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- A Virtual Reality Game as a Tool for Psychotherapy with oCd PatientsPublication . Torrão, André; Natário, João; Carvalho, Paula; Silva, Cláudia M.; Silva, Frutuoso G. M.The treatment of several types of obsessions/compulsions for people with Obsessive-Compulsive Disorders (OCD) can be done using virtual environments (VE). These people experience intrusive, unwanted thoughts that cause anxiety, which trigger intentional repetitive behaviors to decrease their anxiety. The advantage of using a VE to experience and challenge compulsions is that it allows the user to take the risk without taking a real risk asin digital games. This article presents a virtual reality serious game for OCD therapy, which will serve as a tool to expose the patients to stimuli that can trigger OCD symptoms, for example, tidying, cleaning, and checking. The game is more oriented for adolescents and younger adults because OCD usually starts to affect teenagers, accompanying them throughout adulthood, generating a very accentuated degree of disability in all areas of their lives. Despite Covid-19, a small group of specialists did a preliminary evaluation of the game, which has provided promising results on the feasibility of VR interventions for OCD in clinical practice.
- Learning through the dialogue with NPCs using generative AIPublication . Rodrigues, Vanessa; Silva, Frutuoso G. M.The rapid evolution of generative artificial intelligence (GenAI) is revolutionising various areas, including education and gaming industry. GenAI can create original content to enhance traditional teaching methods, making learning more interactive and personalised. These tools can significantly improve educational outcomes by providing personalised feedback to students and increasing their engagement and motivation. However, the integration of GenAI in education raises ethical concerns, particularly regarding privacy, bias, and the accuracy of AI-generated content, as well as the authenticity and authorship of the work. There is a strong emphasis on the need for robust guidelines and human oversight to mitigate these issues. We used GenAI to create an NPC with a unique personality and life background and enable learners to interact with the NPC without scripted dialogue, creating an engaging game-based learning environment to evaluate the perceptions of the students using GenAI as a learning tool. The prototype developed was evaluated by a group of sixteen students, and the main results are presented and discussed.
- Math-Masters: An Educational Game to Practice the Mathematical OperationsPublication . Marques, João A. B. T.; Ferreira, João L. A. P.; Silva, Frutuoso G. M.Educational games have gained significant popularity in recent years as an innovative and engaging means of enhancing learning. These games use technology and game design principles to create a fun learning environment. Educational games have changed how we learn by combining fun and learning goals. They offer an engaging, interactive, and personalized learning experience, promoting critical thinking, problem-solving, and collaboration. However, the design of educational games must combine the fun factor with the learning goals, which sometimes does not happen, creating the impression that educational games are not fun. In this paper, we describe an educational game to learn multiplication operations in a fun way. The game is a point-and-click deck-building and partially rogue-lite third-person educational game with the purpose of teaching multiplication operations in mathematics. It is themed around medieval fantasy, with monsters on one hand and magic spells on the other. The player has a card deck that he can use to solve the mathematical questions and defeat the monsters. Some preliminary tests were carried out with fifty-eight students, which showed the potential of this kind of tool. Most of the students agreed that the game helped them with the multiplication operation and that they would like to play more levels of the game.
- Subtle biases introduced in equity studies through data anonymizationPublication . Fazendeiro, Paulo; Prata, Paula; Ferrão, Maria Eugénia; Altman, MicahThis work investigates the trade-off between data anonymization and utility, particularly focusing on the implications for equity-related research in education. Using microdata from the 2019 Brazilian National Student Performance Exam (ENADE), the study applies the (ε, δ)-Differential Privacy model to explore the impact of anonymization on the dataset's utility for socio-educational equity analysis. By clustering both the original and anonymized datasets, the research evaluates how group categories related to students' sociodemographic variables, such as gender, race, income, and parental education, are affected by the anonymization process. The results reveal that while anonymization techniques can preserve overall data structure, they can also lead to the suppression or misrepresentation of minority groups, introducing biases that undermine the research's objective of promoting educational equity. This finding highlights the importance of involving domain experts in the interpretation of anonymized data, particularly in studies aimed at reducing socio-economic inequalities. The study concludes that careful attention is needed to prevent anonymization efforts from distorting key group categories, which could undermine the validity of data-driven policies aimed at promoting equity.
