Search Results (22)

Generative AI is an emerging tool in higher education; however, its connection with transversal competencies, as well as their sustainable adoption, remains underexplored. The study aims to analyze the scientific and conceptual development of generative artificial intelligence in higher education to identify the most relevant transversal competencies, strategic processes for its sustainable implementation, and global trends in academic production. A systematic literature review (PRISMA) was conducted on the Web of Science, Scopus, and PubMed, analyzing 35 studies for narrative synthesis and 897 publications for bibliometric analysis. The transversal competencies identified were: Academic Integrity, Critical Thinking, Innovation, Ethics, Creativity, Communication, Collaboration, AI Literacy, Responsibility, Digital Literacy, AI Ethics, Autonomous Learning, Self-Regulation, Flexibility, and Leadership. The conceptual framework connotes the interdisciplinary nature and five key processes were identified to achieve the sustainable integration of Generative AI in higher education oriented to the development of transversal competencies: (1) critical and ethical appropriation, (2) institutional management of technological infrastructure, (3) faculty development, (4) curricular transformation, and (5) pedagogical innovation. On bibliometric behavior, scientific articles predominate, with few systematic reviews. China leads in publication volume, and social sciences are the most prominent area. It is concluded that generative artificial intelligence is key to the development of transversal competencies if it is adopted from a critical, ethical, and pedagogically intentional approach. Its implications and future projections in the field of higher education are discussed. Full article

This research examines the impact of digital transformation on teaching practices and evaluates educators’ training requirements within the European Framework for the Digital Competence of Educators (DigCompEdu), focusing specifically on its implementation in the Canary Islands’ educational system. Through a quantitative study involving 546 teachers from primary and secondary institutions during the 2023/2024 academic year (confidence level: 95%, margin of error: 4.15%), we analyzed the relationship between digital competence development and educational innovation. Results indicate significant gaps in four key areas: digital content creation, innovative teaching methodologies, assessment strategies, and feedback mechanisms. The findings reveal a direct correlation between insufficient educational funding and limited professional development opportunities in digital competencies. This study identifies critical areas requiring immediate attention, including increased budgetary allocation for technological infrastructure, systematic professional development programs aligned with DigCompEdu standards, and the restructuring of current innovation approaches in educational institutions. This research contributes to the understanding of how educational systems can effectively adapt to digital transformation while highlighting the crucial role of both financial investment and structured training programs in fostering successful educational innovation, ultimately emphasizing that adapting education systems to digital realities is essential for ensuring future success in an increasingly digitalized educational landscape. Full article

This narrative review synthesizes and analyzes empirical studies on the adoption and acceptance of ChatGPT in higher education, addressing the need to understand the key factors influencing its use by students and educators. Anchored in theoretical frameworks such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Diffusion of Innovation (DoI) Theory, Technology–Organization–Environment (TOE) model, and Theory of Planned Behavior, this review highlights the central constructs shaping adoption behavior. The confirmed factors include hedonic motivation, usability, perceived benefits, system responsiveness, and relative advantage, whereas the effects of social influence, facilitating conditions, privacy, and security vary. Conversely, technology readiness and extrinsic motivation remain unconfirmed as consistent predictors. This study employs a qualitative synthesis of 40 peer-reviewed empirical studies, applying thematic analysis to uncover patterns in the factors driving ChatGPT adoption. The findings reveal that, while the traditional technology adoption models offer valuable insights, a deeper exploration of the contextual and psychological factors is necessary. The study’s implications inform future research directions and institutional strategies for integrating AI to support educational innovation. Full article

Educational institutions are increasingly using audio-based learning resources and technologies nowadays, especially for students who are auditory learners and visually impaired. The ability to design and create online educational talking books with a pedagogical foundation has become essential for students studying instructional and information technology in the age of digital learning. With the need to enhance such skills to target students in higher educational institutions, instructional and information technology students have no specialized platform for designing and producing an online educational talking book without web programming challenges. This study suggests a new specialized, web-based platform that can assist students in developing online educational talking books. In this study, fourteen instructional technology experts evaluated the proposed platform’s usability. An online questionnaire was utilized to gather data, applying qualitative and quantitative methodologies. The results show that the proposed platform is appropriate for creating and developing an online educational talking book for the intended audience of students. Furthermore, the suggested platform’s current version had a workable design that was appropriate for helping students acquire the necessary abilities. Full article

This paper addresses the challenges associated with the centralized storage of educational materials in the context of a fragmented and disparate database. In response to the increasing demands of modern education, efficient and accessible retrieval of materials for educators and students is essential. This paper presents a hybrid model based on the transformer framework and utilizing an API for an existing large language model (LLM)/chatbot. This integration ensures precise responses drawn from a comprehensive educational materials database. The model architecture uses mathematically defined algorithms for precise functions that enable deep text processing through advanced word embedding methods. This approach improves accuracy in natural language processing and ensures both high efficiency and adaptability. Therefore, this paper not only provides a technical solution to a prevalent problem but also highlights the potential for the continued development and integration of emerging technologies in education. The aim is to create a more efficient, transparent, and accessible educational environment. The importance of this research lies in its ability to streamline material access, benefiting the global scientific community and contributing to the continuous advancement of educational technology. Full article

