Search Results (176)

ICT tools are fundamental for promoting educational inclusion, as they allow for flexible teaching practices adapted to the diversity of students. Their appropriate integration into teaching makes it easier to respond to different paces, styles, and needs, promoting the active and meaningful participation of all learners. However, this inclusive potential is only fulfilled if equitable access to and use of ICT is guaranteed, both at school and at home. This qualitative study explores the digital divide in its three main dimensions: access to technology, digital skills, and the meaningful use of ICT in educational settings. Through focus groups and semi-structured interviews, the study gathers the perceptions of different members of the educational community. The sample consists of 89 participants, including teachers, students, families, and school administrators from the Communities of Madrid and Castilla-La Mancha. The results reveal a common concern about inequalities in ICT access and use, related to economic, geographical, and educational factors. These findings emphasise the need for targeted public policies to bridge digital gaps and highlight the importance of promoting digital competence across the entire educational community to achieve true educational inclusion. Full article

Teacher education plays a key role in promoting inclusion and educational equity, especially in contexts characterised by increasing socio-cultural diversity and technological advancement. In this framework, Universal Design for Learning (UDL) and digital technologies are presented as complementary and innovative strategies to create accessible, flexible, and motivating learning environments for all students. The study analysed the impact of UDL-focused learning activities and integrated Information and Communication Technologies (ICT). A comparative tool was applied before and after the intervention to measure the level of knowledge, perception, and digital competence of prospective teachers. Statistical analyses were carried out to evaluate the changes obtained. Findings reveal significant improvements in knowledge about UDL, as well as positive perceptions of ICT as a resource for inclusion. Participants demonstrated a greater understanding of UDL principles and strengthened their digital competences to design educational proposals adapted to diversity. The research confirms the value of integrating UDL and ICT in teacher training, fostering inclusive educational practices. It highlights the need to strengthen training programmes that respond to the current challenges of the education system. Full article

The implementation of new curricula presents significant challenges for teachers and necessitates the adaptation of their professional competencies. This study examines how the digital skills of Swiss teachers differ during and after the implementation of the Media and Information Literacy (MIL) modular curriculum. To achieve this, two independent samples totaling 617 teachers were surveyed at different stages of the reform. The analysis employed a multivariate analysis of variance (MANOVA) to identify differences in the four facets of MIL competence between the samples. The results indicate that MIL competencies did not improve uniformly. While no significant differences were found in the facets of ‘ICT knowledge and application’ and ‘media education knowledge and application’, significant differences were observed in the facets of ‘specialized didactics MIL’ and ‘interdisciplinary pedagogical and didactic knowledge’. The latter facet showed higher values after the reform, likely due to increased exposure to further training measures. These findings illustrate that teachers’ competencies can develop differently throughout a reform process, highlighting the importance of targeted professional development programs. The study provides valuable empirical findings for educational research and offers practical implications for the design of future reform processes. Full article

This paper explores the concept of evolutionary urban resilience by framing cities as complex, open, and adaptive Social-Ecological-Technological Systems (SETS), shaped by multi-scalar dynamics, systemic uncertainty, and interdependent crises. It challenges the reductionist view of resilience as a fixed capacity or linear sequence of risk management phases, and instead proposes a process-based paradigm rooted in learning, creativity, and the ability to navigate disequilibrium. The framework defines urban resilience as a continuous and iterative transformation process, supported by: (i) a combination of tangible and intangible qualities activated according to problem typology; (ii) cross-domain processes involving infrastructures, flows, governance, networks, and community dynamics; and (iii) the engagement of diverse agents in shared decision-making and coordinated action. These dimensions unfold across three incremental and interdependent scenarios—baseline, critical, and chronic crisis—forming a ladder of resilience that guides communities through escalating challenges. Special emphasis is placed on the role of Information and Communication Technologies (ICTs) as relational and adaptive tools enabling distributed intelligence and inclusive governance. The framework also outlines concrete operational and policy implications for cities aiming to build anticipatory and transformative resilience capacities. Applied to the case of Taranto, the approach offers insights into how structurally fragile communities facing conflicting adaptive trajectories can unlock transformative potential. Ultimately, the paper calls for a shift from government to governance, from control to co-creation, and from reactive adaptation to chaos generativity, recasting urban resilience as an evolving project of collective agency, systemic reconfiguration, and co-production of emergent urban futures. Full article

