer system. The analysis of the results shows how our mechanism meets the quality requirements of users while minimizing the synchronization and replication times of service data replicas, as well as the time that services run with degraded quality of service, reducing the times by more than 70% in the service deployment phase and by more than 60% in the service execution phase. It also helps to reduce overall energy consumption.

Online courses heavily relying on programming skills tend to be difficult and time-consuming for students, who may get frustrated when stuck in an assignment. Obviously, this may increase drop-out rate and decrease academic performance as well as students’ satisfaction with the course and the institution in general. In this context, we propose a notification, recommendation and monitoring system which is integrated into an automatic assessment tool with the aim to enhance the learning process in virtual classrooms. In particular, notifications, recommendations and visualization reports are used to show the activity, progress and performance of all students. The system is implemented in a distributed computing course in an online university. A quantitative analysis method used to collect and analyze data of students’ perceptions regarding the system showed that: (1) notifications helped students organize their time and encourage them to work more effectively; (2) recommendations allowed students to receive useful and timely scaffolding for coping with their problems and completing their assignment; and (3) visualization reports provided valuable insights toward monitoring the learning process. Moreover, the analysis of correlations showed that the reception of recommendations and the visualization reports is related to encourage students to do more executions and to start earlier the assignments. Finally, this study seeks to contribute to online teachers’ endeavor to enhance students’ engagement, performance and learning in the field of programming (and not only).

The exploration of augmented reality's (AR) potential in higher education teaching and learning demonstrates an impressive scope of critical inquiry. Online higher education (OHE) represents a transformation in learning practices and educational paradigms on a global scale, with a significant opportunity for the application of AR through e-learning. The overarching goal of the current study is to understand how the presence of AR applications in an OHE multimedia program impacts student learning. The current conceptual study aims to formulate design and development requirements for an AR application, aiming to understand how a user-centred design (UCD) approach could frame such a process. The overarching goal is to design AR resources which enhance student learning in multimedia education. Implementing a user-centred approach ensures that learners are taken into account from the beginning of the design process and throughout the iterative design lifecycle. The current paper presents the results from the first phase of a multi-stage research project. First, conceptually designed personas, scenario reviews, and user journey mappings were developed based on identified learner needs and AR system requirements previously identified. The results show evaluation techniques use within a UCD process while revising AR scenarios from the learner's perspective and exploring design requirements to ensure the feasibility of the AR application. An implication of our study is to demonstrate the value of a range of evaluation techniques presented here using a user-centred design approach, which can be used to design and develop future AR and eXtended Reality (XR) technologies in educational scenarios.