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Nowadays, the search for innovative technological solutions to the organization of access to electronic learning resources in the university and their configuration within the environment to fit the needs of users and to improve learning…
Online continual learning aims to get closer to a live learning experience by learning directly on a stream of data with temporally shifting distribution and by storing a minimum amount of data from that stream. In this empirical…
The application of Artificial intelligence for teaching and learning in the academic sphere is a trending subject of interest in the computing education. ChatGPT, as an AI-based tool, provides various advantages, such as heightened student…
The rise of social media and AI tools has reshaped how students engage with learning, process information, and build trust in educational content. This generation prefers short, visual materials and fast feedback but often struggles with…
In continual learning, a system must incrementally learn from a non-stationary data stream without catastrophic forgetting. Recently, multiple methods have been devised for incrementally learning classes on large-scale image classification…
This paper explores the development and adoption of AI-based formative feedback in the context of biweekly reports in an engineering Capstone program. Each student is required to write a short report detailing their individual…
Tabletop exercises are used to train personnel in the efficient mitigation and resolution of incidents. They are applied in practice to support the preparedness of organizations and to highlight inefficient processes. Since tabletop…
In recent years, Web services are becoming more and more intelligent (e.g., in understanding user preferences) thanks to the integration of components that rely on Machine Learning (ML). Before users can interact (inference phase) with an…
Federated Learning (FL) enables multiple devices to collaboratively train a shared model while ensuring data privacy. The selection of participating devices in each training round critically affects both the model performance and training…
Micro-services are a common architectural approach to software development today. An indispensable tool for evolving micro-service systems is A/B testing. In A/B testing, two variants, A and B, are applied in an experimental setting. By…
In recent years, mobile devices have gained increasing development with stronger computation capability and larger storage space. Some of the computation-intensive machine learning tasks can now be run on mobile devices. To exploit the…
We study a new form of federated learning where the clients train personalized local models and make predictions jointly with the server-side shared model. Using this new federated learning framework, the complexity of the central shared…
Detailed feedback on courses and lecture content is essential for their improvement and also serves as a tool for reflection. However, feedback methods are often only used sporadically, especially in mass courses, because collecting and…
In learning-to-learn the goal is to infer a learning algorithm that works well on a class of tasks sampled from an unknown meta distribution. In contrast to previous work on batch learning-to-learn, we consider a scenario where tasks are…
Federated learning is renowned for its efficacy in distributed model training, ensuring that users, called clients, retain data privacy by not disclosing their data to the central server that orchestrates collaborations. Most previous work…
This paper describes the digital library of historical resources, a research project which involves building a testbed for the purpose of developing and testing new collaborative digital library functionality and presents an initial…
The rise of Generative AI (GenAI) tools like ChatGPT has created new opportunities and challenges for computing education. Existing research has primarily focused on GenAI's ability to complete educational tasks and its impact on student…
Engaging students in creating novel content, also referred to as learnersourcing, is increasingly recognised as an effective approach to promoting higher-order learning, deeply engaging students with course material and developing large…
Abstract concepts like software design patterns and the OSI model often pose challenges for engineering students, and traditional methods may fall short in promoting deep understanding and individual accountability. This study explores the…
Recent work has demonstrated that problems-- particularly imitation learning and structured prediction-- where a learner's predictions influence the input-distribution it is tested on can be naturally addressed by an interactive approach…