The empowerment of rural women through sustainable entrepreneurship is pivotal for fostering economic development and social transformation in developing communities. This study examines the impact of university social responsibility (USR) programs on strengthening sustainable entrepreneurship among rural women, emphasizing the mediating role of economic empowerment. Utilizing a structural equation model (SEM), we explore causal pathways between USR interventions, entrepreneurial capacities, and the sustainability of rural businesses. Key dimensions analyzed include economic resources, social networks, and psychological self-efficacy, as well as their interrelation with community development. The findings demonstrate that multidimensional USR programs integrating technical training, social support, and economic resources significantly enhance entrepreneurial resilience and value chain integration. Notably, the analysis reveals that economic empowerment mediates the relationship between USR programs and business sustainability, with improvements in community participation and ICT quality identified as critical drivers. Furthermore, the post-intervention results highlight a shift from technology access challenges to a focus on ICT content quality and psychosocial development, reflecting maturity in community adaptation and resource utilization. This research provides empirical evidence supporting the effectiveness of USR programs in catalyzing sustainable transformations in rural contexts. The results offer actionable insights for designing targeted interventions that integrate technical, social, and economic dimensions, contributing to the advancement of sustainable entrepreneurship and rural development theory. Full article

This study validates a Spanish-language instrument designed to assess self-efficacy, digital competence, and anxiety in data-driven decision-making (DDDM) among pre-service teachers. Based on the 3D-MEA and the Beliefs about Basic ICT Competencies scale, the instrument was culturally adapted for Chile and Spain. A sample of 512 participants underwent exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Given the ordinal nature of the data and the assumption of non-normality, appropriate estimation methods were utilized. Results supported a well-defined four-factor structure: Interpretation and Application, Technology, Identification, and Anxiety. Factor loadings ranged from 0.678 to 0.869, and internal consistency was strong (α = 0.802–0.888). The CFA confirmed good model fit (χ² (129) = 189.25, p < 0.001; CFI = 0.985; TLI = 0.981; RMSEA = 0.041; SRMR = 0.061). Measurement invariance was established across gender and nationality, reinforcing the validity of cross-group comparisons. The study is framed within an educational context aligned with socioformative principles and sustainable education goals, which support reflective and ethical data use. This validated tool addresses the lack of culturally adapted and psychometrically validated instruments for assessing DDDM competencies in Spanish-speaking contexts, offering a culturally and linguistically relevant instrument with strong internal consistency and a well-supported factor structure. It supports the design of formative strategies in teacher education, enabling the identification of training needs and promoting evidence-based pedagogical decision-making in diverse Hispanic contexts. Future studies should test factorial invariance across additional contexts and explore longitudinal applications. Full article

Traditional single neural network-based geo-localization methods for cross-view imagery primarily rely on polar coordinate transformations while suffering from limited global correlation modeling capabilities. To address these fundamental challenges of weak feature correlation and poor scene adaptation, we present a novel framework termed ICT-Net (Integrated CNN-Transformer Network) that synergistically combines convolutional neural networks with Transformer architectures. Our approach harnesses the complementary strengths of CNNs in capturing local geometric details and Transformers in establishing long-range dependencies, enabling comprehensive joint perception of both local and global visual patterns. Furthermore, capitalizing on the Transformer’s flexible input processing mechanism, we develop an attention-guided non-uniform cropping strategy that dynamically eliminates redundant image patches with minimal impact on localization accuracy, thereby achieving enhanced computational efficiency. To facilitate practical deployment, we propose a deep embedding clustering algorithm optimized for rapid parsing of geo-localization information. Extensive experiments demonstrate that ICT-Net establishes new state-of-the-art localization accuracy on the CVUSA benchmark, achieving a top-1 recall rate improvement of 8.6% over previous methods. Additional validation on a challenging real-world dataset collected at Beihang University (BUAA) further confirms the framework’s effectiveness and practical applicability in complex urban environments, particularly showing 23% higher robustness to vegetation variations. Full article

In recent years, studies analyzing how information and communication technologies (ICTs) contribute to the development of students with special educational needs (SENs) have gained interest. The proliferation of studies in this field has driven the creation of numerous digital resources that can be applied in science teaching. Therefore, this study aims to conduct a systematic review of the literature on the usefulness of ICT in teaching Natural Sciences in Primary Education to address diversity. The methodology used for this systematic review and meta-analysis followed PRISMA guidelines, drawing data from the Scopus and Web of Science databases. A total of three documents were analyzed. The results indicated a favorable effect for the experimental groups (I² = 84; p = 0.002). These findings show that the use of ICT enhances participation and motivation among Primary School students with SENs in Natural Sciences. In conclusion, ICT positively influences learning in Natural Sciences by increasing motivation among Primary School students with SENs. This meta-analysis highlights the importance and positive impact of ICT on Natural Sciences learning in Primary Education, especially in support of student diversity. The reviewed evidence confirms that personalizing learning through adaptive systems, using methodologies based on individual learning styles, and employing innovative technologies significantly enhance academic performance, motivation, and student engagement. The effective use of ICTs for inclusion in primary school science relies on the design of instructional methods that link technology, emotions, and diversity. Full article

