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About

About

I graduated in Mathematics Applied to Computer Science, from Faculty of Sciences (UP) in 1995, and took my MSc in Foundations of Advanced Information Technology, from Imperial College, London, in 1997. In 2004 I concluded my PhD in Computer Science in concurrent and distributed programming.

I am currently an Assistant Professor, with tenure, at Faculty of Sciences in University of Porto. My research interests are in the areas of text and web mining, community detection, e-learning and web-based learning and standards in education.

I'm also a researcher in the CRACS Research Unit where I have been leading international projects involving University of University of Porto, Texas at Austin, University of Coimbra and University of Aveiro, regarding the automatic detection of relevance in social networks.

Interest
Topics
Details

Details

002
Publications

2022

Automated Assessment in Computer Science Education: A State-of-the-Art Review

Authors
Paiva, JC; Leal, JP; Figueira, Á;

Publication
ACM Transactions on Computing Education

Abstract
Practical programming competencies are critical to the success in computer science education and go-to-market of fresh graduates. Acquiring the required level of skills is a long journey of discovery, trial and error, and optimization seeking through a broad range of programming activities that learners must perform themselves. It is not reasonable to consider that teachers could evaluate all attempts that the average learner should develop multiplied by the number of students enrolled in a course, much less in a timely, deeply, and fairly fashion. Unsurprisingly, exploring the formal structure of programs to automate the assessment of certain features has long been a hot topic among CS education practitioners. Assessing a program is considerably more complex than asserting its functional correctness, as the proliferation of tools and techniques in the literature over the past decades indicates. Program efficiency, behavior, readability, among many other features, assessed either statically or dynamically, are now also relevant for automatic evaluation. The outcome of an evaluation evolved from the primordial boolean values to information about errors and tips on how to advance, possibly taking into account similar solutions. This work surveys the state-of-the-art in the automated assessment of CS assignments, focusing on the supported types of exercises, security measures adopted, testing techniques used, type of feedback produced, and the information they offer the teacher to understand and optimize learning. A new era of automated assessment, capitalizing on static analysis techniques and containerization, has been identified. Furthermore, this review presents several other findings from the conducted review, discusses the current challenges of the field, and proposes some future research directions.

2022

What Makes a Movie Get Success? A Visual Analytics Approach

Authors
Vaz B.; de Fátima Barros M.; Lavoura M.J.; Figueira Á.;

Publication
Marketing and Smart Technologies - Smart Innovation, Systems and Technologies

Abstract

2021

Profiling Accounts Political Bias on Twitter

Authors
Guimaraes, N; Figueira, A; Torgo, L;

Publication
2021 16th Iberian Conference on Information Systems and Technologies (CISTI)

Abstract

2021

Towards a pragmatic detection of unreliable accounts on social networks

Authors
Guimarães, N; Figueira, A; Torgo, L;

Publication
Online Social Networks and Media

Abstract

2021

Covid-19 Impact on Higher Education Institution’s Social Media Content Strategy

Authors
Coelho, T; Figueira, A;

Publication
Lecture Notes in Computer Science

Abstract

Supervised
thesis

2021

Reasoning on Semantic Representations of Source Code to Support Programming Education

Author
José Carlos Costa Paiva

Institution
UP-FCUP

2021

Predictive Geovisual Analytics for Early Warning Systems

Author
Pedro Gonçalves

Institution
UP-FCUP

2021

Recommendation System for the News Market

Author
Miguel Ângelo Rebelo

Institution
UP-FCUP

2021

Towards realistic scenarios concerning the identification of unreliable information in social networks

Author
Nuno Ricardo Pinheiro da Silva Guimarães

Institution
UP-FCUP

2021

Análise de publicações no Twitter nas Instituições do Ensino Superior do topo de Ranking Mundial

Author
Tiago da Silva Coelho

Institution
UP-FCUP