134 Search Results for "Portela, Filipe"


Volume

OASIcs, Volume 133

6th International Computer Programming Education Conference (ICPEC 2025)

ICPEC 2025, July 10-11, 2025, PORTIC, Polytechnic of Porto, Portugal

Editors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

Volume

OASIcs, Volume 120

13th Symposium on Languages, Applications and Technologies (SLATE 2024)

SLATE 2024, July 4-5, 2024, Águeda, Portugal

Editors: Mário Rodrigues, José Paulo Leal, and Filipe Portela

Volume

OASIcs, Volume 113

12th Symposium on Languages, Applications and Technologies (SLATE 2023)

SLATE 2023, June 26-28, 2023, Vila do Conde, Portugal

Editors: Alberto Simões, Mario Marcelo Berón, and Filipe Portela

Volume

OASIcs, Volume 94

10th Symposium on Languages, Applications and Technologies (SLATE 2021)

SLATE 2021, July 1-2, 2021, Vila do Conde/Póvoa de Varzim, Portugal

Editors: Ricardo Queirós, Mário Pinto, Alberto Simões, Filipe Portela, and Maria João Pereira

Volume

OASIcs, Volume 91

Second International Computer Programming Education Conference (ICPEC 2021)

ICPEC 2021, May 27-28, 2021, University of Minho, Braga, Portugal

Editors: Pedro Rangel Henriques, Filipe Portela, Ricardo Queirós, and Alberto Simões

Volume

OASIcs, Volume 81

First International Computer Programming Education Conference (ICPEC 2020)

ICPEC 2020, June 25-26, 2020, ESMAD, Vila do Conde, Portugal (Virtual Conference)

Editors: Ricardo Queirós, Filipe Portela, Mário Pinto, and Alberto Simões

Document
Complete Volume
OASIcs, Volume 133, ICPEC 2025, Complete Volume

Authors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
OASIcs, Volume 133, ICPEC 2025, Complete Volume

Cite as

6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 1-226, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@Proceedings{queiros_et_al:OASIcs.ICPEC.2025,
  title =	{{OASIcs, Volume 133, ICPEC 2025, Complete Volume}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{1--226},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025},
  URN =		{urn:nbn:de:0030-drops-245929},
  doi =		{10.4230/OASIcs.ICPEC.2025},
  annote =	{Keywords: OASIcs, Volume 133, ICPEC 2025, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Ricardo Queirós, Mário Pinto, Filipe Portela, and Alberto Simões

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 0:i-0:xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{queiros_et_al:OASIcs.ICPEC.2025.0,
  author =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{0:i--0:xii},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.0},
  URN =		{urn:nbn:de:0030-drops-245910},
  doi =		{10.4230/OASIcs.ICPEC.2025.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Enabling Secure Coding: Exploring GenAI for Developer Training and Education

Authors: Sathwik Amburi, Tiago Espinha Gasiba, Ulrike Lechner, and Maria Pinto-Albuquerque

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
The rapid adoption of GenAI for code generation presents unprecedented opportunities and significant security challenges. Raising awareness about secure coding is critical for preventing software vulnerabilities. To investigate how Generative AI can best support secure coding, we built an AI Secure Coding platform, an interactive training environment that embeds a GPT-4 based chatbot directly into a structured challenge workflow. The platform comprises a landing page, a challenges page with three AI-generated tasks, and a challenge page where participants work with code snippets. In each challenge, developers (1) identify vulnerabilities by reviewing code and adding comments, (2) ask the AI for help via a chat based interface, (3) review and refine comments based on AI feedback, and (4) fix vulnerabilities by submitting secure patches. The study involved 18 industry developers tackling three challenges. Participants used the AI Secure Coding Platform to detect and remediate vulnerabilities and then completed a survey to capture their opinions and comfort level with AI assisted platform for secure coding. Results show that AI assistance can boost productivity, reduce errors, and uncover more defects when treated as a "second pair of eyes," but it can also foster over-reliance. This study introduces the AI Secure Coding platform, presents preliminary results from a initial study, and shows that embedding GenAI into a structured secure-coding workflow can both enable and challenge developers. This work also opens the door to a new research field: leveraging GenAI to enable secure software development.