Accreditation bodies call for curriculum development processes that are open to all stakeholders, reflecting viewpoints of students, industry, university faculty, and society. However, communication difficulties between faculty and non-faculty groups leave an immense collaboration potential unexplored. Using the classification of learning objectives, natural language processing, and data visualization, this paper presents a quantitative method that delivers program plan representations that are universal, self-explanatory, and empowering; promoting stronger links between program courses and curriculum development open to all stakeholders. A simple example shows how the method contributes to representative program planning experiences and a case study is used to confirm the method’s accuracy and utility. Full article

Over the past few decades, the education sector has achieved impressive advancements by incorporating Artificial Intelligence (AI) into the educational environment. Nevertheless, specific educational processes, particularly educational counseling, still depend on traditional procedures. The current method of conducting group sessions between counselors and students does not offer personalized assistance or individual attention, which can cause stress to students and make it difficult for them to make informed decisions about their coursework and career path. This paper proposes a counseling solution designed to aid high school seniors in selecting appropriate academic paths at the tertiary level. The system utilizes a predictive model that considers academic history and student preferences to determine students’ likelihood of admission to their chosen university and recommends similar alternative universities to provide more opportunities. We developed the model based on data from 500 graduates from 12 public high schools in Morocco, as well as eligibility criteria from 31 institutions and colleges. The counseling system comprises two modules: a recommendation module that uses popularity-based and content-based recommendations and a prediction module that calculates the likelihood of admission using the Huber Regressor model. This model outperformed 13 other machine learning modules, with a low MSE of 0.0017, RMSE of 0.0422, and the highest R-squared value of 0.9306. Finally, the system is accessible through a user-friendly web interface. Full article

The field of health and medical sciences has witnessed a surge of published research exploring the applications of ChatGPT. However, there remains a dearth of knowledge regarding its specific potential and limitations within the domain of nutrition. Given the increasing prevalence of nutrition-related diseases, there is a critical need to prioritize the promotion of a comprehensive understanding of nutrition. This paper examines the potential utility of ChatGPT as a tool for improving nutrition knowledge. Specifically, it scrutinizes its characteristics in relation to personalized meal planning, dietary advice and guidance, food intake tracking, educational materials, and other commonly found features in nutrition applications. Additionally, it explores the potential of ChatGPT to support each stage of the Nutrition Care Process. Addressing the prevailing question of whether ChatGPT can replace healthcare professionals, this paper elucidates its substantial limitations within the context of nutrition practice and education. These limitations encompass factors such as incorrect responses, coordinated nutrition services, hands-on demonstration, physical examination, verbal and non-verbal cues, emotional and psychological aspects, real-time monitoring and feedback, wearable device integration, and ethical and privacy concerns have been highlighted. In summary, ChatGPT holds promise as a valuable tool for enhancing nutrition knowledge, but further research and development are needed to optimize its capabilities in this domain. Full article

Online learning is quickly becoming a popular choice instead of traditional education. One of its key advantages lies in the flexibility it offers, allowing individuals to tailor their learning experiences to their unique schedules and commitments. Moreover, online learning enhances accessibility to education, breaking down geographical and economical boundaries. In this study, we propose the use of advanced natural language processing techniques to design and implement a recommender that supports e-learning students by tailoring materials and reinforcement activities to students’ needs. When a student posts a query in the course forum, our recommender system provides links to other discussion threads where related questions have been raised and additional activities to reinforce the study of topics that have been challenging. We have developed a content-based recommender that utilizes an algorithm capable of extracting key phrases, terms, and embeddings that describe the concepts in the student query and those present in other conversations and reinforcement activities with high precision. The recommender considers the similarity of the concepts extracted from the query and those covered in the course discussion forum and the exercise database to recommend the most relevant content for the student. Our results indicate that we can recommend both posts and activities with high precision (above 80%) using key phrases to represent the textual content. The primary contributions of this research are three. Firstly, it centers on a remarkably specialized and novel domain; secondly, it introduces an effective recommendation approach exclusively guided by the student’s query. Thirdly, the recommendations not only provide answers to immediate questions, but also encourage further learning through the recommendation of supplementary activities. Full article

Society currently faces two crucial challenges: digital transition and energy transition. Educative innovation plays a key role in this challenging scenario, particularly engineering careers, where laboratory practices are as important as theoretical classes. This paper presents a standardized training platform supported by five European universities which include a remote laboratory experience. Each university is responsible for developing a training module under the guidance provided by the responsible entity (University of Huelva, Spain). For this purpose, the University of Huelva has implemented a remote laboratory based on a supercapacitor power bank. The rest of the universities have selected any other renewable source and have replicated the information and communications technology (ICT) infrastructure. The result is a European network materialized on a homogenized platform where teachers and students can find all the teaching materials (theory and practice) to train and to be trained in renewable energy matters in the new digital era. Full article

