Search Results (71)

Background: Artificial intelligence and machine learning are playing crucial roles in digital transformation, aiming to improve the efficiency, effectiveness, equity, and responsiveness of primary health systems and their services. Method: Using synthetic knowledge synthesis and bibliometric and thematic analysis triangulation, we identified the most productive and prolific countries, institutions, funding sponsors, source titles, publications productivity trends, and principal research categories and themes. Results: The United States and the United Kingdom were the most productive countries; Plos One and BJM Open were the most prolific journals; and the National Institutes of Health, USA, and the National Natural Science Foundation of China were the most productive funding sponsors. The publication productivity trend is positive and exponential. The main themes are related to natural language processing in clinical decision-making, primary health care optimization focusing on early diagnosis and screening, improving health-based social determinants, and using chatbots to optimize communications with patients and between health professionals. Conclusions: The use of machine learning in primary health care aims to address the significant global burden of so-called “missed diagnostic opportunities” while minimizing possible adverse effects on patients. Full article

As gaitpathology assessment systems improve both in accuracy and efficiency, the prospect of using these systems in real healthcare applications is becoming more realistic. Although gait analysis systems have proven capable of detecting gait abnormalities in supervised tasks in laboratories and clinics, there is comparatively little investigation into making such systems explainable to healthcare professionals who would use gait analysis in practice in home-based settings. There is a “black box” problem with existing machine learning models, where healthcare professionals are expected to “trust” the model making diagnoses without understanding its underlying reasoning. To address this applicational barrier, an end-to-end pipeline is introduced here for creating graph feature embeddings, generated using a bespoke Spatio-temporal Graph Convolutional Network and per-joint Principal Component Analysis. The latent graph embeddings produced by this framework led to a novel semi-supervised weighting function which quantifies and ranks the most important joint features, which are used to provide a description for each pathology. Using these embeddings with a K-means clustering approach, the proposed method also outperforms the state of the art by between 4.53 and 16% in classification accuracy across three datasets with a total of 14 different simulated gait pathologies from minor limping to ataxic gait. The resulting system provides a workable improvement to at-home gait assessment applications by providing accurate and explainable descriptions of the nature of detected gait abnormalities without need of prior labeled descriptions of detected pathologies. Full article

Background/Objectives: The brain serves as the central command center for the nervous system in the human body and is made up of nerve cells known as neurons. When these nerve cells grow rapidly and abnormally, it can lead to the development of a brain tumor. Brain tumors are severe conditions that can significantly reduce a person’s lifespan. Failure to detect or delayed diagnosis of brain tumors can have fatal consequences. Accurately identifying and classifying brain tumors poses a considerable challenge for medical professionals, especially in terms of diagnosing and treating them using medical imaging analysis. Errors in diagnosing brain tumors can significantly impact a person’s life expectancy. Magnetic Resonance Imaging (MRI) is highly effective in early detection, diagnosis, and classification of brain cancers due to its advanced imaging abilities for soft tissues. However, manual examination of brain MRI scans is prone to errors and heavily depends on radiologists’ experience and fatigue levels. Swift detection of brain tumors is crucial for ensuring patient safety. Methods: In recent years, computer-aided diagnosis (CAD) systems incorporating deep learning (DL) and machine learning (ML) technologies have gained popularity as they offer precise predictive outcomes based on MRI images using advanced computer vision techniques. This article introduces a novel hybrid CAD approach named ViT-PCA-RF, which integrates Vision Transformer (ViT) and Principal Component Analysis (PCA) with Random Forest (RF) for brain tumor classification, providing a new method in the field. ViT was employed for feature extraction, PCA for feature dimension reduction, and RF for brain tumor classification. The proposed ViT-PCA-RF model helps detect early brain tumors, enabling timely intervention, better patient outcomes, and streamlining the diagnostic process, reducing patient time and costs. Our research trained and tested on the Brain Tumor MRI (BTM) dataset for multi-classification of brain tumors. The BTM dataset was preprocessed using resizing and normalization methods to ensure consistent input. Subsequently, our innovative model was compared against traditional classifiers, showcasing impressive performance metrics. Results: It exhibited outstanding accuracy, specificity, precision, recall, and F1 score with rates of 99%, 99.4%, 98.1%, 98.1%, and 98.1%, respectively. Conclusions: Our innovative classifier’s evaluation underlined our model’s potential, which leverages ViT, PCA, and RF techniques, showing promise in the precise and effective detection of brain tumors. Full article

