Videogames (VGs) are highly attractive for children and young people. Although videogames were once viewed mainly as sources of distraction and leisure, they are now widely recognised as powerful tools for competence development across diverse domains. Designing and implementing a videogame is even more appealing for children and novice students than merely playing it, but developing programming competencies using a text-based language often constitutes a significant barrier to entry. This article presents the implementation and evaluation of a videogame development experience with university students using the Unity engine and its Visual Scripting block-based tool. Students worked in teams and successfully completed videogame projects, demonstrating substantial gains in programming and game construction skills. The adopted methodology facilitated learning, collaboration, and engagement. Building on a quasi-experimental design that compared a prior unit based on C# and MonoGame with a subsequent unit based on Unity Visual Scripting, the study analyses differences in performance, development effort, and motivational indicators. The results show statistically significant improvements in grades, reduced development time for core mechanics, and higher self-reported confidence when Visual Scripting is employed. The evidence supports the view of Visual Scripting as an effective educational strategy to introduce programming concepts without the syntactic and semantic barriers of traditional text-based languages. The findings further suggest that Unity Visual Scripting can act as a didactic bridge towards advanced programming, and that its adoption in secondary and primary education is promising both for reinforcing traditional subjects (history, language, mathematics) and for fostering foundational programming and videogame development skills in an inclusive manner.
The selective determination of tryptophan in pasteurized milk is an indicator of quality, as its presence indicates that the process has been carried out at the correct temperatures. Tryptophan analysis is costly for industries, but the use of a sensor would reduce both costs and analysis times. A sensor using l-tryptophan dehydrogenase (TrpDH) was optimized, with the system immobilized using an electrode to quantify the tryptophan content in industrial milk. The stability of the enzyme was studied at a controlled temperature of 4 °C, and it was observed that it maintained 90
Background: Nutritional status assessment is the cornerstone of the Nutrition Care Process, guiding diagnosis, intervention, and monitoring. The classical ABCD model (Anthropometry, Biochemical, Clinical, Dietary) has been widely applied; however, it presents limitations in addressing current nutritional and epidemiological challenges. Objective: This narrative review aims to synthesize and update the scientific evidence on the expanded nutritional assessment model, known as ABCDEFG, which incorporates the Ecological–microbiota (E), Functional (F), and Genomic–nutrigenomic (G) approaches. Methods: A narrative review of the literature was conducted through PubMed, Scopus, and Web of Science, covering publications from 2013 to 2025. Articles were selected based on relevance to at least one of the seven assessment domains. Findings were synthesized descriptively and critically, highlighting applications, strengths, and limitations. Results: The ABCDEFG framework offers a multidimensional perspective of nutritional assessment. While anthropometric, biochemical, clinical, and dietary methods remain essential, the inclusion of ecological dimensions (gut microbiota, environmental influences), functional measures (e.g., muscle strength, physical performance), and genomics enables a more sensitive and personalized evaluation. This integrative approach supports better clinical decision-making and research innovation in nutrition and health sciences. Conclusions: The seven-method model broadens the scope of nutritional assessment, bridging traditional and emerging tools. Its application enhances the capacity to identify nutritional risks, design targeted interventions, and advance precision nutrition.
The growing demand for lifelong learning and workforce adaptability has positioned micro-credentials as a strategic innovation in higher education systems worldwide. While individual micro-credentials initiatives have expanded rapidly, their effectiveness and sustainability increasingly depend on coherent national and system-level ecosystems that integrate governance, quality assurance, and technological infrastructure. This study conducts a scoping review of the international literature on national and institutional ecosystems of stackable micro-credentials in higher education, following the PRISMA-ScR guidelines. Searches were conducted primarily in Scopus, complemented by searches in Web of Science (Core Collection) and ERIC, as well as relevant grey literature from international organizations. A total of 18 studies were included after systematic screening and eligibility assessment. The results reveal converging conceptual frameworks that position micro-credentials within lifelong learning systems, alongside diverse governance models ranging from state-led to hybrid arrangements. Key enabling mechanisms include alignment with national qualifications frameworks, robust quality assurance processes, and interoperable digital credentialing systems. However, persistent challenges remain, particularly in developing regions, where fragmented governance and limited regulatory clarity constrain implementation. Drawing on these findings, the study highlights evidence-informed implications for the development of a national stackable micro-credentials ecosystem in Ecuador, contributing to policy-oriented debates on the future of higher education.
The rapid integration of Industry 4.0 technologies into non-computer engineering curricula presents a significant pedagogical challenge: avoiding a “one-size-fits-all” approach. While Project-Based Learning (PBL) is widely advocated for teaching Internet of Things (IoT), little research addresses how students from different engineering branches—specifically Industrial, Environmental, and Electrical—respond to identical technical requirements. This study evaluates the deployment of ESP32-based IoT solutions for local agriculture and beekeeping problems in the Peruvian Andes, analyzing the performance and perception of three distinct student cohorts (Total N = 95). Results indicate a significant divergence in learning outcomes and satisfaction. The cohort predominantly composed of Industrial Engineering students (NRC-33563) demonstrated lower adherence to technical code modularization (88% vs. 97%) and lower overall course recommendation rates compared to the mixed cohorts (NRC-33562/33561), who reported higher engagement with the hardware implementation. These findings suggest that while Environmental and Electrical engineering students naturally align with the sensing and actuation layers of IoT, Industrial engineering students may require a curriculum that emphasizes process optimization and data analytics over raw firmware development. We propose a differentiated pedagogical framework to maximize engagement and competency acquisition across diverse engineering disciplines.
