Seminars in Medical Writing and Education
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University education 5.0: artificial intelligence and emerging technologies for innovation in higher education
Full text linkArtificial Intelligence (AI) has become a key driver in the transformation of higher education, introducing new approaches to teaching, learning, and academic management. This study analysed its impact on university teaching through a multinational comparative approach involving Ecuador, Peru, and Colombia, with the aim of identifying benefits, challenges, and opportunities from the perspectives of both lecturers and students. A mixed-methods design was employed, combining a systematic review of 15 articles published between 2019 and 2024 with a structured survey administered to 450 participants (150 in each country). Quantitative data analysis was conducted to measure perceptions and trends, while the documentary review provided further contrast and enrichment of the findings. Results revealed that AI is perceived as a positive driver of educational innovation, particularly in personalised learning, the use of virtual assistants for feedback, and the optimisation of teaching time. However, concerns persist regarding algorithmic bias, transparency in automated assessment, and inequity in access to technological infrastructure. Moreover, Ecuador exhibited the highest levels of acceptance, while Peru and Colombia displayed more neutral attitudes, reflecting contextual barriers to its implementation. In conclusion, AI holds significant potential to transform higher education in the Andean region, provided its incorporation is supported by robust ethical frameworks, inclusive institutional policies, and continuous teacher training programmes that ensure sustainable adoption
Transforming the classroom into Higher Education: The Synergy between Design Thinking, the TPACK Model, and Open Educational Resources
Full text linkThis study proposed the transformation of higher education teaching through the synergy of Open Educational Resources (OER), the TPACK model, and the Design Thinking methodology. It focused on the learning of stereochemistry and isomerism of biomolecules within the Biology degree program at the Facultad de Ciencias, UNAM, under a new curriculum based on Kolb’s experiential learning model. During the COVID-19 pandemic, the need for flexible, ICT-supported methodologies became evident. In this context, OER served as key tools to democratize knowledge and promote autonomous and collaborative learning. The TPACK model enabled the integration of content, pedagogy, and technology, while Design Thinking provided a student-centered structure for solving complex problems through empathy, creativity, and experimentation. The methodological strategy was structured around six instructional actions; each linked to expected outcomes. Students followed an experiential learning process divided into four stages, in which specific actions, resources, and prototyping activities were defined. The approach included the manipulation of three-dimensional molecular models to encourage interdisciplinary, hands-on learning under the Design Thinking framework. This strategy enhanced students\u27 conceptual understanding and ability to apply knowledge in real-life contexts through active experimentation. The proposal emphasized the need for continuous teacher training and institutional support to ensure the successful adoption of these innovative practices in higher education
Current trends in educational sciences: contemporary implications and social relevance
Full text linkThe Science of Education has its origins in the 19th century and has transformed and evolved in response to cultural, social, technological and economic changes throughout history. In an increasingly globalised world, understanding current trends in this field is vital for training professionals who are not only competent in their area, but also capable of adapting to a constantly changing landscape. Qualitative research was conducted to analyse current trends in Education Sciences, their contemporary implications and social relevance. Empirical (documentary analysis) and theoretical (analytical-synthetic, inductive-deductive, historical-logical analysis, systems approach) methods were used to carry out the research. Twenty-six bibliographies were used. Current trends in Education Sciences reflect a need for adaptation and evolution in a changing world. From competency-based learning and projects to inclusive education, educational technology and socio-emotional health, each trend offers opportunities and challenges that must be addressed to ensure quality education
Dimensionality and internal consistency of the Roberts’ scale for suicidal ideation among Colombian pregnant women
Full text linkIntroduction: Suicidal ideation is an understudied issue during the gestational period, requiring valid and reliable instruments for timely measurement and to provide support in perinatal mental health. However, there are limited scales available to assess suicidal ideation in pregnant women in Colombia.Objective: To explore the dimensionality and internal consistency of the Roberts’ scale for suicidal ideation in pregnant women from Santa Marta, Colombia.Methods: 172 pregnant women between 18 and 44 years of age (M=24.7; SD=5.49) completed the Roberts suicidal ideation scale. An exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were carried out to determine dimensionality and Cronbach\u27s alpha and McDonald\u27s omega coefficients were calculated to establish internal consistency.Results: In the CFA the Roberts’ scale indicated a unidimensional internal structure explaining 50.5% of the variance and with adequate goodness-of-fit indicators (X2=5.85, gl=2, p<0.054; RMSEA=0.104 (CI90%=0.000-0.210); SRMR=0.025; CFI=0.981; TLI=0.944). Cronbach\u27s alpha coefficient was 0.781 and McDonald\u27s omega coefficient was 0.801, showing acceptable internal consistency.Conclusions: Roberts’ scale is a brief, reliable measure with strong validity evidence for assessing suicidal ideation in pregnant women. Further instrumental studies with a larger sample size are recommended to corroborate the psychometric performance of the instrument in the Colombian population
Virtual higher education in Bolivia: Towards a comprehensive organizational, technological, and pedagogical model.
