Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About

About

I was born in Portugal in 1964. I graduated in mathematics from the Faculty of Sciences of the University of Porto and earned a Ph.D. in Computer Science from the same institution.
My current position is auxiliary professor at the Computer Science department of the Faculty of Sciences of the University of Porto. I am also affiliated with the Center for Research in Advanced Computing Systems (CRACS), an R&D unit of INESCTEC Research Laboratory, where I am an effective member.
My main research interests are technology enhanced learning, web adaptability, and semantic web.

Interest
Topics
Details

Details

  • Name

    José Paulo Leal
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2009
003
Publications

2023

PROGpedia: Collection of Source-Code Submitted to Introductory Programming Assignments

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

Publication
DATA IN BRIEF

Abstract

2023

Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedback

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

Publication
Electronics

Abstract
Learning to program requires diligent practice and creates room for discovery, trial and error, debugging, and concept mapping. Learners must walk this long road themselves, supported by appropriate and timely feedback. Providing such feedback in programming exercises is not a humanly feasible task. Therefore, the early and steadily growing interest of computer science educators in the automated assessment of programming exercises is not surprising. The automated assessment of programming assignments has been an active area of research for over a century, and interest in it continues to grow as it adapts to new developments in computer science and the resulting changes in educational requirements. It is therefore of paramount importance to understand the work that has been performed, who has performed it, its evolution over time, the relationships between publications, its hot topics, and open problems, among others. This paper presents a bibliometric study of the field, with a particular focus on the issue of automatic feedback generation, using literature data from the Web of Science Core Collection. It includes a descriptive analysis using various bibliometric measures and data visualizations on authors, affiliations, citations, and topics. In addition, we performed a complementary analysis focusing only on the subset of publications on the specific topic of automatic feedback generation. The results are highlighted and discussed.

2022

Managing Gamified Programming Courses with the FGPE Platform

Authors
Paiva, JC; Queiros, R; Leal, JP; Swacha, J; Miernik, F;

Publication
INFORMATION

Abstract
E-learning tools are gaining increasing relevance as facilitators in the task of learning how to program. This is mainly a result of the pandemic situation and consequent lockdown in several countries, which forced distance learning. Instant and relevant feedback to students, particularly if coupled with gamification, plays a pivotal role in this process and has already been demonstrated as an effective solution in this regard. However, teachers still struggle with the lack of tools that can adequately support the creation and management of online gamified programming courses. Until now, there was no software platform that would be simultaneously open-source and general-purpose (i.e., not integrated with a specific course on a specific programming language) while featuring a meaningful selection of gamification components. Such a solution has been developed as a part of the Framework for Gamified Programming Education (FGPE) project. In this paper, we present its two front-end components: FGPE AuthorKit and FGPE PLE, explain how they can be used by teachers to prepare and manage gamified programming courses, and report the results of the usability evaluation by the teachers using the platform in their classes.

2022

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

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

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

Integration of Computer Science Assessment into Learning Management Systems with JuezLTI

Authors
Carrillo, JV; Sierra, A; Leal, JP; Queirós, R; Pellicer, S; Primo, M;

Publication
Third International Computer Programming Education Conference, ICPEC 2022, June 2-3, 2022, Polytechnic Institute of Cávado and Ave (IPCA), Barcelos, Portugal.

Abstract

Supervised
thesis

2022

Semantic Measures in Large Semantic Graphs

Author
André Fernandes dos Santos

Institution
UP-FCUP

2022

Sumariação de grafos semânticos de grande dimensão usando espaços de nomes

Author
Ana Rita Santos Lopes da Costa

Institution
UP-FCUP

2022

Reasoning on Semantic Representations of Source Code to Support Programming Education

Author
José Carlos Costa Paiva

Institution
UP-FCUP

2021

Integrating multi-source data into HandSpy

Author
Hristo Orlinov Valkanov

Institution
UP-FCUP

2021

Reasoning on Semantic Representations of Source Code to Support Programming Education

Author
José Carlos Costa Paiva

Institution
UP-FCUP