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Robotics technology has become increasingly common both for businesses and for private citizens. Primary and secondary schools, as a mirror of societal evolution, have increasingly integrated science, technology, engineering and math concepts into their curricula. Our research questions are: “In teaching robotics to primary and secondary school students, which pedagogical-methodological interventions result in better understanding and knowledge in the use of sensors in educational robotics?”, and “In teaching robotics to primary and secondary school students, which analytical methods related to Learning Analytics processes are proposed to analyze and reflect on students’ behavior in their learning of concepts and skills of sensors in educational robotics?”. To answer these questions, we have carried out a systematic review of the literature in the Web of Science and Scopus databases regarding robotics sensors in primary and secondary education, and Learning Analytics processes. We applied PRISMA methodology and reviewed a total of 24 articles. The results show a consensus about the use of the Learning by Doing and Project-Based Learning methodologies, including their different variations, as the most common methodology for achieving optimal engagement, motivation and performance in students’ learning. Finally, future lines of research are identified from this study.

The privacy policies, terms, and conditions of use in any Learning Management System (LMS) are one-way contracts. The institution imposes clauses that the student can accept or decline. Students, once they accept conditions, should be able to exercise the rights granted by the General Data Protection Regulation (GDPR). However, students cannot object to data processing and public profiling because it would be conceived as an impediment to teachers to execute their work with normality. Nonetheless, regarding GDPR and consulted legal advisors, a student could claim identity anonymization in the LMS, if adequate personal justifications are provided. Per contra, the current LMSs do not have any functionality that enables identity anonymization. This is a big problem that generates undesired situations which urgently requires a definitive solution. In this work, we surveyed students and teachers to validate the feasibility and acceptance of using aliases to anonymize their identity in LMSs as a sustainable solution to the problem. Considering the positive results, we developed a user-friendly plugin for Moodle that enables students’ identity anonymization by the use of aliases. This plugin, presented in this work and named Protected users, is publicly available online at GitHub and published under GNU General Public License.

Data in the educational context are becoming increasingly important in decision-making and teaching-learning processes. Similar to the industrial context, educational institutions are adopting data-processing technologies at all levels. To achieve representative results, the processes of extraction, transformation and uploading of educational data should be ubiquitous because, without useful data, either internal or external, it is difficult to perform a proper analysis and to obtain unbiased educational results. It should be noted that the source and type of data are heterogeneous and that the analytical processes can be so diverse that it opens up a practical problem of management and access to the data generated. At the same time, ensuring the privacy, identity, confidentiality and security of students and their data is a “sine qua non” condition for complying with the legal issues involved while achieving the required ethical premises. This work proposes a modular and scalable data system architecture that solves the complexity of data management and access. On the one hand, it allows educational institutions to collect any data generated in both the teaching-learning and management processes. On the other hand, it will enable external access to this data under appropriate privacy and security conditions.

This study examines the influence of gender composition on corporate financial performance, measured by the Price-to-Earnings (P/E) ratio and Tobin's Q, considering both male and female directors. Using an econometric panel data analysis, a dual fixed effects model and the Generalized Method of Moments (GMM) were applied to all Spanish listed companies from 2017 to 2022. The findings reveal no statistically significant correlation between gender diversity in the boards of directors (hereinafter, the board) and the financial performance indicators analyzed. However, a significant association was observed between gender diversity in non-board managerial positions and improved firm economic performance. This challenges the traditional focus on female representation in boards by highlighting the broader impact of gender composition across corporate structures. This study underscores the need for a comprehensive theoretical framework that considers both male and female directors to better understand gender diversity dynamics in governance. From a practical perspective, the results emphasize the importance of promoting gender diversity not only at the board level but also across all managerial positions. Policymakers and corporations should implement strategies to foster balanced gender representation throughout management levels to enhance economic performance.

Growing interest in corporate sustainability has prompted firms to rethink governance practices, particularly the role of gender diversity on boards. This study investigates whether the representation of women in executive and non-executive board roles influences Environmental, Social and Governance (ESG) performance across firms in 95 countries between 2018 and 2023. A dynamic panel analysis was conducted using the system Generalized Method of Moments (GMM) estimator, complemented by quantile regressions to assess distributional heterogeneity. The study identifies a non-linear, inverted U-shaped relationship between gender diversity and ESG performance, with optimal thresholds differing based on the type of board role. Female executive directors were found to influence ESG outcomes more directly through decision-making, while non-executive directors contributed through oversight and legitimacy signaling. These results suggest that diversity thresholds must be tailored by function to avoid symbolic appointments and maximize strategic effectiveness. The findings have implications for corporate governance reform, particularly in designing balanced diversity policies across board structures. For regulators and investors, this study offers empirical evidence to support role-specific diversity strategies that enhance sustainability performance without compromising governance efficiency. Recommendations include promoting targeted board reforms and reinforcing disclosure quality to strengthen ESG accountability.

