Abstract
The paper presents the e-facilitator concept and explores the perspective of some professionals in the field (stakeholders) on this role and its competencies. Facilitation in virtual learning environments is a growing challenge when more and more learners find their way to online learning platforms and many universities adapt their courses to digital environments since the global pandemic forced many people to stay at home.

Abstract
Software engineering education requires students to develop technical knowledge and advanced cognitive and behavioral skills, particularly in the transition from novice to proficient. In distance learning, the hurdles are greater because students require greater autonomy, adopting strategies of self and co-regulation of learning. Facing these challenges, the SimProgramming approach has been transposed into the context of DL: e-SimProgramming. In the second iteration of e-SimProgramming implementation (2019/2020), one adaptation was inclusion of metacognitive challenges (MC) to promote students' self-reflection on their learning process. We explain the design of the two types of implemented MCs. We provide qualitative and quantitative analysis of: 1) evolution of MCs submission throughout the semester, identifying regularity and completion within deadlines and their relationship to student success; 2) students' perceptions of MCs. Results show a positive correlation between high MC submission and student success, greater interest and involvement of students in type 2 MCs and positive perceptions of students about MCs.

Abstract

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.

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.

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.