As the Fourth Industrial Revolution (4IR) reshapes society, digital leadership in education becomes crucial. This study explores teachers’ perspectives on high school principals’ digital leadership competencies in Oyo State, Nigeria, a region grappling with the digital divide. This offers a counterpoint to research in high-income countries. Using a quantitative, descriptive research design, 381 teachers across three senatorial districts were selected via multi-stage sampling. The study addressed one research question and tested two hypotheses. Data were collected using the High Schools’ Digital Leadership Standards Questionnaire (HSDLSQ). The reliability coefficients ranged from α = 0.85 to 0.91 across five domains: visionary leadership, digital learning culture, professional development, systemic improvement, and digital citizenship. Descriptive statistics (percentages, mean, and standard deviation) and inferential statistics (independent t-test) were used for analysis at a 0.05 significance level. The findings revealed that high school leaders possess the skills to meet the ISTE-A digital leadership standards set by the International Society for Technology in Education (ISTE). Female leaders exhibited slightly higher digital skills than males, though gender was insignificant in meeting the ISTE-A standards overall. The study underscores the importance of digital leadership in school management, offering practical implications for leadership practices, policy decisions, and future research. Although the ISTE-A standards are met, the emphasis on systemic improvement highlights how Nigerian principals adapt strategies to local resource constraints, differing from high-tech education systems. Recommendations include promoting the ISTE-A standards among school leaders, investing in digital leadership training, fostering digital literacy, and supporting adaptability to technological changes to advance digital transformation in education. Full article

The importance of flood fighting is becoming increasingly apparent worldwide in the context of climate change. In light of the often-limited conditions and resources available for the deployment of military and professional rescue teams in emergencies, flood-fighting corps that help protect communities from floods have been organized by community members in numerous regions. This study aims to evaluate the extent to which the capabilities of flood-fighting corps and other participating organizations were developed through a field exercise conducted in Japan involving 55 relevant organizations and 1025 participants. The requisite data were obtained through structured in-person interviews with 18 participants playing key roles in the exercise, who were questioned about the effects of the exercise. The findings showed that the exercise achieved three principal outcomes: (1) the strengthening of inter-organizational collaboration, (2) the learning of authentic capabilities by simulating a real-world flood-fighting environment, and (3) an increase in public awareness of flood fighting through extensive public relations efforts. Furthermore, this study concluded that the national government should take a leading role in organizing such large-scale exercises involving multiple organizations with diverse cultural backgrounds and responsibilities in order to generate these outcomes. Full article

This study aims to explore the professional learning and development needs of Special Educational Needs Coordinators (SENCOs) as strategic leaders in primary schools in Ireland. With the SENCO role lacking formal recognition in Irish policy, this research is important to identify the support structures necessary to enhance their effectiveness in leading inclusive education. Employing a mixed-methods sequential explanatory design, theoretically framed by Bronfenbrenner’s Ecological Systems Theory and Wenger’s Community of Practice model, the study first surveyed 371 SENCOs to assess their professional learning experiences and needs. This was followed by semi-structured interviews with nine school leaders, including SENCOs, SENCO principals, and principals, to gather in-depth insights into the role’s dynamics. The Department of Education’s school database was used to contact participants. Data analysis utilised descriptive statistics for the survey and reflexive thematic analysis for the interview data. Key findings indicate a significant demand for formal SENCO-specific professional learning programmes, with a focus on leadership, evidence-informed practices, and community engagement. The study concludes that professional learning for SENCOs should be structured around transformative social learning models and should include postgraduate courses and communities of practice. The research calls for policy development to formally recognise the SENCO role, and provide a coherent framework for their professional learning and development to ensure inclusive educational practices are effectively led and implemented in Irish schools. Full article

The relationship between teacher professional learning and school leadership has recently attracted great attention from scientists. However, only a few studies have focused on the relationship between innovative school leadership and teacher professional learning. Therefore, this study aimed to draw attention to the mediating role of the principal–teacher relationship in the relationship between innovative school leadership and teacher professional learning. The study used a quantitative method with a correlational, cross-sectional, and mediation design. Data obtained from 357 teachers working in high schools in Eskişehir, Türkiye, were examined with a mediation analysis based on the bootstrap method. The findings showed that teachers perceived their professional learning highly, school administrators perceived innovative school leadership characteristics highly, and principal–teacher relationships had a significant effect. In addition, moderate positive significant relationships were determined between innovative school leadership and teacher professional learning and principal–teacher relationships; low positive significant relationships were determined between teacher professional learning and principal–teacher relationships. It was determined that the principal–teacher relationship mediated innovative school leadership and teacher professional learning. Our results expand the field’s understanding that innovative leadership is practiced in Türkiye, an eastern society, and that school leadership has the potential to improve student outcomes indirectly through teacher professional learning. Full article