- A scoping study of reviews on artificial intelligence in educationPublication . Gabriel, Graça; Ferrão, Maria Eugénia; Prata, PaulaThis scoping study synthesizes recent developments in artificial intelligence in education (AIEd), addressing knowledge structures, research priorities, learning theories, ethical considerations, and impact evaluation. A bibliometric analysis of 31 review articles (2019-2023) indexed in Scopus (Social Sciences) was conducted using VOSviewer and complementary statistical methods. The corpus is concentrated in the United Kingdom, Hong Kong, China, Germany, the United States, and Taiwan, with Asian countries accounting for 48.4%. Multidisciplinary journals attract 4.4 times more citations than education-only outlets. Findings indicate a marked rise in AIEd research, primarily led by education-affiliated scholars, yet often lacking robust pedagogical grounding and systematic impact assessment. The prevalence of small samples, limited quantitative rigor, and inconsistent contextual reporting constrain generalizability and inference. To enhance educational relevance and fairness, the field should be anchored in pedagogical frameworks and advanced through collaborative efforts that build stronger theories, methods, and practices responsive to diverse educational needs.
- Carbon Fiber Epoxy Composites for Both Strengthening and Health Monitoring of StructuresPublication . Salvado, Rita; Lopes, Catarina; Szojda, Leszek; Araújo, Pedro; Górski, Marcin; Velez, Fernando J.; Castro-Gomes, João; Krzywon, RafalThis paper presents a study of the electrical and mechanical behavior of several continuous carbon fibers epoxy composites for both strengthening and monitoring of structures. In these composites, the arrangement of fibers was deliberately diversified to test and understand the ability of the composites for self-sensing low strains. Composites with different arrangements of fibers and textile weaves, mainly unidirectional continuous carbon reinforced composites, were tested at the dynamometer. A two-probe method was considered to measure the relative electrical resistance of these composites during loading. The measured relative electrical resistance includes volume and contact electrical resistances. For all tested specimens, it increases with an increase in tensile strain, at low strain values. This is explained by the improved alignment of fibers and resulting reduction of the number of possible contacts between fibers during loading, increasing as a consequence the contact electrical resistance of the composite. Laboratory tests on strengthening of structural elements were also performed, making hand-made composites by the “wet process”, which is commonly used in civil engineering for the strengthening of all types of structures in-situ. Results show that the woven epoxy composite, used for strengthening of concrete elements is also able to sense low deformations, below 1%. Moreover, results clearly show that this textile sensor also improves the mechanical work of the strengthened structural elements, increasing their bearing capacity. Finally, the set of obtained results supports the concept of a textile fabric capable of both structural upgrade and self-monitoring of structures, especially large structures of difficult access and needing constant, sometimes very expensive, health monitoring.
- Leveraging Machine Learning for Weed Management and Crop Enhancement: Vineyard Flora ClassificationPublication . Corceiro, Ana; Pereira, Nuno José Matos; Alibabaei, Khadijeh; Gaspar, Pedro DinisThe global population’s rapid growth necessitates a 70% increase in agricultural production, posing challenges exacerbated by weed infestation and herbicide drawbacks. To address this, machine learning (ML) models, particularly convolutional neural networks (CNNs), are employed in precision agriculture (PA) for weed detection. This study focuses on testing CNN architectures for image classification tasks using the PyTorch framework, emphasizing hyperparameter optimization. Four groups of experiments were carried out: the first one trained all the PyTorch architectures, followed by the creation of a baseline, the evaluation of a new and extended dataset in the best models, and finally, the test phase was conducted using a web application developed for this purpose. Of 80 CNN sub-architectures tested, the MaxVit, ShuffleNet, and EfficientNet models stand out, achieving a maximum accuracy of 96.0%, 99.3%, and 99.3%, respectively, for the first test phase of PyTorch classification architectures. In addition, EfficientNet_B1 and EfficientNet_B5 stood out compared to all other models. During experiment 3, with a new dataset, both models achieved a high accuracy of 95.13% and 94.83%, respectively. Furthermore, in experiment 4, both EfficientNet_B1 and EfficientNet_B5 achieved a maximum accuracy of 96.15%, the highest one. ML models can help to automate crop problem detection, promote organic farming, optimize resource use, aid precision farming, reduce waste, boost efficiency, and contribute to a greener, sustainable agricultural future.