Cite as

Sathwik Amburi, Tiago Espinha Gasiba, Ulrike Lechner, and Maria Pinto-Albuquerque. Enabling Secure Coding: Exploring GenAI for Developer Training and Education. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{amburi_et_al:OASIcs.ICPEC.2025.2,
  author =	{Amburi, Sathwik and Espinha Gasiba, Tiago and Lechner, Ulrike and Pinto-Albuquerque, Maria},
  title =	{{Enabling Secure Coding: Exploring GenAI for Developer Training and Education}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{2:1--2:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.2},
  URN =		{urn:nbn:de:0030-drops-240321},
  doi =		{10.4230/OASIcs.ICPEC.2025.2},
  annote =	{Keywords: Secure Coding, Industry, Software Development, Generative AI, Large Language Models, Teaching}
}
Document
On the Use of Concept Maps to Improve Student Skills in an Introductory Object-Oriented Analysis and Design Course

Authors: José F. Vélez, A. Belén Moreno, Victoria Ruiz-Parrado, and Ángel Sánchez

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
This paper presents an ongoing work on the application of concept maps to teaching an introductory Object-Oriented Analysis and Design course for Computer Science students. There exist previous works that introduce the concept map model in these object-oriented courses. However, these works do not usually go deeply enough into the transition from concept maps to static class diagrams. Although concept maps present some clear advantages when defining the abstractions present in object-oriented software modeling, some drawbacks may also appear if the transformation from these maps to class diagrams when the task is carried out through simplistic rules. In this paper we propose an approach, which is illustrated through a use case, to transition from a concept map to a static class diagram in a more realistic way.

Cite as

José F. Vélez, A. Belén Moreno, Victoria Ruiz-Parrado, and Ángel Sánchez. On the Use of Concept Maps to Improve Student Skills in an Introductory Object-Oriented Analysis and Design Course. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 3:1-3:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{velez_et_al:OASIcs.ICPEC.2025.3,
  author =	{V\'{e}lez, Jos\'{e} F. and Moreno, A. Bel\'{e}n and Ruiz-Parrado, Victoria and S\'{a}nchez, \'{A}ngel},
  title =	{{On the Use of Concept Maps to Improve Student Skills in an Introductory Object-Oriented Analysis and Design Course}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{3:1--3:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.3},
  URN =		{urn:nbn:de:0030-drops-240337},
  doi =		{10.4230/OASIcs.ICPEC.2025.3},
  annote =	{Keywords: Object-Oriented Programming, Concept Map, Abstraction, Unified Modeling Language (UML), Static Class Diagram}
}
Document
Exploring Mutation Testing for Teaching Introductory Programming

Authors: Pedro Vasconcelos

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
This paper proposes the use of introductory programming assignments based on mutation testing where students are asked to write tests rather than code. We believe such exercises can be used to teach code reading skills before students could write the corresponding programs on their own. Furthermore, feedback for such exercises can be automatically generated using testing tools. We have extended an existing web-based system for programming exercises with such mutation testing assignments and show some example use cases. This is on-going work that has yet to be validated in the classroom.

Cite as

Pedro Vasconcelos. Exploring Mutation Testing for Teaching Introductory Programming. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 1:1-1:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{vasconcelos:OASIcs.ICPEC.2025.1,
  author =	{Vasconcelos, Pedro},
  title =	{{Exploring Mutation Testing for Teaching Introductory Programming}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{1:1--1:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.1},
  URN =		{urn:nbn:de:0030-drops-240319},
  doi =		{10.4230/OASIcs.ICPEC.2025.1},
  annote =	{Keywords: mutation testing, programming education}
}
Document
The Influence of GenAI on the Evaluation of Computer Programming Students in Higher Education

Authors: Teresa Terroso and Mário Pinto

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
Artificial Intelligence (AI) has assumed an increasingly prominent role in education, transforming the dynamics of teaching and learning while introducing new pedagogical opportunities and challenges. In computer programming education, generative AI tools have had a particularly profound impact. Historically, computer programming education has emphasized problem-solving skills, syntax accuracy, and code efficiency. However, the emergence of generative AI models capable of supporting automatic code generation, producing high-quality code snippets and entire programs, personalized explanations and tutoring, and real-time debugging, has triggered a paradigm shift. These tools make learning processes and assessment less effective and less clear about students' true knowledge. In this context, the paper explores three key dimensions: the broader impact of AI in education, the new challenges that AI presents in teaching and learning computer programming in higher education, and the implications for student assessment, an essential element of the educational process. To investigate these topics, we conducted an online survey targeting Portuguese higher education instructors teaching programming-related courses. Our primary objective was to understand the changes introduced in evaluation methods and criteria due to the growing use of generative AI tools, particularly those focused on code generation.

Cite as

Teresa Terroso and Mário Pinto. The Influence of GenAI on the Evaluation of Computer Programming Students in Higher Education. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 18:1-18:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{terroso_et_al:OASIcs.ICPEC.2025.18,
  author =	{Terroso, Teresa and Pinto, M\'{a}rio},
  title =	{{The Influence of GenAI on the Evaluation of Computer Programming Students in Higher Education}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{18:1--18:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.18},
  URN =		{urn:nbn:de:0030-drops-240482},
  doi =		{10.4230/OASIcs.ICPEC.2025.18},
  annote =	{Keywords: Generative Artificial Intelligence, Computer Programming Education, Student Assessment, Teaching and Learning, Higher Education}
}
Document
Osiris: A Multi-Language Transpiler for Educational Purposes

