Sobral, Sónia Rolland
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Data de nascimento
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Último Nome
Sobral
Primeiro Nome
Sónia Rolland
Nome
Sónia Rolland Sobral
Biografia
Licenciada em Informática de Gestão, mestre em Engenharia Eletrotécnica e de Computadores, doutora em Tecnologias e Sistemas de Informação e possui o título de agregado em Ciências da Informação. Desde 1993 é docente da Universidade Portucalense (UPT), sendo atualmente professora associada com agregação. Lecionou em diversos cursos como Engenharia Informática e Engenharia e Gestão Industrial, em diversas instituições como Lodz University of Technology e a Universidade de Aveiro, e em diversos países como Angola e Cabo Verde. Participou em diferentes órgãos, tendo sido presidente do Conselho Pedagógico da UPT. Pertence à comissão de várias conferências internacionais e revistas científicas. É autora de uma centena de publicações, a sua maioria indexadas na SCOPUS e/ou WoS. É membro integrado no REMIT – Research on Economics, Management and Information Technologies, sendo atualmente coordenadora de um dos dois grupos de investigação (Transformação Digital e Inovação nas Organizações).
Afiliação:
REMIT – Research on Economics, Management and Information Technologies.
DCT - Departamento de Ciência e Tecnologia.
Identificadores
ED15-C9EC-5996
37091626900
G-2227-2014Projetos de investigação
Unidades organizacionais
REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura.
Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture.
Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations:
- the understanding of local, national and international environment;
- the development of activities oriented to professional practice, namely in the business world.
7 resultados
Resultados da pesquisa
A mostrar 1 - 7 de 7
Publicação Acesso Aberto How Does Learning Analytics Contribute to Prevent Students’ Dropout in Higher Education: A Systematic Literature Review2021-11-04 - Oliveira, Catarina Félix de; Sobral, Sónia Rolland; Ferreira, Maria João; Moreira, FernandoRetention and dropout of higher education students is a subject that must be analysed carefully. Learning analytics can be used to help prevent failure cases. The purpose of this paper is to analyse the scientific production in this area in higher education in journals indexed in Clarivate Analytics’ Web of Science and Elsevier’s Scopus. We use a bibliometric and systematic study to obtain deep knowledge of the referred scientific production. The information gathered allows us to perceive where, how, and in what ways learning analytics has been used in the latest years. By analysing studies performed all over the world, we identify what kinds of data and techniques are used to approach the subject. We propose a feature classification into several categories and subcategories, regarding student and external features. Student features can be seen as personal or academic data, while external factors include information about the university, environment, and support offered to the students. To approach the problems, authors successfully use data mining applied to the identified educational data. We also identify some other concerns, such as privacy issues, that need to be considered in the studies.Publicação Acesso Aberto Enhancing Higher Education in Portugal: Leveraging generative Artificial Intelligence for learning-teaching process2024-10-23 - Santos-Pereira, Carla; Ferreira, Maria João; Sobral, Sónia Rolland; Durão, Natércia; Moreira, FernandoRecent advancements in Generative Artificial Intelligence (GAI) have revolutionized numerous fields, including higher education. This study focuses on the integration of GAI in Portuguese higher education institutions and explores its multifaceted implications and potential. Our research, conducted through a comprehensive survey between April and June 2023, engages with higher education faculty to understand their perceptions and utilization of GAI tools in teaching and learning processes. The potential of GAI to enhance personalized learning and interactive teaching methodologies is significant. It enables the creation of customized educational content, interactive simulations, and real-time feedback mechanisms, thus reducing the educators' workload and enhancing the learning experience. However, this integration is not without challenges. The study identifies critical ethical concerns around the use of GAI, including data privacy, intellectual property, and the potential for bias in AI-generated content. Additionally, our findings indicate varying acceptance and readiness among educators to adopt these technologies. While some express enthusiasm for the potential of GAI to transform educational practices, others remain cautious, highlighting the need for comprehensive training and support to leverage GAI capabilities fully. This paper captures the essence of the study's findings, illustrating both the promising opportunities and the complex challenges associated with using Generative AI in higher education. Higher education institutions can significantly enhance teaching and learning landscapes by addressing these challenges and fostering an informed and ethical approach to GAI integration.Publicação Acesso