Abstract
This paper presents an action research study aiming to motivate undergraduate students to develop their computer programming learning skills, particularly within the transition from beginner to proficient level. The SimProgramming motivational approach is presented as a didactic proposal for this context. From the results of this iterative research process, we concluded that SimProgramming is a promising tool for teaching computer programming skills in intermediate classes, with potential to be used and/or applied in other educational contexts. © 2021, Springer Nature Switzerland AG.

Abstract
Augmented Reality (AR) is a field of knowledge that emerged in the middle of the last century, and its use has been spreading because of its usefulness, but also because of mobile platforms, accessible to most users. AR characteristics are valued in several fields of human activity, and also in the field of Education and Training, being AR pointed out as useful to the learning process. In this paper we search and analyse surveys and reviews of AR. We present a AR’s definition, and we create a classification scheme of two dimensions for AR: the dimension of the fields of application of AR, and the dimension of the technologies of AR. © 2021, Springer Nature Switzerland AG.

Abstract
In the competitive automotive market, where extremely high-quality standards must be ensured independently of the growing product and manufacturing complexity brought by customization, reliable and precise detection of any non-conformities before the vehicle leaves the assembly line is paramount. In this paper we propose a wearable solution to aid quality control workers in the detection, visualization and relay of any non-conformities, while also reducing known performance issues such as skill gaps and fatigue, and improving training methods. We also explore how the reliability, precision and validity tests of the visualization module of our framework were performed, guaranteeing a 0% chance occurrence of undesired non-conformities in the following usability tests and training simulator. © 2021, Springer Nature Switzerland AG.

Abstract
The fields of artificial intelligence, knowledge inference, data science, etc. have been deeply studied over time and many theoretical approaches have been developed, including its application to health and diseases inference. The creation of prototype and consumer systems has been restrained by the technology limitations on data acquisition and processing, which has been greatly overcome with the new sensors and mobile devices technologies. So, in this work we go through a literature review of the current state of the art on record to the usage of mobile technologies for diseases inference. The review methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The criteria were based on journal articles, prior to 2008, and using the defined keywords. A total of 14 selected articles were analyzed. A general conclusion was attained regarding the current state of maturity of the field, leading to fully functional consumer and professional market products.

Abstract
Tailoring of the user experience to each individuals needs and preferences can lead to more accessible solutions. Adaptation has a key role on matching the systems characteristics with the user needs. This can be achieved with personalization (system-driven adaptation) or customization (user-driven adaptation). Personalization have good results on matching the user needs but raises concerns about privacy and how the information is retrieved. Customizations require that the user manually choose the preferences configuration. This article proposed two versions of a web wizard to elicit the accessibility preferences. One version was based on a quiz and the other one presented small interactive activities. The activities version was proposed to help reduce the burden of configuration by implicitly eliciting the user preferences through interactive small activities. The preliminary results with healthy participants suggest that both versions obtained a positive evaluation. However, there was no major difference between each wizard. The causes of these findings are discussed.

Abstract
According to the author's knowledge task scheduling in fog paradigm is highly complex and in the literature there are still few studies on it. In the cloud architecture, it is widely studied and in many researches, it is approached from the perspective of service providers. Trying to bring innovative contributions in these areas, in this paper, we propose a solution to the context-aware task-scheduling problem for fog paradigm. In our proposal, different context parameters are normalized through Min Max normalization, requisition priorities are defined through the application of the Multiple Linear Regression (MLR) technique and scheduling is performed using Multi-Objective Non-Linear Programming Optimization (MONLIP) technique.