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Publications

Publications by Verónica Silva Vasconcelos

2023

A Teacher-Focused Impact Assessment in Scratch4All Project

Authors
Vasconcelos, V; Bigotte, E; Marques, L; Almeida, R;

Publication
Iberian Conference on Information Systems and Technologies, CISTI

Abstract
The 'Scratch4All' project aims to reduce school dropout rates by encouraging and motivating students in the 1st, 2nd, and 3rd cycles of elementary schools to achieve academic success. In addition, the project promotes true equality of opportunity in terms of educational resources. A learning environment that contributes positively to the improvement of educational results is created through the use of new technologies, specifically programming in the Scratch language and robotics. Impact indicators were developed and used as project evaluation tools based on Theory of Change. This paper presents and analyzes the changes observed from the perspective of the project's teachers' stakeholders during the 2020/2021 school year. This group of beneficiaries is critical to the project's success and continuation, not only because of the special relationship they have with the students, but also with their families and the school. The assessment of impact is very positive in terms of indicators such as school success and motivation, particularly in Mathematics and Portuguese Language, as well as in the reduction of inequalities, access to new technologies, and contribution to gender equality. © 2023 ITMA.

2023

An integrated framework for STEM education experiments with focus on sustainability and renewable energies

Authors
Vasconcelos, V; Bigotte, E; Almeida, R; Amaro, J; Marques, L;

Publication
EAEEIE 2023 - Proceedings of the 2023 32nd Annual Conference of the European Association for Education in Electrical and Information Engineering

Abstract
In a global world, within the context of an unprecedented climate crisis, STEM education may decisively contribute to sustainable economic growth. Within this context, Portugal has been following EU guidelines by creating programs that encourage students and teachers to envision STEM education with innovative methodologies. Today's schools should provide students with motivating approaches to increase their interest in enrolling STEM courses and professions. Despite all the efforts, the results are still far from the desired goals in some areas, such as electrical engineering. In this paper, an articulation program between Coimbra Institute of Engineering (ISEC), secondary schools, and a Private Social Solidarity Institution - CASPAE, being developed under the PO ISE Program, co-financed by EU, is described. The main objective of this program is to promote STEM subjects next to young students, in an interesting, experimental and interactive environment. The program proposes several experiments that are closely related to renewable energies and sustainable energy use, in which STEM knowledge is mandatory. With technical support from ISEC, a set of interactive experiments of real-world problems was developed. To make each experiment more appealing, a multidisciplinary approach was used, bringing together experts in electrical engineering, computer science, and art designers. Four experiments called "Energy Rivers", "A Breath of Wind", "Sun Flower"and "Kilometer by Kilometer"integrate a physical prototype and a simulator of a Hydroelectric Power Plant, a Photovoltaic Panel, a Wind Turbine, and an Electrical Vehicle, respectively. Each experiment is integrated into an attractive design that suggests the purpose of the experiment, enclosed in portable modules. The set of experiments will travel to schools, thus increasing the project audience target. © 2023 Fontys University of Applied Science.

2023

Scratch4All Project - Educate for an All-inclusive Digital Society

Authors
Vasconcelos, V; Almeida, R; Marques, L; Bigotte, E;

Publication
2023 32ND ANNUAL CONFERENCE OF THE EUROPEAN ASSOCIATION FOR EDUCATION IN ELECTRICAL AND INFORMATION ENGINEERING, EAEEIE

Abstract
Computational thinking is a fundamental competence for the 21st century. It refers to a set of capacities and skills that can be stimulated to facilitate the teaching-learning process in a wide range of fields, including Science, Technology, Engineering and Mathematics (STEM). Experts in information technology argue that the earlier children are exposed to programming through digital platforms appropriate for their age, the easier it will be for them to assimilate their concepts in the future. This effort should be continued throughout the educational stages of children and youth to increase students' interest in pursuing STEM studies and careers. This paper describes the Scratch4All project promoted by the consortium CASPAE ( a Private Social Solidarity Institution) and Inova-Ria, with technical assistance from professors at the public higher education institution Coimbra Institute of Engineering. Scratch4All Project includes the activities Scratch on Road, Programming and Robotics Lab, and the Scratch4All Digital Platform. According to the impact assessment for the school year 2020-2021, the Scratch4All project promotes school success and true equality in access to new technologies for students in the 1st, 2nd, and 3rd cycles of elementary school, developing essential skills for their academic and professional future such as computational thinking, STEM competencies and social skills. By encouraging young girls to participate in technological projects, this project also aims to combat gender stereotypes.

2024

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Authors
Vasconcelos, V; Domingues, I; Paredes, S;

Publication
Lecture Notes in Computer Science

Abstract

2024

Mammogram Retrieval System: Aggregating Image Classifiers for Enhanced Breast Cancer Diagnosis

Authors
Roriz, C; Moreira, I; Vasconcelos, V; Domingues, I;

Publication
ACM International Conference Proceeding Series

Abstract
Breast cancer remains a significant global health concern. This study presents an image retrieval system to aid specialists in the analysis of mammogram images. The system employs individual classifiers for eight dimensions: laterality, view, breast density, BI-RADS classification, masses, calcifications, distortions, and asymmetries. Four pre-trained networks, ResNet50, VGG16, InceptionV3, and InceptionResNetV2, were used to train these classifiers. The retrieval model combines these classifiers through a weighted sum. Four weight assignment strategies were explored, ranging from equal weights to weights based on empirical, literature-based, and specialist-informed considerations. Results are illustrated using the INBreast database, which comprises 410 images. Besides the native annotations, ground truth to validate retrieval models had to be acquired. Classification accuracy is as high as 100% for some of the dimensions. Results also demonstrate the effectiveness of the proposed weighted-sum approach, with variations in weight assignments impacting model performance. © 2024 Owner/Author.

2024

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Authors
Vasconcelos, V; Domingues, I; Paredes, S;

Publication
Lecture Notes in Computer Science

Abstract

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