This paper presents a web-based software tool for tutoring support of engineering students without any need of data scientist background for usage. This tool is focused on the analysis of students’ performance, in terms of the observable scores and of the completion of their studies. For that purpose, it uses a data set that only contains features typically gathered by university administrations about the students, degrees and subjects. The web-based tool provides access to results from different analyses. Clustering and visualization in a low-dimensional representation of students’ data help an analyst to discover patterns. The coordinated visualization of aggregated students’ performance into histograms, which are automatically updated subject to custom filters set interactively by an analyst, can be used to facilitate the validation of hypotheses about a set of students. Classification of students already graduated over three performance levels using exploratory variables and early performance information is used to understand the degree of course-dependency of students’ behavior at different degrees. The analysis of the impact of the student’s explanatory variables and early performance in the graduation probability can lead to a better understanding of the causes of dropout. Preliminary experiments on data of the engineering students from the 6 institutions associated to this project were used to define the final implementation of the web-based tool. Preliminary results for classification and drop-out were acceptable since accuracies were higher than 90% in some cases. The usefulness of the tool is discussed with respect to the stated goals, showing its potential for the support of early profiling of students. Real data from engineering degrees of EU Higher Education institutions show the potential of the tool for managing high education and validate its applicability on real scenarios.

The progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient’s home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient’s movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity $\mathcal{O}\left(1\right)$ were tested to improve the signal’s noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor.

Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs.

Virtual learning environments systems are based on the classroom paradigm, in which the knowledge is transmitted for all the students in the same way. To enhance e-learning, adapting the contents to the needs of each student is essential, and a more personalized learning support is required. The adoption of pedagogical agents and new artificial intelligence methodologies can response to the needs of individual students and provide a more effective collaboration in virtual learning environments. The learning experience of each student can be adapted to others students with the same characteristics. The adaptation of past cases to solve new problems is one of the features of case-based reasoning methodology, which can provide an effective knowledge transmission, based on learning activities. In this paper, we present a case-based reasoning approach to Adaptive Web-based Educational Systems using fuzzy logic to adapt e-learning contents and contexts according to the student learning style and individual needs.

Purpose – This paper seeks to investigate and report on the status of identity management systems and e-learning standards across Europe for promoting mobility, collaboration and the sharing of contents and services in higher education institutions. Design/methodology/approach – The present research work examines existing e-learning standards and the tools and processes applied to managing the identity of learners registered for programmes of study in higher education. The paper draws on recent developments and argues that the creation of identity management federations is mandatory to provide the mobility of users and to permit the exchange of contents and services between institutions. Findings – It is revealed that it is crucial to create identity management federation to provide for ease of mobility and facilitate collaboration and sharing information amongst staff and students in higher education. Research limitations/implications – The challenges arising from language, culture and differences in systems for the regions require consideration. Future work intends to incorporate some of these issues, to examine and report on them from the diverse perspectives, taking into account, the impact of globalisation. Originality/value – This paper presents the main features of e-learning standards and how they can be used in conjunction with identity management systems to create collaborative learning objects repositories to promote a more effective learning experience and a more competitive European space for higher education, with respect to the requirements of knowledge-based societies.