Full text linkIntroduction: Virtual education has taken on a central role in higher education, allowing to overcome geographical barriers and improve access to knowledge. In Bolivia, the transition to this modality faces challenges related to technological infrastructure, teacher training, and institutional regulation.Objective: The purpose of this research is to propose a comprehensive model for virtual higher education in Bolivia, ensuring an efficient implementation that optimizes teaching and learning processes.Method: The study employs a qualitative approach based on document analysis and systematic literature review. The PRISMA method is used to select relevant research in recognized databases such as Scopus, SciELO, and Web of Science. Inclusion and exclusion criteria were established to ensure the relevance of the analyzed studies.Results: The study findings indicate that virtual education promotes access and flexibility in learning, but its success depends on factors such as teacher training, technological infrastructure, and the quality of the organizational models adopted. Hybrid and fully online approaches were identified, highlighting the importance of interaction among teachers, students, and administrators. Technological tools such as LMS platforms, video conferencing, gamification, and multimedia resources were analyzed, enhancing the learning experience.Conclusion: Virtual education in Bolivia has the potential to transform higher education, but its consolidation requires clear policies, investment in technology, and continuous teacher training. A comprehensive model should include quality standards, innovative learning strategies, and effective regulation to ensure accessibility and equity in virtual education
AI in Education: A Systematic Literature Review of Emerging Trends, Benefits, and Challenges
Full text linkIntroduction: artificial intelligence (AI) is reshaping education by enabling personalized learning, improving instructional practices, and automating academic and administrative tasks. Despite its accelerating adoption, evidence on AI’s effectiveness, challenges, and broader implications remains fragmented across technologies, contexts, and outcomes.
Method: this study conducted a systematic literature review of peer-reviewed publications from January 2020 to August 2024, following PRISMA 2020 guidelines. Searches across Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, ERIC, and the first 100 Google Scholar results were screened, appraised, and synthesized thematically. Thirty-nine studies meeting the inclusion criteria were analyzed.
Results: the synthesis revealed emerging trends in AI applications spanning special education, K–12 schooling, higher education, vocational training, and language learning. Reported benefits included personalized learning pathways, improved pedagogy and assessment, enhanced feedback mechanisms, reduced administrative workload, and increasing emphasis on AI literacy for both educators and students. Persistent challenges involved infrastructural limitations, inadequate teacher training, algorithmic bias, ethical and data-privacy concerns, and inequities in access. Notable research gaps included a shortage of classroom-based empirical evidence, limited ethical frameworks, underrepresentation of marginalized populations, and insufficient strategies for AI literacy development.
