This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. Leveraging data from Moodle, a widely used learning management system (LMS), we analyzed 450 students’ academic records spanning nine semesters. Five machine learning algorithms—k-nearest neighbors, random forest, logistic regression, decision trees, and neural networks—were applied to identify correlations between courses and predict grades. The results indicated that courses with strong correlations (+0.3 and above) significantly enhanced predictive accuracy, particularly in binary classification tasks. kNN and neural networks emerged as the most robust models, achieving F1 scores exceeding 0.8. These findings underscore the potential of EDM to optimize instructional strategies and support personalized learning pathways. This study offers insights into the effective application of data-driven approaches to improve educational outcomes and foster student success.

Modern consumer electronics (CE) devices have evolved such that human interaction with machines is ever more natural and effective. The forthcoming deployment of the Internet of Things (IoT) over the existing Internet infrastructure promises to expand this interaction by providing applications and services that allow the human-computer interaction to integrate an automated customization of everyday life [1]. The vision is very optimistic on the amount of smart objects (SOs) deployed around us as the building blocks of the IoT. Experts forecast that 28 billion "things" will be connected to the Internet by 2020 [2].

Augmented reality is now a well-known concept, a technology that integrates digital content to the user's physical world. As more and more applications begin to reshape user's daily lives in multiple domains, cultural heritage sites have begun to focus on capitalizing augmented reality's potential and improve their visitor experience. This work provides an overview of the state-of-the-art techniques, methodologies, and technologies integrated with augmented reality applications for cultural heritage while also categorizing the current works according to the latest techniques as they integrate to enrich the user's experience. The survey presents an overview of the characteristics of an augmented reality system, and discusses the current challenges, issues, limitations, and future directions. Finally, this work examines the methods and techniques that are used in the cultural heritage and augmented reality integration, outlining benefits, and open issues.

In recent years, Recommendation Systems (RSs) have gained popularity in different scientific fields through the creation of (mostly mobile) applications that deliver personalized services. A mobile recommendation system (MRS) that classifies in situ visitors according to different visiting profiles could act as a mediator between their visiting preferences and cultural content. Drawing on the above, in this paper, we propose ACUX Recommender (ACUX-R), an MRS, for recommending personalized cultural POIs to visitors based on their visiting preferences. ACUX-R experimentally employs the ACUX typology for assigning profiles to cultural visitors. ACUX-R was evaluated through a user study and a questionnaire. The evaluation conducted showed that the proposed ACUX-R satisfies cultural visitors and is capable of capturing their nonverbal visiting preferences and needs.

In recent years, researchers in the field of natural heritage have intensified their efforts to develop new ways to enhance the promotion and accessibility of natural content in order to attract more audiences using virtual representations of physical objects (digital twins). Therefore, they are increasingly incorporating new technologies and digital tools in their operations since their usage by the general public and in the natural heritage (NH) museums is considered particularly effective. Simultaneously, the increasing quality of the produced digitizations has opened up new opportunities for the exploitation of the outcomes of digitization beyond the initial anticipations. Responding to the growing demand of museum visitors for a personalized digital tour experience, especially amidst the recent COVID-19 pandemic, the v-PalM project aims to develop a digital platform to offer virtual guidance and education services at the Museum of Paleontology and Geology, which is hosted at the National Kapodistrian University of Athens. The development of the platform will be based on collecting data through various methods, including crowdsourcing, innovative information, and communication technologies, taking advantage of content digitization using 3D scanning devices. This paper demonstrates an enhanced methodology for the digitization of paleontological exhibits. The methodology uses photogrammetry and laser scanning methods from various devices, such as drones, laser scanners, and smartphones. These methods create digital twins that are suitable for various scenarios, including research, education, and entertainment. The proposed methodology has been applied to over fifty paleontological museum exhibits of varying sizes and complexities, and the resulting 3D models exhibit high accuracy in both their material and geometric aspects, while they also feature crucial details that assist researchers and the scientific community.

The paper introduces an innovative methodology that combines photogrammetry and laser scanning techniques to create detailed 3D models of historic mansions within the Kifissia region of Attica, Greece. While photogrammetry excels in capturing intricate textures, it faces challenges such as lighting variations and precise image alignment. On the other hand, laser scanning offers precision in capturing geometric details but struggles with reflective surfaces and large datasets. Our study integrates these methods to leverage their strengths and address limitations, resulting in comprehensive and accurate digital twins of cultural spaces. The methodology section outlines the step-by-step process of integration, emphasizing solutions to specific challenges encountered in the study area. Preliminary results showcase the enhanced fidelity and completeness of the digital twins, demonstrating the effectiveness of the combined approach. The subsequent sections of the paper delve into a detailed presentation of the methodology, provide a comprehensive analysis of obtained results, and discuss the implications of this innovative approach in cultural preservation and broader applications.