Background: Innovation in education is essential for fostering improved learning outcomes, operation efficiency and school excellence. Many challenges persist due to due to gaps in leadership strategies, limited stakeholder engagement, and inadequate professional development opportunities. This study explores the role of school principals in promoting a culture of innovation in private schools in Abu Dhabi, UAE. Methods: A quantitative research design was employed, utilizing an electronic questionnaire to examine how school leaders drive innovation. The study explores the correlation between a culture of innovation and five key elements: school leadership performance, relationships with students and parents, school activities and programs, the overall school environment, and principals’ demographic factors. An innovation assessment tool measured the level of innovation across selected schools. Results: By identifying key school performance weaknesses, this study aims to provide insights that can help school principals enhance their leadership practices and cultivate a thriving culture of innovation within their institutions. Conclusions: The findings contribute to understanding teachers’ and staff members’ propensity to innovate under effective school leadership. Full article

This interpretive phenomenological study explores the perspectives of in-service, K-12 teachers in a graduate teacher education program on using goal setting to promote culturally responsive practices. The participants set two goals, documented their growth, and rated course instructional strategies that contributed to their learning. Data were collected through written reflections and responses to an anonymous midterm questionnaire in an online forum. Additional data came from the participants’ final reflections, the principal researcher’s reflective teaching notes, and end-of-semester reflections gathered by an unaffiliated critical friend after grades were posted. Coded data revealed that: 1. In-service teachers created goals that were relevant to specific areas of growth in professional learning and development in culturally responsive teaching practices and understanding diverse learners, 2. Goal setting, as a self-regulated learning strategy, serves to empower teachers toward teaching for promoting culturally responsive teaching practices, 3. Instructional supports and activities enhance personal development in becoming culturally responsive teachers, 4. Teacher educators’ reflection-on-action supports professional development. Full article

This article addresses the validation of an instrument designed to measure organizational leadership practices for inclusion and evaluates the said instrument’s factorial structure and convergent validity. This work responds to the need for quantitative tools to assess how school principals promote inclusion, in recognition of its importance for guaranteeing student access to an equitable quality education at all levels, from early childhood education through high school. The above-referenced instrument was developed based on a comprehensive literature review and consultations with experts, resulting in a 36-item scale structured in six key dimensions: D1: Professional Development; D2: Inclusive Vision; D3: Support for the Teaching–Learning Process; D4: Building Networks; D5: Participation and Dialog, and D6: Resource Management. The validation process included a confirmatory factor analysis that supported the existence of a hierarchical structure of a general factor of leadership for inclusion that determines the aforementioned key dimensions, with adequate fit indices (χ²(588) = 1694.624, p < 0.001, CFI = 0.945, TLI = 0.941, RMSEA = 0.060, SRMR = 0.034) and high internal consistency in the general scale (α = 0.98, Ω = 0.96). In terms of convergent validity, the instrument showed significant and consistent correlations with related constructs such as teacher self-efficacy and pedagogical leadership. This study highlights the importance of leadership for inclusion as a central element of fostering participation and learning in diverse school contexts, by providing a reliable tool for continuous improvement of the school management team’s performance of its functions. Also, it is important input for education policymakers charged with formulating student equity, who recognize the enhanced well-being and active participation in the social environment that result from the greater inclusion of students in their educational communities. Full article

Human perceptions of animal consciousness have evolved over time, influencing how they are treated. This study aimed to assess perceptions of animal consciousness in people working in conservation. An online survey of 87 participants evaluated their perceptions of animals’ capabilities across 10 dimensions of consciousness, including self-consciousness, learning, and reasoning. The sum of the answers to the questions was validated as a “perception index” using a principal component analysis. Next, its variation according to taxonomic, demographic, professional factors, and the duration, type, and frequency of interaction with animals was assessed with generalized linear models and stepwise model selection. Participants’ perceptions varied with taxonomic class and the level of education, with mammals obtaining higher indexes than birds (−0.14; 95% confidence interval [CI] −0.24, −0.03, p < 0.01) or reptiles (−0.41; 95% CI −0.55, −0.27, p < 0.01), and respondents holding a PhD exhibiting higher perception indexes than those with BScs (−0.19; 95% CI −0.32, −0.06, p < 0.01) or lower education (−0.18; 95% CI −0.32, −0.03, p = 0.01). The attribution of consciousness followed a phylogenetic pattern, but several exceptions (e.g., the octopus and raven) were noted on a finer scale supporting a multifactorial influence on the perception of animal consciousness that emerges upon a baseline phylogenetic pattern. Finally, the results suggest that conservationists are influenced by culture and scientific knowledge, as much as their personal experiences, when evaluating animals’ perceptions, highlighting the need for further research on the convergence between perception, belief, and evidence. Full article