Aberto Exploring the impact of Artificial Intelligence generative tools on research in Higher Education Institutions: A perspective from Portugal2024-10-23 - Sobral, Sónia Rolland; Ferreira, Maria João; Santos-Pereira, Carla; Durão, Natércia; Moreira, FernandoArtificial Intelligence (AI) generative tools have emerged as transformative instruments in various domains, including research and academia. It is important to see what is positive and what is not. This study focuses on the integration of GAI in Portuguese higher education institutions and explores its multifaceted implications and potential. Our research was conducted through a comprehensive survey between April and June 2023, garnering 77 responses. To this purpose, the analysis will have several insights into the research process, namely, to assess the frequency of use and objectives of using generative AI for higher education research and to explore possible trends and future directions in the adoption and application of generative AI in this field.Publicação Acesso Aberto Proposta de um modelo blended mobile learning orientado ao contexto.2010 - Sobral, Sónia Rolland; Ferreira, Maria João; Moreira, FernandoO aumento constante do número de dispositivos móveis no dia-a-dia da população, em especial junto das camadas mais jovens, leva ao aparecimento de novos paradigmas nas mais diversas áreas de actividade nomeadamente na educação. Como exemplo de um novo paradigma no processo ensino/aprendizagem poderemos invocar o m-learning (mobile learning) que tal como as tecnologias não pararam e evoluiu para o modelo Blended Mobile Learning (BML). Neste artigo é proposto um modelo BML orientado ao contexto, que assenta na utilização de software open source, para o LMS, para o mLMS e para uma ferramenta ligada à programação. O contexto de aprendizagem como factor é um dos aspectos de relevância no modelo devido às condicionantes técnicas e económicas que envolve o BML.Publicação Acesso Aberto Ensino de Redes de Computadores Inserido num Modelo BML Orientado ao Contexto2011 - Sobral, Sónia Rolland; Ferreira, Maria João; Moreira, FernandoO aumento constante do número de dispositivos móveis no dia-a-dia da população em geral e em particular junto das camadas mais jovens, leva ao aparecimento de novos paradigmas nas mais diversas áreas de actividade, nomeadamente na educação. Como exemplo de um novo paradigma no processo ensino/aprendizagem podemos invocar o m-learning (mobile learning) que, tal como as tecnologias, não parou e evoluiu ao integrar-se no modelo Blended Mobile Learning (BML). No trabalho em investigação pretende-se estender um modelo BML orientado ao contexto, que assenta na utilização de software open source, ao ensino de redes de computadores.Publicação Acesso Aberto Interpretable success prediction in a computer networks curricular unit using machine learning2024-07-25 - Oliveira, Catarina Félix de; Sobral, Sónia Rolland; Ferreira, Maria João; Moreira, FernandoToday, higher education institutions are focused on understanding which factors are associated with the failure or success of students to, early on, be able to implement measures that can reduce the low performance of students and even dropout. The retention rate is positively and negatively influenced by factors belonging to several dimensions (personal, environmental, and institutional). We aim to use information from those dimensions to identify students enrolled in a Computer Networks course at risk of failing the subject. Besides, this needs to happen as early as possible, to be able to provide the students, for example, with extra support or resources to try to prevent that negative outcome. For predicting the grade level on the first test, the best accuracy obtained was 55%. However, most C-level grades were correctly classified, with 63% accuracy in predicting the students that are most at risk of failing, which is one of our main objectives. As for the prediction of the second test’s grade level, the best accuracy obtained was 89% and concerned data regarding the students’ interaction with the LMS together with students’ grades history. All the C-level grades were correctly classified (100% accuracy) and so we were able to correctly predict every student at a high risk of failing. Using the procedure described in this paper, we are able to anticipate the students needing extra support, and provide them with different resources, to try to prevent their negative outcome.Publicação Acesso Aberto A Blended Mobile Learning Model-Context Oriented (BML-CO).2010 - Ferreira, Maria João; Sobral, Sónia Rolland; Moreira, FernandoThe steady increase in the number of mobile devices nowadays, particularly among younger people, leads to the emergence of new paradigms in several areas of activity including education. As an example of a new paradigm in the teaching / learning we could refer the m-learning (mobile learning) that, just as technology, has continued and evolved into the Blended Mobile Learning (BML) model. In this paper we propose a BML context oriented model that relies on the use of open source software for the LMS, mLMS and a tool related to the programming environment. The learning context is a relevant aspect of the proposed model by the technical and economic constraints that BML involves.