Conclusions: AI holds transformative potential to enrich teaching, learning, and educational equity. Realizing this promise requires targeted investments in infrastructure and teacher professional development, integration of AI literacy into curricula, and the establishment of robust ethical and governance frameworks. Expanding empirical research—particularly in underrepresented contexts—will be critical to ensuring AI’s responsible and inclusive integration into education
A Call to Action: International Classification for Nursing Practice Integration for Undergraduate Nursing Education in the UAE – A Narrative Review
Full text linkIntroduction: The United Arab Emirates (UAE) is experiencing rapid changes in healthcare and education, yet undergraduate nursing education faces challenges in addressing the theory-practice gap and adopting standardized terminologies. The international classification for nursing practice (ICNP) offers a framework to enhance nursing education, but its integration remains underexplored. Development: This review evaluates the potential of ICNP, combined with the systematized nomenclature of medicine – clinical terms (SNOMED CT), to improve patient care, interprofessional collaboration, and healthcare system efficiency. It proposes a phased curriculum integration plan, identifies stakeholder roles, and addresses global adoption challenges. The review highlights benefits for career preparedness, health informatics, and data interoperability. Conclusion: Integrating ICNP into UAE nursing education can bridge the theory-practice gap, enhance global competitiveness, and align with national health priorities. A structured implementation plan ensures sustainability, positioning UAE nursing education as a leader in health informatics
Medical Images Noise Removal using Improved Adversarial Generative Network
Full text linkIntroduction; The protection of patient privacy through medical image de-identification stands as a vital yet complicated healthcare challenge which demands both accurate diagnosis and privacy protection. Deep learning techniques now provide superior methods to enhance medical images which suffer from acquisition noise and low-resolution degradation. The research develops a Generative Adversarial Network (GAN) architecture to create a deep-learning solution which enhances medical images while removing identifying information.Objective; The proposed method uses adversarial learning to eliminate noise while restoring detailed high-resolution content from low-quality medical images.Method; The research team analysed medical images through data analysis of their dataset. The GAN model received training and validation through experiments that compared its performance against established demo denoising and super-resolution techniques to assess its overall performance. The fundamental technology shows promise for future medical applications because it can enhance image quality to diagnose and treat multiple diseases. Medical image analysis requires images with diverse detailed features for proper evaluation.Results; The proposed model demonstrates successful background noise reduction and improved image clarity with preserved diagnostic elements according to the obtained results. The proposed method achieved better results in PSNR and SSIM metrics than baseline models which proved its ability to restore vital diagnostic details.
Conclusion; The research introduces an innovative GAN-based system which delivers superior medical image quality while maintaining patient information confidentiality during de-identification processes. The method shows promise to create efficient and economical diagnostic processes through its ability to analyze poor-quality medical images
AI and education: combination to enhance knowledge
Full text linkArtificial intelligence (AI) has revolutionized numerous fields, education is one of the most benefited. Technologies like Chat GPT have marked a before and after in the evolution of AI, providing tools to automate repetitive tasks, allowing educators to dedicate more time to students. In addition to optimizing time and resource management, AI personalizes education through advanced algorithms and data analysis, adapting resources and methodologies to the individual needs of each student. This facilitates learning, promotes inclusion and offers more effective education, especially for people with disabilities or diverse learning styles. In this article, a bibliometric review was carried out on the relationship between AI and education. The essential requirements of the search were scientific texts published in the last five years (2020-2024) and to be found in the Scopus and Web of Science databases, fundamentally. AI opens new perspectives in educational research, allows more detailed analysis on large volumes of data and can identify previously undetected areas of improvemen
Pedagogical conceptions about teaching academic writing in postgraduate studies: a literature review
Full text linkIntroductionPostgraduate academic writing instruction remains a field of pedagogical tension, especially between normative approaches and critical, inclusive models. This integrative review aimed to analyze current pedagogical conceptions and teaching strategies for academic writing in postgraduate education, with emphasis on critical and sociocultural approaches.MethodsAn integrative literature review was conducted following a systematic protocol. Academic databases were searched using keywords in English and Spanish. A total of 812 records were identified. After applying inclusion and exclusion criteria, 28 peer-reviewed articles published between 2021 and 2025 were selected for in-depth analysis.ResultsFindings revealed two dominant pedagogical conceptions: traditional models focused on textual correction and standardized formats, and critical approaches that view writing as a situated, dialogic, and epistemically just practice. In addition, technical and sociocultural teaching approaches were identified, often coexisting in postgraduate programs. Persistent tensions were found between formal normativity and creative, critical expression, especially in contexts with high epistemic diversity.ConclusionsThe review confirmed the need to shift from prescriptive teaching models to more reflective and inclusive practices that support students\u27 epistemic agency. It emphasized the importance of institutional support, teacher training in critical pedagogies, and evaluation systems that recognize process-oriented and context-sensitive academic writing