2025-07-01
Salvador Gutiérrez Molero, Hugo Heredia Ponce, Manuel Francisco Romero Oliva
The constant technological transformations have given rise to the so-called Digital Society, which is increasingly developing in virtual spaces. In this context, the Alpha generation corresponds as the most exposed and familiarised with digital devices from a great diversity towards their mastery and conception. The aim of this study is to analyse the level of knowledge, skills, attitudes and emotions that 5 th and 6 th grade primary school students have towards the use of technology. For this purpose, a quantitative approach has been carried out, with a non-experimental, cross-sectional and exploratory design, with a sample of 274 students from five schools in the province of Cadiz. The Bastarrachea et al. (2023) questionnaire was used to collect the data. The results show that mothers act as advisors on how their children should use technology. Furthermore, although the young people have acceptable skills, they do not have good technological knowledge.
2025-07-01
Oskar Almazán-López, Helen Hasbún, Sara Osuna-Acedo
This study explores teachers' attitudes and perceptions regarding their (post)digital identity in relation to Generative Artificial Intelligence (GenAI) and Smart Technologies (ST). A non-experimental design with a mixed approach was used, including a questionnaire, focus groups and an in-depth interview. The sample consisted of 177 teachers, mainly from Spain and the United States and included all educational levels. The results show a high degree of reliability of the instrument used (α = 0.847) and a significant (p < 0.01) strong positive correlation (r = 0.525) between the level of knowledge and experience with ST and teachers' attitudes and perceptions towards these tools. Although teachers hold a mostly positive attitude towards these technologies, more than 50% consider their knowledge and experience to be limited. Teachers' perceptions oscillate between caution and optimism regarding ST´s practical impact, emphasizing the need for individual, social and methodological changes to facilitate effective educational innovation. The analysis suggests that media education is key to overcoming barriers that hinder the adoption of these tools. The research concludes that, for teachers to embrace their postdigital identity, it is essential to reflect on how to integrate these technologies in a critical, inclusive, and ethical manner, thereby strengthening their role in fostering a more just society and adapting to new technological paradigms.
2025-07-01
Francisco Marcos Martín-Martín, Ignacio Aguaded Gómez
This paper presents a systematic review of research exploring the utilisation of artificial intelligence (AI) in the context of education and communication for older adults. In accordance with the PRISMA 2020 protocol, a total of 15 studies were selected from the WoS, Scopus, EBSCO, ERIC and Dialnet Plus databases, published between 2015 and 2024, for analysis. The findings indicate a paucity of scientific output in the field of educommunication pertaining to AI and older people, underscoring the necessity for an expansion of research in this domain. Potential avenues for future inquiry include the design of adaptive AI applications, the development of targeted media literacy programmes, and the creation of conversational agents to enhance the efficacy of educational intervention strategies with older people. However, the persistence of the digital divide and ageism impede the effective integration of AI.
2025-07-01
Beatriz Peña-Acuña, Rosario Herrada-Valverde, Gabriel Herrada-Valverde, Agnieszka Andrychowicz-Trojanowska
The key learning-to-learn competence involves a deeper level of personal learning than simple skills development. With the aim of analysing the development of the competence’s cognitive dimension in the university context, this research presents a digital storytelling intervention undertaken with students from two Spanish universities. Using the Evaluation of Learning to Learn Competence in University Students (CECAPEU) Questionnaire and the data collected from 237 students via a Google Forms questionnaire, a quasi-experimental study with inferential tests was carried out. The results show that most students are distributed between the medium and high competence levels, and that students with good academic performance have better cognitive competence, which is more dependent on subject performance than on their score in the Evaluation Test for University Entrance (PEvAU) or Vocational Training (FP). It is therefore concluded that academic performance in the subject through elaborated interventions is crucial for developing cognitive skills associated with the key learning-to-learn competency.
2025-07-01
Jeanette Chaljub-Hasbún, Julio Cabero Almenara, Pamela Michel-Acosta, Rafael Bello, Josefina Pepín
Virtual reality is part of the set of haptic technologies that allow the user to interact with an artificial scenario, different from the real world but very similar to it. Within the field of education, it promotes active and dynamic learning with immersive experiences. The goal of this study was to assess the usability of an object in VR format for oscilloscope instruction. We created a virtual physics lab environment in version 1.0. The methodology has a quantitative, descriptive approach. Brooke (1996) designed the System Usability Scale (SUS), which collected data from experts in both technology and physics, totaling 42 participants. We obtained Cronbach's alpha and McDonald’s omega indexes with values of 0.924 and 0.901, respectively. The results reveal that the virtual reality (VR) resource received an assessment of 72.58, corresponding to a percentile between 65 and 69, across 500 previous studies by various authors on the SUS. This indicates that the created object has a good acceptance range, being valued as very good and suitable for use in teaching.
2025-07-01
Alberto Urueña López
In an era of rapid technological advancement, the ability to innovate effectively is a critical competency. Patentes para Tod@s (Patents for All) project, supported by the European Engineering Learning Innovation and Science Alliance (EELISA), redefines innovation by emphasizing the potential of expired patents as a foundation for social progress. Implemented within the Concepts and Legal Aspects of Innovation course at Universidad Politécnica de Madrid, this initiative engages national and international students in repurposing existing inventions to address societal challenges. Rooted in Challenge-Based Learning (CBL), the project bridges theoretical knowledge with hands-on application, equipping students with essential skills in intellectual property management, interdisciplinary collaboration, and problem-solving. Through structured teamwork and expert-led training, students analyze and modify expired patents, fostering an iterative approach to innovation. A comprehensive assessment framework —including student evaluations, expert interviews, and the Context, Input, Process, Product (CIPP model)— demonstrates the project's impact on enhancing creativity, professional competencies, and social responsibility. Findings suggest that working with expired patents cultivates a deeper understanding of technological adaptation and sustainability, reinforcing the important role of higher education in fostering real-world innovation. Future iterations will refine training methodologies and collaborative structures to further maximize educational and societal benefits.
2025-07-01
Mohammad Omar AL-Momani, Elham Mahmoud Rababa
The study aimed to identify the degree of employment of artificial intelligence techniques in the educational process from the point of view of Jordanian university students and its relationship to the variables of gender and academic degree. The descriptive analytical approach was used, and the study sample consisted of (10,000) male and female students from various Jordanian universities. The study results concluded that the use of artificial intelligence techniques in universities was moderate, and the results indicated no statistically significant differences at the significance level (α<0.05) in the degree of use of artificial intelligence techniques due to the gender variable. The study found statistically significant differences due to the academic degree variable favoring undergraduate and postgraduate students.