2021
Autores
Sousa, SC; Martins, P; Cravino, J;
Publicação
ISD
Abstract
2021
Autores
Carvalho, D; Rocha, T; Martins, P; Barroso, J;
Publicação
INNOVATIVE TECHNOLOGIES AND LEARNING
Abstract
Dyscalculia is a specific neurological affliction that disrupts a person's ability to understand and manipulate numbers. We intend to develop a serious game for children who attend primary school (up to 4th grade) and whose purpose is making the learning of basic mathematics (simple arithmetic) easier, by introducing specific mathematical problems and educational games that stimulate memory, among other aspects. To that end, we undertook a straightforward and preliminary evaluation of the serious game developed and present its results. Indeed, we believe that the findings of our pilot case study can be useful to determine some perceptions that may be vital to understanding the problems with teaching mathematics and the issues students face in this regard.
2021
Autores
Sousa, S; Cravino, J; Lamas, D; Martins, P;
Publicação
RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Abstract
In recent years, there has been a growing need for measuring and understand how to foster Trust in technology. This need for understanding the trust factor, which potential transformed (in a short time) the way we work, learn and teach. It allowed us to realize that a simple technological tool per si can be a means to facilitate a task or an objective but not necessarily is a solution to create sustainable interactions. This sustainability comes together with the insurance that irrespective of the ability to monitor or control, we are willing to be vulnerable to another party’s actions based on the expectation that the other will perform a particular action important to us. We define Trust, as an attitude, an intention or behaviour. We see Trust as an interpersonal phenomenon that promotes social activities such as collaboration, sharing, or social capital creation. But also as a factor that facilitates interaction and participation in remote and networked contexts. Trust is an instrument that supports and regulates technological mediation processes, encourages technology interactions and continuous adoption. In this study’s scope, we seek to illustrate the state of the art of the different methodologies of analysis, design and reliable assessment of interactive systems. We were briefly contextualizing the problem and defining Trust from a Human-Computer Interaction point of view. Conclude with a reflection on how and how these practices can be pressing to develop more sustainable online mediation tools, which also encourage the participation of the actors involved. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.
2021
Autores
Reis, A; Barroso, J; Lopes, JB; Mikropoulos, TA; Fan, CW;
Publicação
TECH-EDU
Abstract
2021
Autores
Resende, M; Carvalho, D; Branco, A; Rocha, T;
Publicação
10th International Conference on Digital and Interactive Arts
Abstract
2021
Autores
Vicêncio, D; Silva, H; Soares, S; Filipe, V; Valente, A;
Publicação
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Abstract
Through technological advents from Industry 4.0 and the Internet of Things, as well as new Big Data solutions, predictive maintenance begins to play a strategic role in the increasing operational performance of any industrial facility. Equipment failures can be very costly and have catastrophic consequences. In its basic concept, Predictive maintenance allows minimizing equipment faults or service disruptions, presenting promising cost savings. This paper presents a data-driven approach, based on multiple-instance learning, to predict malfunctions in End-of-Line Testing Systems through the extraction of operational logs, which, while not designed to predict failures, contains valid information regarding their operational mode over time. For the case study performed, a real-life dataset was used containing thousands of log messages, collected in a real automotive industry environment. The insights gained from mining this type of data will be shared in this paper, highlighting the main challenges and benefits, as well as good recommendations, and best practices for the appropriate usage of machine learning techniques and analytics tools that can be implemented in similar industrial environments. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.