Abstract
This article summarises the research studies published in the special issue on Project Management and Scheduling devoted to the 18th International Conference on Project Management and Scheduling (PMS). The special issue contains state-of-the art research in the field of (non-)robust project and machine scheduling and the contribution of each individual study to the academic literature are discussed. We notice that there is a growing interest in the research community to investigate robust scheduling approaches and optimisation problems observed in real-life business settings. This allows us to derive some interesting future research directions for the project and machine scheduling community.

Abstract
Immersive Virtual Reality (iVR) is a promising educational tool for learning a second/foreign language. However, interactive iVR studies remain in their infancy, with more research required to validate what and how it can be implemented. This study focuses on the English listening dimension and evaluates the impact of a realistic interactive iVR compared to traditional listening exercises. The results were favourable and indicated that interactive iVR positively impacts the users' knowledge retention compared to a traditional listening approach. Likewise, the users revealed a preference for using iVR for learning when compared to traditional listening exercises, as well as higher user satisfaction with the iVR experiment.

Abstract
Considering the great challenge of implementing digital tools to improve collaboration in the value chain and promote the adoption of circularity strategies, as is the case with digital traceability tools and digital product passports. This paper presents an innovative proposal for implementing an industrial data sharing ecosystem, namely an architecture and platform for digital traceability between entities based on Data Spaces. To validate our proposal, a use case scenario was implemented as part of the BioShoes4All project.

Abstract
Nowadays, Higher Education Institutions (HEIs) are faced with the crucial challenge of establishing and supervising strategies and policies that are essential for decisions in various areas and at various levels. Within this context, the importance of Business Intelligence (BI) has increased significantly, emerging as an essential tool for analysing and managing data. This BI capability enables HEIs to make more informed choices in line with their global strategies. This research focuses on developing a roadmap for the effective implementation of BI systems in HEIs. Using a Design Science Research (DSR) methodology, this work proposes a structured and adaptable roadmap that covers the key factors from the design to the implementation of BI systems in HEIs. This roadmap includes not only a reference architecture for BI systems but also a set of dashboards. The roadmap was validated through a case study at the University of Tras-os-Montes e Alto Douro (UTAD), involving exploratory analysis and feedback from experts. This study stands out for its practical and theoretical approach, offering a strategic and practical guide for the adoption of BI systems in HEIs, thus responding to a need identified in the academic literature.

Abstract
Recent advances in deep learning have promoted the advent of many computational systems capable of performing intelligent actions that, until then, were restricted to the human intellect. In the particular case of human languages, these advances allowed the introduction of applications like ChatGPT that are capable of generating coherent text without being explicitly programmed to do so. Instead, these models use large volumes of textual data to learn meaningful representations of human languages. Associated with these advances, concerns about copyright and data privacy infringements caused by these applications have emerged. Despite these concerns, the pace at which new natural language processing applications continued to be developed largely outperformed the introduction of new regulations. Today, communication barriers between legal experts and computer scientists motivate many unintentional legal infringements during the development of such applications. In this paper, a multidisciplinary team intends to bridge this communication gap and promote more compliant Portuguese NLP research by presenting a series of everyday NLP use cases, while highlighting the Portuguese legislation that may arise during its development. © 2024 ELRA Language Resource Association.

Abstract
This paper presents a study comparing different user interface modes (Controller-Based Selection, Object Interaction, and Voice Recognition) within immersive Virtual Reality (iVR) environments for foreign language learning. Given the rapid advancements and potential of iVR in education, there is a need for focused research on optimising user interfaces for effective learning experiences. This study aimed to identify optimal interfaces for integrating iVR applications as complementary educational tools while gauging student preferences. Participants engaged in interactive learning tasks across the three conditions, with assessments focused on System Usability, Presence, User Satisfaction, Cybersickness, Learning Outcomes, and Task Duration. Findings indicate high usability across all conditions, with a preference observed for Controller-Based Selection and Object Interaction. Object Interaction showed strong motivational appeal but required more time to complete tasks than Controller-Based. Therefore, for time-constrained educational settings, the Controller-Based Selection interface is practical due to its lower physical effort requirement. Despite recent advances, our study found Voice Recognition interaction to be the least preferred interaction method, indicating a need for further technological improvements to boost its acceptance and effectiveness in educational contexts.