Background: Tuberculosis (TB) is a bacterial disease that mainly affects the lungs, but it can also impact other parts of the body, such as the brain, bones, and kidneys. The disease is caused by a bacterium called Mycobacterium tuberculosis and spreads through the air when an infected person coughs or sneezes. TB can be inactive or active; in its active state, noticeable symptoms appear, and it can be transmitted to others. There are ongoing challenges in fighting TB, including resistance to medications, co-infections, and limited resources in areas heavily affected by the disease. These issues make it challenging to eradicate TB. Objective: Timely and precise diagnosis is essential for effective control, especially since TB often goes undetected and untreated, particularly in remote and under-resourced locations. Chest X-ray (CXR) images are commonly used to diagnose TB. However, difficulties can arise due to unusual findings on X-rays and a shortage of radiologists in high-infection areas. Method: To address these challenges, a computer-aided diagnosis (CAD) system that uses the vision transformer (ViT) technique has been developed to accurately identify TB in CXR images. This innovative hybrid CAD approach combines ViT with Principal Component Analysis (PCA) and machine learning (ML) techniques for TB classification, introducing a new method in this field. In the hybrid CAD system, ViT is used for deep feature extraction as a base model, PCA is used to reduce feature dimensions, and various ML methods are used to classify TB. This system allows for quickly identifying TB, enabling timely medical action and improving patient outcomes. Additionally, it streamlines the diagnostic process, reducing time and costs for patients and lessening the workload on healthcare professionals. The TB chest X-ray dataset was utilized to train and evaluate the proposed CAD system, which underwent pre-processing techniques like resizing, scaling, and noise removal to improve diagnostic accuracy. Results: The performance of our CAD model was assessed against existing models, yielding excellent results. The model achieved remarkable metrics: an average precision of 99.90%, recall of 99.52%, F1-score of 99.71%, accuracy of 99.84%, false negative rate (FNR) of 0.48%, specificity of 99.52%, and negative predictive value (NPV) of 99.90%. Conclusions: This evaluation highlights the superior performance of our model compared to the latest available classifiers. Full article

This systematic review aims to analyse the existing research on the introduction of maker education in teacher training and continuous professional development. There is a growing interest in defining the state of the art on this topic. Using the WOS database, 20 empirical studies published in peer-reviewed journals between 2019 and 2023 were further analysed. The studies were systematically examined to identify the general characteristics related to the type of maker education training intervention. The principal findings of this review indicate that the majority of training programmes are primarily aimed at pre-service and in-service teachers, and the number of articles published has increased significantly in recent years; moreover, the characteristics of these programmes vary considerably across the studies identified, indicating an uneven distribution of research activity. Despite the growth in the literature, there is still a notable gap in terms of the specific knowledge acquisition that teachers require in order to effectively implement maker education. While many studies emphasise equipping educators with both practical skills and theoretical knowledge, fewer focus solely on knowledge acquisition. This review emphasises the value of immersive experiences for training teachers, demonstrating the positive impact such experiences can have on their confidence and mindset. Additionally, the potential of virtual training programmes to create collaborative, supportive learning environments represents an innovative approach to enhancing teacher preparation in maker education. Based on the findings, it must be emphasised that there is still a need for the further research and development of maker education training models specifically designed to facilitate the integration of making approaches into formal education. Full article

Despite efforts to address racial disparities in STEM fields, little attention has been paid to the experiences and aspirations of queer and trans Black (QT Black) students in grades K-12. This study explored whether there were any significant differences in the choice of STEM majors between QT Black students and non-QT Black students. We found that Black QT students are less likely to choose STEM majors. Additionally, we found significant differences in science teachers’ perceptions of teaching, comparing between QT Black and non-QT Black students. Finally, we found that several factors predicted science-teacher perception of collective responsibility, perceptions of content professional learning community (PLC), self-efficacy, perception of content teacher expectations, and perceptions of principal support for teachers of QT Black and non-QT Black students. Implications for research and practice are discussed. Full article

This article presents a study that addresses the challenge of establishing a relationship between the axiological and the affective, by validating a structural model through an assessment instrument (SEMORCUNA) that isolates the moral feelings associated with ‘affective care’. The research sample consisted of 222 teachers, all of whom were either in training or were active professionals in the teaching field. To achieve the research objectives, a group of experts selected a total of 11 moral sentiments, based on which Principal Component Analysis was conducted. Subsequently, Cronbach’s alpha was calculated to determine the internal consistency of the factors obtained. Confirmatory factor analysis was also performed. The results indicate that the selected feelings are part of a single factor. We conclude that all the emotional–moral experiences included in the test are empirically associated with the value of affective care. This work provides a tool to study the degree of teacher identification with the moral feelings that characterize the school as a ‘learning caring institution’, which is a fundamental condition for ensuring ‘resilient educational communities’. Full article