La Analítica del Aprendizaje (proveniente del término en inglés Learning Analytics) procesa los datos de los estudiantes, incluso los estudiantes menores de edad. El ciclo analítico consiste en recoger datos, almacenarlos durante largos períodos y utilizarlos para realizar análisis y visualizaciones. A mayor cantidad de datos, mejores resultados en el análisis. Este análisis puede ser descriptivo, predictivo e, incluso, prescriptivo, lo que implica la gestión, el tratamiento y la utilización de datos personales. El contexto educativo es, por lo tanto, muy sensible, a diferencia de los contextos individuales en los que el análisis se utiliza a voluntad. No está claro cómo están utilizando los datos de los estudiantes las empresas de tecnología que dan servicio en educación y a quiénes realmente se les beneficia, cómo esto afectará a los estudiantes en un futuro a corto y largo plazo, o qué nivel de privacidad o seguridad se aplica para proteger los datos de los estudiantes. Por consiguiente, y en relación con lo expuesto, el análisis de datos educativos implica un contexto sensible y de fragilidad en la gestión y análisis de datos personales de los estudiantes, incluidos menores, en el que hay que maximizar las precauciones. En esta revisión sistemática de la literatura se explora la importancia de la protección y seguridad de los datos personales en el campo de la educación mediante las promesas emergentes de los interesados en usar la tecnología blockchain. Los resultados denotan que es importante entender las implicaciones y riesgos derivados de usar tecnologías emergentes en educación, su relación con la sociedad y la legalidad vigente.

Although STEAM (science, technology, engineering, art, and math) and student-centered instruction are growing rapidly in popularity, their reach is not adequately distributed across diversity groups (including individuals of different genders, economic backgrounds, immigrant backgrounds, abilities, and races, among other characteristics). The CreaSTEAM project intends to address diversity gaps by developing STEAM-Labs, student-centered spaces that combine components of fab labs, media labs, and user labs to specifically target diversity gaps. This paper carried out an informal PRISMA systematic review of a collection of 124 worldwide STEAM diversity initiatives to gather data on existing best practices that will be used in the STEAM-Labs. The review studied the geographic distributions, organizational structures, founding years, and activity offerings of the initiatives, along with the dataset’s overall STEAM content area prevalence and diversity target area prevalence. STEM was the most common approach, and gender was the most common diversity target area. Since 2010 initiative creation has increased, with most growth in gender-focused initiatives.

At the UN Summit in New York 2015 it was agreed that a sustainable development of the planet is essential to strengthen universal peace in a broader capacity. On that basis, a call was made to all nations to achieve this through the 2030 Agenda. The issue is a complex one, as is evident from its 17 Sustainable Development Goals (SDGs) and their interwoven interaction. Engineering plays a leading role in achieving the great majority of the SDGs. For this reason, engineering education should focus its efforts on training engineers to be active agents of sustainability in the world. Our research question is, in fact, how the engineering higher education institutions around the world are deploying the 2030 Agenda. To answer it, we carried out a systematic review of the literature regarding SDGs and engineering schools in the Scopus and Web of Science (WOS) databases. We applied PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) methodology and, as a result, 22 papers were thoroughly studied. The results showed a consensus on the need for collaboration among the different stakeholders to achieve the desired degree profile of responsible engineers. Proposals to ensure this are diverse. They range from changes in curricula and competencies to a variety of teaching–learning strategies. Finally, future lines of research are identified from this study.

Dashboards are useful tools for generating knowledge and support decision-making processes, but the extended use of technologies and the increasingly available data asks for user-friendly tools that allow any user profile to exploit their data. Building tailored dashboards for any potential user profile would involve several resources and long development times, taking into account that dashboards can be framed in very different contexts that should be studied during the design processes to provide practical tools. This situation leads to the necessity of searching for methodologies that could accelerate these processes. The software product line paradigm is one recurrent method that can decrease the time-to-market of products by reusing generic core assets that can be tuned or configured to meet specific requirements. However, although this paradigm can solve issues regarding development times, the configuration of the dashboard is still a complex challenge; users’ goals, datasets, and context must be thoroughly studied to obtain a dashboard that fulfills the users’ necessities and that fosters insight delivery. This paper outlines the benefits and a potential approach to automatically configuring information dashboards by leveraging domain commonalities and code templates. The main goal is to test the functionality of a workflow that can connect external algorithms, such as artificial intelligence algorithms, to infer dashboard features and feed a generator based on the software product line paradigm.

The Covid-19 pandemic led Catalan universities to do all teaching and evaluation online from 11 March 2020 until the end of term on 30 July. Conventional universities made the transition to online teaching in just a few days and suddenly virtual platforms become the centre of interaction between lecturers and students. Data that were obtained from the virtual platforms gave extremely valuable information about what was being done in class. This paper analyses data taken from Atenea, the Moodle virtual platform at the Universitat Politècnica de Catalunya (UPC), during quarantine. The key indicators and a data analysis design for Moodle have been proposed, which reveal teaching developments at various levels (overall and at the centre and subject level). This is applied to study data from the UPC Moodle and the results are discussed. The methodology can be extrapolated to other universities with Moodle platforms because the UPC is a set of small campuses and centres.