Cookies
O website necessita de alguns cookies e outros recursos semelhantes para funcionar. Caso o permita, o INESC TEC irá utilizar cookies para recolher dados sobre as suas visitas, contribuindo, assim, para estatísticas agregadas que permitem melhorar o nosso serviço. Ver mais
Aceitar Rejeitar
  • Menu
Publicações

Publicações por CRACS

2022

Managing Gamified Programming Courses with the FGPE Platform

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

Publicação
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

Integration of Computer Science Assessment into Learning Management Systems with JuezLTI

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

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

Abstract
Computer science is a skill that will continue to be in high demand in the foreseeable future. Despite this trend, automated assessment in computer science is often hampered by the lack of systems supporting a wide range of topics. While there is a number of open software systems and programming exercise collections supporting automated assessment, up to this date, there are few systems that offer a diversity of exercises ranging from computer programming exercises to markup and databases languages. At the same time, most of the best-of-breed solutions force teachers and students to alternate between the Learning Management System - a pivotal piece of the e-learning ecosystem - and the tool providing the exercises. This issue is addressed by JuezLTI, an international project whose goal is to create an innovative tool to allow the automatic assessment of exercises in a wide range of computer science topics. These topics include different languages used in computer science for programming, markup, and database management. JuezLTI borrows part of its name from the IMS Learning Tools Interoperability (IMS LTI) standard. With this standard, the tool will interoperate with reference systems such as Moodle, Sakai, Canvas, or Blackboard, among many others. Another contribution of JuezLTI will be a pool of exercises. Interoperability and content are expected to foster the adoption of JuezLTI by many institutions. This paper presents the JuezLTI project, its architecture, and its main components. © Carrillo, Juan V.; Sierra, Alberto; Leal, Jose Paulo; Queirs, Ricardo; Pellicer, Salvador; Primo, Marco; licensed under Creative Commons License CC-BY 4.0

2022

A Roadmap to Convert Educational Web Applications into LTI Tools

Autores
Leal, JP; Queirós, R; Ferreirinha, P; Swacha, J;

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

Abstract
This paper proposes a roadmap to integrate existing educational web applications into the ecosystem based on a learning management system. To achieve this integration, applications must support the Learning Tools Interoperability specification in the role of tool provider. The paper starts with an overview of the evolution of this specification, emphasizing the main features of the current stable version. Then, it proposes a set of design goals and milestones to guide the adaptation process. The proposed roadmap was validated with existing applications. This paper reports on the challenges faced to apply it in these concrete cases. © Leal, Jose Paulo; Queirs, Ricardo; Ferreirinha, Pedro; Swacha, Jakub; licensed under Creative Commons License CC-BY 4.0

2022

Large Semantic Graph Summarization Using Namespaces

Autores
da Costa, ARSL; Santos, A; Leal, JP;

Publicação
11th Symposium on Languages, Applications and Technologies, SLATE 2022, July 14-15, 2022, Universidade da Beira Interior, Covilhã, Portugal.

Abstract
We propose an approach to summarize large semantics graphs using namespaces. Semantic graphs based on the Resource Description Framework (RDF) use namespaces on their serializations. Although these namespaces are not part of RDF semantics, they have intrinsic meaning. Based on this insight, we use namespaces to create summary graphs of reduced size, more amenable to be visualized. In the summarization, object literals are also reduced to their data type and the blank nodes to a group of their own. The visualization created for the summary graph aims to give insight of the original large graph. This paper describes the proposed approach and reports on the results obtained with representative large semantic graphs. © Ana Rita Santos Lopes da Costa, André Santos, and José Paulo Leal.

2022

Generation of Document Type Exercises for Automated Assessment

Autores
Leal, JP; Queirós, R; Primo, M;

Publicação
11th Symposium on Languages, Applications and Technologies, SLATE 2022, July 14-15, 2022, Universidade da Beira Interior, Covilhã, Portugal.

Abstract
This paper describes ongoing research to develop a system to automatically generate exercises on document type validation. It aims to support multiple text-based document formalisms, currently including JSON and XML. Validation of JSON documents uses JSON Schema and validation of XML uses both XML Schema and DTD. The exercise generator receives as input a document type and produces two sets of documents: valid and invalid instances. Document types written by students must validate the former and invalidate the latter. Exercises produced by this generator can be automatically accessed in a state-of-the-art assessment system. This paper details the proposed approach and describes the design of the system currently being implemented. © José Paulo Leal, Ricardo Queirós, and Marco Primo.

2022

A Matching Algorithm to Assess Web Interfaces

Autores
Leal, JP; Primo, M;

Publicação
ADVANCED RESEARCH IN TECHNOLOGIES, INFORMATION, INNOVATION AND SUSTAINABILITY, ARTIIS 2022, PT I

Abstract
The work presented in this article is part of ongoing research on the automated assessment of simple web applications. The proposed algorithm compares two interfaces by mapping their elements, using properties to identify those with the same role in both interfaces. The algorithm proceeds in three stages: firstly, it selects the relevant elements from both interfaces; secondly, it refines elements' attributes, excluding some and computing new ones; finally, it matches elements based on attribute similitude. The article includes an experiment to validate the algorithm as an assessment tool. As part of this experiment, a set of experts classified multiple web interfaces. Statistical analysis found a significant correlation between classifications made by the algorithm and those made by experts. The article also discusses the exploitation of the algorithm's output to access both the layout and functionality of a web interface and produce feedback messages in an automated assessment environment, which is planned as future research.

  • 20
  • 200