Decision-making is a fundamental challenge in science and engineering, mainly when subjective factors influence the process. This paper introduces a decision support model based on the Analytic Hierarchy Process (AHP) that was specifically adapted for binary decisions and we term Binary AHP. The model facilitates structured decision-making when evaluating two opposing alternatives, such as yes/no scenarios. To demonstrate its applicability, we applied the Binary AHP model to a real-world case in the Brazilian public sector, where agencies must determine whether a technological solution qualifies as an Information and Communication Technology (ICT) solution. This classification is crucial since it directly impacts procurement policies and regulatory compliance. Our results show that Binary AHP enhanced the decision consistency, transparency, and reproducibility, and reduced the subjective discrepancies between the evaluators. Additionally, by inverting the priority vectors, the model allowed for a comparative analysis of both decision alternatives, thus offering more profound insights into the classification process. This study highlights the flexibility of AHP-based decision support methodologies and proposes a structured approach to refining binary decision frameworks in complex, multi-criteria environments. Full article

(1) Background: The objective of this study was to verify a model proposed adapted to the case of teachers working in the field of early childhood education of children with functional diversity. The model analyses the relationship between the perceptions, use, and necessity of Information and Communication Technologies (ICTs) and the level of ICT training. (2) Methods: Snowball sampling was used to acquire a random sample of 254 in-service teachers working in early childhood education centers including children with functional diversity in Andalusia (Spain). A partial least squares–structural equation model was developed. (3) Results: A positive relationship between teachers’ perceptions of ICTs and their use was found, corroborating the findings of previous studies on pre-service teachers working with students with functional diversity. However, unlike previous studies, no significant relationship was found between ICT use and needs and the level of ICT training. The novelty of this study is that the participants are in-service teachers, the education context is early childhood, and the model includes age as a control variable, which had a negative impact in this case in Spain. (4) Conclusions: The importance of improving teacher training to optimize the use of ICTs is emphasized. The professionals interviewed highlighted the need for early assessments and increased material and human resources in public educational institutions. The urgency of administrative restructuring to expedite the delivery of financial aid and the recruitment of more specialized professionals is underscored. Full article

This study tested whether Information and Communication Technology (ICT) proficiency moderates the relationship between climate anxiety and specific expectations of future extreme weather events. Using survey data from 259 university students in Croatia and Bosnia and Herzegovina, we applied moderation analysis (Hayes PROCESS Model 1) and find a significant moderation (Int = 0.108, p = 0.030; ΔR² = 1.8%). A Johnson–Neyman procedure indicated that climate anxiety reliably predicts risk expectations once ICTSkill is ≥3.99 (≈76.8% of the sample). By embedding ICT proficiency as a domain-specific perceived behavioural control construct, our results suggest that targeted digital literacy training can serve as a sustainability education tool, converting climate concern into informed preparedness. Full article

Background: Activities of Daily Living (ADLs) are essential tasks performed at home and used in healthcare to monitor sedentary behavior, track rehabilitation therapy, and monitor chronic obstructive pulmonary disease. The Barthel Index, used by healthcare professionals, has limitations due to its subjectivity. Human activity recognition (HAR) is a more accurate method using Information and Communication Technologies (ICTs) to assess ADLs more accurately. This work aims to create a singular, adaptable, and heterogeneous ADL dataset that integrates information from various sources, ensuring a rich representation of different individuals and environments. Methods: A literature review was conducted in Scopus, the University of California Irvine (UCI) Machine Learning Repository, Google Dataset Search, and the University of Cauca Repository to obtain datasets related to ADLs. Inclusion criteria were defined, and a list of dataset characteristics was made to integrate multiple datasets. Twenty-nine datasets were identified, including data from various accelerometers, gyroscopes, inclinometers, and heart rate monitors. These datasets were classified and analyzed from the review. Tasks such as dataset selection, categorization, analysis, cleaning, normalization, and data integration were performed. Results: The resulting unified dataset contained 238,990 samples, 56 activities, and 52 columns. The integrated dataset features a wealth of information from diverse individuals and environments, improving its adaptability for various applications. Conclusions: In particular, it can be used in various data science projects related to ADL and HAR, and due to the integration of diverse data sources, it is potentially useful in addressing bias in and improving the generalizability of machine learning models. Full article

