Mauricio Echiburu, José L. Marcos, René Ríos
et al.
In 1949, Captain Alberto Larraguibel and his horse Huaso set the world record for equestrian high jump in Viña del Mar, Chile, by clearing a height of 2.47 meters, a mark that remains unbeaten. This work proposes the use of this historical event as a teaching resource for physics, integrating perspectives from biomechanics and veterinary medicine. Based on the analysis of an audiovisual record of the jump, a kinematic model is developed using the \textit{Tracker} software, determining variables such as displacement, velocity, and acceleration of the horse--rider system. The results make it possible to reflect on the biomechanical and physiological factors involved in animal performance, thus linking physics with real biological processes. It is proposed that this interdisciplinary approach, based on authentic cultural and scientific contexts, may promote meaningful learning, motivation, and a more comprehensive understanding of natural phenomena in science education.
Gifty Budu, Edward Owusu , Levina N. Abunya
et al.
This study examines selected undergraduate students’ learning styles and preferences at a public university in Ghana. These participants were Level 100 students pursuing the Bachelor of Information Technology programme. The study sought to answer three research questions: What are the students’ learning styles? What are the students’ preferred learning styles? What characteristics do students demonstrate to establish their learning styles? Thirty participants (30) were purposefully sampled from the Faculty of Computing and Information Systems of a public university in Accra, Ghana. In this study, the research instruments used for the data collection were Fleming’s questionnaire on learning styles and semi-structured interviews. The outcome of this study revealed that the participants used all the learning styles such as Visual, Auditory, Read and Write, and Kinesthetic (VARK). The most favoured learning style indicated by the questionnaire responses was Auditory. The interview responses indicated that they used different learning styles, but each participant had the most preferred learning style. The study concluded that learners should be allowed to integrate varied learning styles to improve their learning and make learning interesting and relaxed. The study will be beneficial in formulating policies (at the tertiary education level) that seek to provide different opportunities for students regarding learning styles and preferences for studying English as a second language.
Abstract Introduction The number of postmenopausal women is expected to grow dramatically in the coming decades in Iran. Adopting a health-promoting lifestyle (HPL) is essential for improving health and quality of life of this population. This study pursues two objectives: (1) to assess the HPL levels among Iranian postmenopausal women and (2) to investigate the socio-demographic and psychological variables including self-efficacy and self-esteem associated with HPL. Methods In this cross-sectional study with correlational design, 400 married postmenopausal women in Shiraz (southwestern Iran) were selected via stratified random sampling. The data collection tools were the Health-Promoting Lifestyle Profile-II (HPLP-II), General Self-Efficacy Scale (GSE), the Rosenberg Self-Esteem Scale, and a sociodemographic information questionnaire. Pearson’s correlation coefficient test, independent samples t-tests, and stepwise multiple linear regression were used for analyzing the data in SPSS v. 22. Results The average age of natural menopause among participants was 49.33 ± 3.43 years, and they had relatively good HPLP (136.52 ± 21.46). The results highlighted that among all the HPLP subscales, the highest mean score was observed for health responsibility (33.62 ± 6.98), whereas the lowest scores were observed for stress management (12.26 ± 3.13) and physical activity (17.64 ± 6.52). Both self-efficacy (r = 0.445, p < 0.01) and self-esteem (r = 0.425, p < 0.01) demonstrated significant, moderate positive correlations with the total HPL score. Also, there was a significant association between the total HPLP score and two demographic variables: women’s education (r = 0.17, p < 0.01) and husband’s educational level (r = 0.113, p < 0.05). In addition, the HPLP total score had a significant negative relationship with the number of children (r=-0.114, p < 0.05). The stepwise multiple linear regression analysis revealed that the variables independently associated with the HPL of participants were self-efficacy (β = 0.32, p < 0.001), self-esteem (β = 0.27, p < 0.001), and occupation (β = 0.144, p < 0.001). Conclusion It is suggested that health care professionals implement comprehensive planning to enhance the HPL of postmenopausal women. Interventions aimed at improving HPL in this population should prioritize strategies to enhance self-efficacy and self-esteem. Particular attention should be paid to women with lower education, unemployment, and a higher number of children.