This study explored college students’ learning experiences and outcomes as club committee members. Using a linear regression model, it investigated the relevance of personal background variables and club learning experiences to club learning outcomes. This study selected 15 universities and colleges’ student club committee members in TaiwanA total of 1850 questionnaires were distributed, and 1761 valid questionnaires were recovered, with a recovery rate of over 95%. The study findings are as follows: Regarding learning experiences and learning outcomes, the student club committee members was good. According to this study’s linear regression analysis: The personal background of student club committee members and their club learning experience had significant explanatory power on the learning outcomes, with R² values ranging from 39.6% to 61.1% for each dimension. This indicates that learning from club activities can be an essential pathway to cultivating students’ learning outcomes and a valuable reference for promoting club education in colleges and universities in Taiwan. Higher education practitioners should plan activities or programs for student club leaders with learning outcomes in mind, and design learning programs to meet the needs of student club leaders in each school so that students can achieve higher quality learning outcomes. In addition, this study also found that the assessment indicators of learning outcomes of the CAS of the U.S. can be applied to check the learning outcomes of student clubs in higher education in Taiwan. Full article

The massive development of mobile computing and mobile networks attracts developers and researchers to emerge a new direction for augmented reality on the Web. Web augmented reality is inherently considered platform independent, no pre-installation is required, easy to apply, easy to access, and easy to develop. The current study aims to introduce a vision of including Web AR in school instructional material to keep the teaching methods in line with the tremendous technological growth and invest students’ knowledge in this field. The main objective of this study is to develop a QR code-based tracking Web AR application to investigate the effect of Web AR on the achievement of 4th-year primary school pupils in English. The procedure of Web AR application includes two basic steps. Firstly, the convincing Web AR development platform is selected according to three evaluation criteria. Secondly, developing the Web AR with 73 English vocabularies included in the last four units of the Iraqi English pupil’s book. The procedures of the study include; First, a random selection of a sample of pupils and assigning them to experimental and control groups. Second, equalize the elected pupils in the factors that may affect their performance. Then, the control and experimental groups have been taught English for 12 weeks, and finally, three achievement posttests are constructed and applied to the involved groups in order to assess their performance. Having a long period of learning on using Web AR is significant, as the pupils’ tendencies and acceptance of the experiment tools require time and effort. Full article

The choice of technique for the creation of a 3D digital human bone model from natural specimens has a critical impact on the final result and usability of the obtained model. The cornerstone factor in 3D modeling is the number of faces of polygon mesh, along with topological accuracy, as well as resolution and level of detail of the texture map. Three different techniques (3D scanning, photogrammetry, and micro-computed tomography) have been used to create a digital 3D model of the human zygomatic bone. As implementation and use of 3D models can be divided into three main categories—visualization, simulation, and physical replication to obtain a functioning model (implant or prothesis)—the obtained models have been evaluated by the density and topological accuracy of the polygonal mesh, as well as by visual appearance by inspecting the obtained texture map. The obtained data indicate that for biomedical applications and computer biomechanical simulation the most appropriate technique of 3D model obtainment is micro-computed tomography, in its turn for visualization and educational purposes, the photogrammetry technique is a more preferable choice. Full article

Several kinds of research conclude that the level of digital competence of students is mainly oriented to their daily activities. Therefore, we present the current paper which seeks to determine the impact of implementing a blended learning course designed to improve digital competence for research (DCR) among a group of undergraduate engineering students. With this approach, a quasi-experimental explanatory methodology with a causal-comparative scope was applied. For this reason, the results were analyzed before and after applying a specially designed course to the experimental group, comparing it with a passive control group by collecting data using three previously validated instruments. For data analysis, students’ t-tests and two-way ANOVA (Analysis of Variance) were used, estimating the effects with Cohen’s study. Given the results, there was a statistically significant improvement (p ≤ 0.05) in their skills and attitudes, but not in their knowledge, obtaining a significant effect size only in the procedural dimension (f = 0.41 y η² = 0.142). Therefore, the implementation of the course used in the blended learning modality is considered to significantly improve the DCR of a group of undergraduate engineering students, although the results should be evaluated with due reservations. Full article

The aim of the research was to evaluate the performance of smartphone depth sensors (Time of Flight Camera(ToF) and Light Detection and Ranging (LiDAR)) from Android (Huawei P30 Pro) and iOS (iPhone 12 Pro and iPAD 2021 Pro) devices in order to build a 3D point cloud. In particular, the smartphones were tested in several case studies involving the scanning of several objects: 10 building material samples, a statue, an interior room environment and the remains of a Doric column in a major archaeological site. The quality of the point clouds was evaluated through visual analysis and using three eigenfeatures: surface variation, planarity and omnivariance. Based on this approach, some issues with the point clouds generated by smartphones were highlighted, such as surface splitting, loss of planarity and inertial navigation system drift problems. In addition, it can finally be deduced that, in the absence of scanning problems, the accuracies achievable from this type of scanning are ~1–3 cm. Therefore, this research intends to describe a method of quantifying anomalies occurring in smartphone scans and, more generally, to verify the quality of the point cloud obtained with these devices. Full article