Background: After the end of the COVID-19 pandemic, abusive use of the internet and new information and communication technologies (ICT) among university students was detected. Our research questions were as follows: what has been the impact on the academic performance of university students, and how did the pandemic affect students’ relationship with ICTs? The aim of this research was to explore the use of cell phones and the internet in students from different cultures (Spanish and Japanese) after the pandemic. Methods: This descriptive and exploratory study analysed 206 university students from Spanish and Japanese cultures to understand their perceptions of academic performance after the pandemic, their general use of ICT, and their abusive use of the internet and mobile phones. Instruments included the Internet Overuse Scale (IOS) and the Cell-Phone Overuse Scale (COS), adapted for both Spanish and Japanese populations. Differences between quantitative variables were analyzed using the non-parametric Mann–Whitney U test for independent samples (Spanish and Japanese students or by sex). Contingency tables were created to record and analyse relationships between qualitative variables using the chi-squared test, with statistical significance set at p < 0.05. Results: Approximately 29.6% of participants displayed excessive internet use, while 25.2% showed pathological mobile phone use. A strong association was found between high internet and mobile phone usage. Significant cultural and gender differences were observed, with higher problematic use among Japanese students and female participants. Conclusions: Excessive ICT use remains a concern in university settings, with gender and cultural factors playing key roles. These findings highlight the need for targeted digital well-being interventions. Full article

Small and medium-sized enterprises (SMEs) face unique challenges that can be effectively addressed through the adoption of data mining and business intelligence (BI) tools. This systematic literature review scrutinizes the deployment and efficacy of BI and data mining technologies across SME sectors, assessing their impact on operational efficiency, strategic decision-making, and market competitiveness. Therefore, drawing from a methodologically rigorous analysis of 93 scholarly articles published between 2014 and 2024, the review elucidates the evolving landscape of BI tools and techniques that have shaped SME practices. It reveals that advanced analytics such as predictive modeling and machine learning are increasingly being adopted, though significant gaps remain, particularly shaped by economic factors. The utilization of BI and data mining enhances decision-making processes and enables SMEs to adapt effectively to market dynamics. Despite these advancements, SMEs encounter barriers such as technological complexity, high implementation costs, and substantial skills gaps, impeding effective utilization. Our review, grounded in the analysis of business intelligence tools used indicates that dashboards (31.18%) and clustering techniques (10.75%) are predominantly utilized, highlighting their strategic importance in operational settings. However, a considerable number of studies (66.67%) do not specify the BI tools or data mining techniques employed, pointing to a need for more detailed methodological transparency in future research. The predominant focus on the ICT and manufacturing sectors underscores the industrial context sector specific applicability of these technologies, with ICT accounting for 45.16% and manufacturing 22.58% of the studies. We advocate for targeted educational programs, development of user-friendly and cost-effective BI solutions, and strategic partnerships to facilitate knowledge transfer and technological empowerment in SMEs. Empirical research validating the impacts of BI and data mining on SME performance is crucial, providing a directional pathway for future academic inquiries and policy formulation. Full article

Video games, as interactive artifacts within the continuum of information and communication technology (ICT), encapsulate an ontological inquiry: which mechanism maintains user engagement while evolving with ICT-driven innovations? How is this mechanism structured within video games in the competitive industry? This study analyzes the emergent narrative of the Animal Crossing franchise, focusing on the interplay between persistence and evolution, aligning with our inquiry by examining how technological integration, interactive design, and player agency co-construct narrative adaptations across generations. Employing an integrated approach, we introduced the ENSF framework to analyze emergent narrative mechanisms. On this basis, the qualitative walkthrough method and quantitative unsupervised learning methods—principal component analysis and VADER techniques—were used to examine narrative flow, linguistic metrics, and sentiment tendencies across four game generations and official materials (N = 37). This study contributes to (a) establishing the structural emergent narrative simulation framework (ENSF) delineating the narrative techniques’ interrelations—simulation, orientations, story events, resolutions, evaluations, and characters; and (b) interpreting how narrative mechanisms within interactive design balance persistence with evolution, proving that ICT innovations comply with player agency reinforcement. These discoveries establish a hermeneutic proposal identifying the socio-technological characteristics of interactive communications in video game design, emphasizing the dynamic balance within innovative gaming environments. Full article