Gynecology and obstetrics, Public aspects of medicine
Yeimy Andrea Rivera Cerquera, Milany Andrea Gómez Betancur
El presente artículo busca identificar las deficiencias en la implementación de los estudios afrodescendientes en la educación secundaria en Colombia a partir de una revisión sistemática centrada en América Latina y el Caribe. Para lograrlo se revisaron 2653 contenidos publicados entre 2015 y 2024 en bases de datos y motores de búsqueda especializados (Dialnet, Redalyc, Unesdoc, Jstor, Scopus, Scielo y Google Scholar), de los cuales un total de 29 cumplió los criterios PRISMA y los de inclusión-exclusión definidos por las investigadoras. Los hallazgos revelan una falta de implementación de estos estudios en la región a pesar de los avances legislativos. Aunque se muestran esfuerzos por cumplir la normativa, se evidencia la falta de voluntad de las directivas, el poco seguimiento de las entidades territoriales, la apatía de algunos docentes, la escasez de recursos y materiales didácticos, y la poca preparación docente en esta área.
The societal role of technology, including artificial intelligence (AI), is often shaped by sociocultural narratives. This study examines how U.S. news media construct narratives about the efficacy of generative AI (GenAI), using ChatGPT in higher education as a case study. Grounded in Agenda Setting Theory, we analyzed 198 articles published between November 2022 and October 2024, employing LDA topic modeling and sentiment analysis. Our findings identify six key topics in the media discourse, with sentiment analysis revealing generally positive portrayals of ChatGPT's integration into higher education through policy, curriculum, teaching practices, collaborative decision-making, skill development, and human-centered learning. In contrast, media narratives express more negative sentiment regarding their impact on entry-level jobs and college admissions. This research highlights how media coverage can influence public perceptions of GenAI in education and provides actionable insights for policymakers, educators, and AI developers navigating its adoption and representation in public discourse.
Sinh Trong Vu, Huong Thu Truong, Oanh Tien Do
et al.
Large language models have been widely applied in many aspects of real life, bringing significant efficiency to businesses and offering distinctive user experiences. In this paper, we focus on exploring the application of ChatGPT, a chatbot based on a large language model, to support higher educator in generating quiz questions and assessing learners. Specifically, we explore interactive prompting patterns to design an optimal AI-powered question bank creation process. The generated questions are evaluated through a "Blind test" survey sent to various stakeholders including lecturers and learners. Initial results at the Banking Academy of Vietnam are relatively promising, suggesting a potential direction to streamline the time and effort involved in assessing learners at higher education institutes.
Isaac Alpizar-Chacon, Hieke Keuning, Imke de Jong
et al.
The application of Artificial Intelligence, in particular Generative AI, has become more widespread among educational institutions. Opinions vary widely on whether integrating AI into classrooms is the way forward or if it is detrimental to the quality of education. Increasingly, research studies are giving us more insight into the consequences of using AI tools in learning and teaching. Studies have shown how, when, and why students use AI tools. Because developments regarding the technology and its use are moving fast, we need frequent, ongoing, and more fine-grained investigation. One aspect that we do not know much about yet is how students use and think about AI across \textit{different types of education}. In this paper, we present the results of a multi-institutional survey with responses from 410 students enrolled in the computing programs of 23 educational institutions, representing high schools, colleges, and research universities. We found distinct usage patterns across the three educational institution types. Students from all types express excitement, optimism, and gratitude toward GenAI. Students in higher education more often report worry and skepticism, while high school students report greater trust and fewer negative feelings. Additionally, the AI hype has had a minimal influence, positive or negative, on high school students' decision to pursue computing. Our study contributes to a better understanding of inter-institutional differences in AI usage and perception and can help educators and students better prepare for future challenges related to AI in computing education.
The current study describes a cost-effective method for adapting large language models (LLMs) for academic advising with study-abroad contexts in mind and for application in low-resource methods for acculturation. With the Mistral-7B-Instruct model applied with a Low-Rank Adaptation (LoRA) method and a 4-bit quantization method, the model underwent training in two distinct stages related to this study's purpose to enhance domain specificity while maintaining computational efficiency. In Phase 1, the model was conditioned with a synthetic dataset via the Gemini Pro API, and in Phase 2, it was trained with manually curated datasets from the StudyAbroadGPT project to achieve enhanced, contextualized responses. Technical innovations entailed memory-efficient quantization, parameter-efficient adaptation, and continuous training analytics via Weights & Biases. After training, this study demonstrated a reduction in training loss by 52.7%, 92% accuracy in domain-specific recommendations, achieved 95% markdown-based formatting support, and a median run-rate of 100 samples per second on off-the-shelf GPU equipment. These findings support the effective application of instruction-tuned LLMs within educational advisers, especially in low-resource institutional scenarios. Limitations included decreased generalizability and the application of a synthetically generated dataset, but this framework is scalable for adding new multilingual-augmented and real-time academic advising processes. Future directions may include plans for the integration of retrieval-augmented generation, applying dynamic quantization routines, and connecting to real-time academic databases to increase adaptability and accuracy.
