Innovative teaching methodologies begat blended learning, which seems to facilitate engineering students’ achievement of competencies required for the 21st century and has proven to be essential to keep quality standards as university education has suffered the COVID-19 pandemic. In this paper, we approach the use of b-learning and digital technologies before the pandemic started, and how it worked like a vaccine, enabling university education resilience and facilitating the sustainability of the students learning process. A questionnaire-based study is presented, in which the data came from Aerospace Engineering students following a Mathematics subject in a Technological University in Spain. ANOVA and ANCOVA analysis provided a significant difference in the appreciation of the adaptation based on the prior application of b-learning methodologies or more traditional methodologies. Results obtained indicated that the use of digital resources and educational platforms caused a noticeable change in the students’ way of learning, improving habits and digital skills.

Generative artificial intelligence is reshaping students’ learning strategies, yet most definitions of “AI competency” rely on self-reports and prescriptive checklists. We analyzed data from N = 686 university students in Spain to uncover behavioral patterns of AI use and translate them into practical guidance for teaching and policy. Using unsupervised clustering (k-means) complemented with a topological summary (Mapper), we identified four coherent profiles along a continuum of engagement and self-regulation: Low-Engagement, Active–Cautious, Balanced–Confident, and High-Use–Vigilant. The profiles differ in how often students use AI, how they revise outputs, their reliance on AI, and their ethical awareness, and they show distinct emotional patterns (e.g., curiosity, motivation, stress). A continuous structure links profiles rather than separating them rigidly. Self-rated digital competence and studying in STEM fields were associated with higher-level profiles. Overall, the results support a layered, data-informed view of AI competency that prioritizes observed practices over single summary scores. We introduce AI CAR as a formative framework to help institutions (i) locate students on this continuum and (ii) design targeted supports that strengthen revision habits, ethical reflection, and self-regulation across the curriculum.

Nowadays we cannot speak of a society without linking it to instant, global and, digital knowledge. Since 2001, Information Society Technology (1ST) associated with a new type of citizens - the digital natives - provoked severe changes to which not only countries, regions, and society, but also individuals, are trying to adapt in a race still not finished. Policies focus on smart growth through the development of knowledge and innovation as a starting point to accomplish the process. The process of adaptation of any digital innovation to local and global challenges makes from resilience a must in a global society. The success of a resilience society comes from the hand of those individuals that form the society. If we live in a digital society growing in digital possibilities as the technology continues improving, those individuals will be evolved digital natives fully experienced and updated because they have grown up in a discovery-driven learning environment. For a resilient society it is crucial to get to know how its new individuals are learning new habits, abilities and capabilities and how they are using them, so that it will be feasible to help them to solve problems still not known with solutions not even imagined. The present work tries to define the new digital citizen that will be fully able to adapt himself to new challenges and quickly recover from old ones.

The upcoming of the European Higher Education Area (EHEA) has brought out a transformation towards more student centered methodologies which go in the line of much more than catching up with the nowadays times and the uprising of the digital new technologies. Encouraging active learning and entrepreneurship are in the skeleton of competencies that the new engineer must achieve for several reasons. Ideas and solutions to new challenges quite often require creative and innovative engineers that have to catch up with a resilient society where environment and conditions are continuously changing. This contrasts with the traditional input-oriented approach to higher education focusing on the transmission of defined curriculum content. Thus there is need to get even further of a learning outcomes orientation, focusing on what the student is expected to know, understand and be able to do. The shift towards a learning outcomes approach is really a major cultural transformation that is taking time to become fully implemented. In order to tackle this issue from the first stages of a just newcomer university student, the authors propose an active methodology in Mathematics theoretical classes for Aerospace Engineering students that provides activities to be developed by them before each theoretical and problem solving exam comes as part of their apprenticeship. In this way the students are faced in front of activities designed to develop their competencies achievement by promoting their deep understanding of the subject and having to confront their engineering skills while learning a basic subject such as Mathematics. Since these activities are not developed in a controlled environment, students must perform an individual test at the time of delivery to check their authorship and understanding of the processes developed at their activities.

Evaluating competencies achieved by students within a subject and its different topics is a multivariable and complex task whose outcome should provide actual information on their evolution. A relevant feature when a continuous assessment (CA) rules this evaluation is to track their learning process so that pertinent feedforward may be harnessed to proactively promote improvement when required. As this process is performed via a number of activities, such as lectures, problem solving, and lab practice, different competencies are developed, depending on the recurrence and type of conducted activity. Measuring and registering their achievement is the leitmotif of competency-based assessment. In this paper, we assemble topic, activity and competency data into a 3D matrix array to form what we call a TAC cuboid. This cuboid showcases a detailed account of each student evolution, aiding instructors and students to design and follow, respectively, an individualized curricular strategy within a continuous and aligned assessment methodology, which facilitates each student to adequately modify his/her level of development of each competency. In addition, we compare the TAC cuboids’ usage in grading a mathematics subject versus a traditional CA method as well as when a dynamical continuous assessment approach is considered to measure the achievement of mathematical competencies.