Authors: Breno Marrão, José Paulo Leal, and Ricardo Queirós

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
While server-side assessment of programming exercises, with its ease of installing diverse compilers and execution environments, is common, it presents three key limitations: the necessity of a constant Internet connection, increased bandwidth consumption, and centralized execution load. The alternative is to rely on JavaScript, the single programming language supported by all standard web browsers. This paper introduces Osiris, a pure JavaScript multi-language transpiler designed to enable the execution of diverse programming languages within web browsers. Targeted primarily at Virtual Learning Environments (VLE) for language programming education, Osiris employs a parser generator to translate small student programs into JavaScript based on language-specific grammars with semantic rules. It also includes a comprehensive, though not exhaustive, JavaScript library that emulates the standard libraries of its supported languages. Validation of Osiris indicates the pedagogical effectiveness of browser-based transpilation for introductory programming education.

Cite as

Breno Marrão, José Paulo Leal, and Ricardo Queirós. Osiris: A Multi-Language Transpiler for Educational Purposes. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{marrao_et_al:OASIcs.ICPEC.2025.17,
  author =	{Marr\~{a}o, Breno and Leal, Jos\'{e} Paulo and Queir\'{o}s, Ricardo},
  title =	{{Osiris: A Multi-Language Transpiler for Educational Purposes}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{17:1--17:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.17},
  URN =		{urn:nbn:de:0030-drops-240471},
  doi =		{10.4230/OASIcs.ICPEC.2025.17},
  annote =	{Keywords: Transpiler, Programming Education, JavaScript, Python, Virtual Learning Environments, Client-Side Execution}
}
Document
Can Open Large Language Models Catch Vulnerabilities?

Authors: Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
As Large Language Models (LLMs) become increasingly integrated into secure software development workflows, a critical question remains unanswered: can these models not only detect insecure code but also reliably classify vulnerabilities according to standardized taxonomies? In this work, we conduct a systematic evaluation of three state-of-the-art LLMs - Llama3, Codestral, and Deepseek R1 - using a carefully filtered subset of the Big-Vul dataset annotated with eight representative Common Weakness Enumeration categories. Adopting a closed-world classification setup, we assess each model’s performance in both identifying the presence of vulnerabilities and mapping them to the correct CWE label. Our findings reveal a sharp contrast between high detection rates and markedly poor classification accuracy, with frequent overgeneralization and misclassification. Moreover, we analyze model-specific biases and common failure modes, shedding light on the limitations of current LLMs in performing fine-grained security reasoning.These insights are especially relevant in educational contexts, where LLMs are being adopted as learning aids despite their limitations. A nuanced understanding of their behaviour is essential to prevent the propagation of misconceptions among students. Our results expose key challenges that must be addressed before LLMs can be reliably deployed in security-sensitive environments.

Cite as

Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque. Can Open Large Language Models Catch Vulnerabilities?. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 4:1-4:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{gasparlopes_et_al:OASIcs.ICPEC.2025.4,
  author =	{Gaspar Lopes, Diogo and Espinha Gasiba, Tiago and Amburi, Sathwik and Pinto-Albuquerque, Maria},
  title =	{{Can Open Large Language Models Catch Vulnerabilities?}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{4:1--4:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.4},
  URN =		{urn:nbn:de:0030-drops-240340},
  doi =		{10.4230/OASIcs.ICPEC.2025.4},
  annote =	{Keywords: Large Language Models (LLMs), Secure Coding, CWE Classification, Machine Learning, Software Vulnerability Detection, Artificial Intelligence, Code Analysis, Big-Vul Dataset}
}
Document
Integrating Questions About Learners’ Code in an Automated Assessment System

Authors: Afonso B. Caniço and André L. Santos

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)


Abstract
Questions about Learners' Code (QLCs) assess programming students' program comprehension skills by providing personalised questions targeting the students' own program code. We conducted a preliminary, experimental implementation of integrating QLCs in the Automated Assessment System (AAS) used in an introductory programming course using Java. QLCs targeted some of the code assignments which students had to complete during the course. We collected 889 answers to QLCs, answered by 13 students over five course modules. We found that as the complexity of exercises increases, the success rate of the same type of QLC may not improve, and even exhibit a decline over time. We further analysed incorrect answers individually to relate them to possible misconceptions.

Cite as

Afonso B. Caniço and André L. Santos. Integrating Questions About Learners’ Code in an Automated Assessment System. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 5:1-5:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{canico_et_al:OASIcs.ICPEC.2025.5,
  author =	{Cani\c{c}o, Afonso B. and Santos, Andr\'{e} L.},
  title =	{{Integrating Questions About Learners’ Code in an Automated Assessment System}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{5:1--5:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.5},
  URN =		{urn:nbn:de:0030-drops-240353},
  doi =		{10.4230/OASIcs.ICPEC.2025.5},
  annote =	{Keywords: programming education, student assessment, program comprehension, questions about learners’ code}
}
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