Cognitive structure is a student's subjective organization of an objective knowledge system, reflected in the psychological construction of concepts and their relations. However, cognitive structure assessment remains a long-standing challenge in student modeling and psychometrics, persisting as a foundational yet largely unassessable concept in educational practice. This paper introduces a novel framework, Cognitive Structure Generation (CSG), in which we first pretrain a Cognitive Structure Diffusion Probabilistic Model (CSDPM) to generate students' cognitive structures from educational priors, and then further optimize its generative process as a policy with hierarchical reward signals via reinforcement learning to align with genuine cognitive development levels during students' learning processes. Experimental results on four popular real-world education datasets show that cognitive structures generated by CSG offer more comprehensive and effective representations for student modeling, substantially improving performance on KT and CD tasks while enhancing interpretability.
Amrina Octaviana, Roslina Roslina, Ika Fitria Elmeida
et al.
The maternal mortality rate (MMR) in Lampung Province in 2020 has increased compared to 2019, namely from 110 cases to 115 cases. Bandar Lampung City is one of the regions in Lampung Province with the third highest MMR, 10 cases (8.69%). This research aims to determine the description of childbirth complications experienced by postpartum mothers using the IKAlin instrument (Labour Complications Instrument) in Bandar Lampung in 2023. This type of research uses a descriptive survey method with random sampling. A sample of 222 postpartum mothers with labor complications. This research method involves interviews with postpartum mothers using the IKAlin instrument. The average results of mothers' answers show that the complication of preeclampsia that is felt is high blood pressure, the bleeding complication that is most often felt during labor is experiencing heavy bleeding, and the complication of dystocia that is most often felt is undergoing a prolonged second stage. The advice given is to encourage education about early detection in the community so that people, especially pregnant women, are aware of the importance of monthly pregnancy checks at health facilities to detect birth complications as early as possible.
This article presents a comprehensive analysis of the potential integration and implications of Small Modular Reactors (SMRs) into Colombia's energy matrix, set against the backdrop of the global energy transition and the urgent need to address climate change. Focusing on the technical and technological aspects of nuclear energy, particularly SMRs, the study explores the advantages of nuclear power in terms of constant generation capacity and minimal carbon emissions, while also addressing public perception challenges and radioactive waste management. It delves into Colombia's current energy landscape, dominated by hydroelectric and thermal power, and highlights the need for diversification and resilience in the face of climatic and geopolitical challenges. The potential of SMRs in Colombia is scrutinized, considering their operational costs, environmental impact, and role in non-interconnected zones. Additionally, the article examines Colombia's historical and future trajectory in nuclear energy, emphasizing the importance of a robust regulatory framework, sustainable mining practices, public education, and awareness. The study concludes with strategic recommendations for Colombia, advocating for continuous training, international cooperation, exploration of economic opportunities, and investment in renewable energies alongside nuclear power to ensure a sustainable and diversified energy future.
Non-communicable diseases (NCDs) are still a morbidity and mortality problem in Southeast Asia. However, NCD in Southeast Asia still needs to be handled faster. WHO recommends the use of digital in treating NCDs in Southeast Asia. Therefore, this literature review study aims to describe how mHealth is utilized to overcome the problem of NCDs in Southeast Asian countries. The author collected articles using Google Scholar and Proquest, which were published in 2019-2023. The focus of the search was articles published in English-language Research Journals. Researchers used advanced search with the keywords NCD, Non-communicable diseases, mHealth, Mobile Health, Nursing, and Health Promotion. Keywords are combined using Boolean and/or the online database that the researcher chose. Articles that have been filtered are filtered again by selecting research locations in Southeast Asian countries. Ten articles obtained came from research in Southeast Asian countries Indonesia (n=4), Malaysia (n=1), Singapore (n=1), Vietnam (n=1), Thailand (1), Cambodia (n=1), Philippines (n=1). All articles discussed the use of mHealth for NCD management in their countries and aimed to determine the barriers (n=3), feasibility (n=1), effectiveness (n=2), impact (n=2), potential (n=1), perception (n=1), and perspective (n=1) of service providers, as well as the experience of using mHealth in remote areas (n=1). It can be concluded that mHealth can be used for independent screening for PTM, providing education about NCDs, and can be applied in rural areas as a comprehensive effort to handle NCDs.