- Imputação de Valores Omissos em Análise Descritiva de Dados, em RPublication . Salambiaku, Luzizila; Prata, Paula; Ferrão, Maria EugéniaOs valores omissos representam um problema frequente no processo de análise de dados. Neste artigo foram comparados seis métodos distintos de imputação, disponíveis no software R e avaliado o seu desempenho em conjuntos de dados relacionados com a área da educação. Foi estudada uma amostra de 20408 estudantes para testar os seis algoritmos em quatro conjuntos de dados gerados por simulação com diferentes percentagens de valores omissos, considerando 5%, 10%, 15% e 20% nas variáveis de interesse. Foram explorados métodos de imputação simples (Média, Mediana e Moda), métodos baseados em aprendizagem automática (kNN e bPCA) e um método de imputação múltipla (MICE). Foi avaliado o desempenho de cada método calculando os respetivos erros de imputação através as métricas RMSE e MAE. Os resultados obtidos mostram que a imputação pela Moda forneceu quase de forma constante menores valores de erro.
- Anonymized Data Assessment via Analysis of Variance: An Application to Higher Education EvaluationPublication . Ferrão, Maria Eugénia; Prata, Paula; Fazendeiro, PauloThe assessment of the utility of an anonymized data set can be operational-ized by the determination of the amount of information loss. To investigate the possible degradation of the relationship between variables after anony-mization, hence measuring the loss, we perform an a posteriori analysis of variance. Several anonymized scenarios are compared with the original data. Differential privacy is applied as data anonymization process. We assess data utility based on the agreement between the original data structure and the anonymized structures. Data quality and utility are quantified by standard metrics, characteristics of the groups obtained. In addition, we use analysis of variance to show how estimates change. For illustration, we apply this ap-proach to Brazilian Higher Education data with focus on the main effects of interaction terms involving gender differentiation. The findings indicate that blindly using anonymized data for scientific purposes could potentially un-dermine the validity of the conclusions.
- Teaching in conditions of difficult knowledge transfer due to the state of emergency caused by the pandemicPublication . Mravik, Miloš; Šarac, Marko; Veinovic, Mladen; Pombo, NunoIntroduction/purpose: This paper presents the transformation of the current, classical approach to teaching. Online platforms enable students with and without disabilities to follow classes without hindrance during the lecture period. After the lecture, they are allowed to view video and presentation materials. The main advantage of this way of teaching is the possibility of attending classes from any location and from any device; it is only important to be connected to the Internet. Methods: Full integration with the already existing Faculty Information System has been performed. The paper describes a new approach to teaching and illustrates the expected benefits of online teaching. The platforms used in this integration are Microsoft Azure, Microsoft Office 365 Admin, Microsoft Teams, Microsoft Stream and Microsoft SharePoint. Results: The result of the test of work with students showed that by introducing a system for online teaching, we directly affect the improvement and quality of teaching. Conclusion: Considering all the results, it can be concluded that the transition to the online way of teaching allows end listeners a comprehensive transfer of knowledge as well as re-listening to the same. This model can be used for an unlimited number of users in all Institutions, regardless of whether the field of activity of these Institutions is of educational origin.