Ievgeniia Kuzminykh, Tareita Nawaz, Shihao Shenzhang
et al.
AI tools, particularly large language modules, have recently proven their effectiveness within learning management systems and online education programmes. As feedback continues to play a crucial role in learning and assessment in schools, educators must carefully customise the use of AI tools in order to optimally support students in their learning journey. Efforts to improve educational feedback systems have seen numerous attempts reflected in the research studies but mostly have been focusing on qualitatively benchmarking AI feedback against human-generated feedback. This paper presents an exploration of an alternative feedback framework which extends the capabilities of ChatGPT by integrating embeddings, enabling a more nuanced understanding of educational materials and facilitating topic-targeted feedback for quiz-based assessments. As part of the study, we proposed and developed a proof of concept solution, achieving an efficacy rate of 90% and 100% for open-ended and multiple-choice questions, respectively. The results showed that our framework not only surpasses expectations but also rivals human narratives, highlighting the potential of AI in revolutionising educational feedback mechanisms.
This study conducts a comparative analysis of national policies on Generative AI across four countries: China, Japan, Mongolia, and the USA. Employing the Qualitative Comparative Analysis (QCA) method, it examines the responses of these nations to Generative AI in higher education settings, scrutinizing the diversity in their approaches within this group. While all four countries exhibit a positive attitude toward Generative AI in higher education, Japan and the USA prioritize a human-centered approach and provide direct guidance in teaching and learning. In contrast, China and Mongolia prioritize national security concerns, with their guidelines focusing more on the societal level rather than being specifically tailored to education. Additionally, despite all four countries emphasizing diversity, equity, and inclusion, they consistently fail to clearly discuss or implement measures to address the digital divide. By offering a comprehensive comparative analysis of attitudes and policies regarding Generative AI in higher education across these countries, this study enriches existing literature and provides policymakers with a global perspective, ensuring that policies in this domain promote inclusion rather than exclusion.
John C. Howell, Brian Flores, Juan Javier Naranjo
et al.
We report on an educational pilot program for low-cost physics experimentation run in Ecuador, South Africa, and the United States. The program was developed after having needs-based discussions with African educators, researchers, and leaders. It was determined that the need and desire for low-cost, skills-building, and active-learning tools is very high. From this, we developed a 3D-printable, Raspberry Pi-based multispectral camera (15 to 25 spectral channels in the visible and near-IR) for as little as $100. The program allows students to learn 3D modeling, 3D printing, feedback, control, image analysis, Python programming, systems integration and artificial intelligence as well as spectroscopy. After completing their cameras, the students in the program studied plant health, plant stress, post-harvest fruit ripeness, and polarization and spectral analysis of nanostructured insect wings, the latter of which won the ``best-applied research" award at a conference poster session and will be highlighted in this paper. Importantly, these cameras can be an integral part of any developing country's agricultural, recycling, medical, and pharmaceutical infrastructure. Thus, we believe this experiment can play an important role at the intersection of student training and developing countries' capacity building.
This survey is an updated and improved version of the previous one published in 2013 in this journal with the title data mining in education. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last decade, this research area has evolved enormously and a wide range of related terms are now used in the bibliography such as Academic Analytics, Institutional Analytics, Teaching Analytics, Data-Driven Education, Data-Driven Decision-Making in Education, Big Data in Education, and Educational Data Science. This paper provides the current state of the art by reviewing the main publications, the key milestones, the knowledge discovery cycle, the main educational environments, the specific tools, the free available datasets, the most used methods, the main objectives, and the future trends in this research area.
The rapid advancement of generative Artificial Intelligence (AI) technologies, particularly Generative Pre-trained Transformer (GPT) models such as ChatGPT, has the potential to significantly impact cybersecurity. In this study, we investigated the impact of GPTs, specifically ChatGPT, on tertiary education in cybersecurity, and provided recommendations for universities to adapt their curricula to meet the evolving needs of the industry. Our research highlighted the importance of understanding the alignment between GPT's ``mental model'' and human cognition, as well as the enhancement of GPT capabilities to human skills based on Bloom's taxonomy. By analyzing current educational practices and the alignment of curricula with industry requirements, we concluded that universities providing practical degrees like cybersecurity should align closely with industry demand and embrace the inevitable generative AI revolution, while applying stringent ethics oversight to safeguard responsible GPT usage. We proposed a set of recommendations focused on updating university curricula, promoting agility within universities, fostering collaboration between academia, industry, and policymakers, and evaluating and assessing educational outcomes.