Search Results (50)

Background: We present a multidisciplinary training experience based on simulation techniques and critical resource management implemented in the emergency department. Methods: Simulation courses/workshops were conducted with a multidisciplinary team from the Hospital Emergency Department. The timeline for their development includes a preliminary analysis of needs, objectives, and scenario design, development of the simulation course, and finally, areas of implementation. In this last phase, the teaching team prepares a document and/or report/summary of the activity in which, among other things, the aspects with the greatest capacity for improvement or the areas for implementation of safety measures are determined. A total of 112 healthcare professionals (doctors, nurses, and care assistants) participated in this training program. Its design consisted of the following stages: a preliminary analysis of training needs, the establishment of objectives and scenario design, the development of the simulation workshop, and finally, a report on areas for improvement in patient safety identified during the workshop learning process. Results: The workshops enabled us to identify areas for improvement and develop local protocols/recommendations aimed at improving patient safety in the emergency department, such as standardizing a protocol to guide us in managing resources in crisis situations, a protocol for airway management, a protocol for massive transfusion, and a review of the triage process. In addition, we added value by incorporating cognitive aids and visual tools into the standardization of processes. Conclusions: For resource management in this type of crisis in the hospital emergency setting, it is essential to use a debriefing process guided by experienced instructors after a specific experiential learning experience through simulation scenarios. This helps to contextualize and analyze the advantages and disadvantages of general recommendations. Full article

The integration of Artificial Intelligence (AI) in education has raised important questions about its role in supporting inclusive practices, particularly in special education. This qualitative-dominant study with quantitative support examines how special education teachers in inclusive primary classrooms in Greece use ChatGPT to design Individualized Education Programs (IEPs) for students with learning disabilities. Six teachers participated, with some employing ChatGPT and others relying on traditional methods. The quality of IEP goals was described using the Revised IEP/IFSP Goals and Objectives Rating Instrument (R-GORI), while in-depth teacher perspectives were explored through thematic analysis. Findings suggest that ChatGPT contributed to clearer goal-setting, generation of diverse instructional resources, and more structured lesson planning. However, teachers emphasized the need for critical oversight, adaptation to real-world classroom conditions, and safeguarding the relational and emotional aspects of teaching. Participants expressed cautious optimism, viewing ChatGPT as a valuable support tool when integrated thoughtfully and ethically. These context-specific, exploratory results offer preliminary guidance for educators, policymakers, and researchers seeking to integrate AI tools into special education. They highlight the importance of targeted professional development, ethical safeguards, and further large-scale research to evaluate the broader applicability of AI-assisted IEP planning. Full article

Many early career educators, such as teaching assistants (TAs) in college courses, as well as pre-college educators, need help both with content and pedagogical knowledge to effectively help their students learn. One pedagogical approach that has been found effective in prior studies is collaboration with peers. Collaborative learning not only has the potential to help educators develop content knowledge but can also improve their pedagogical knowledge. This study examines the performance of physics graduate students, enrolled in a professional development course for teaching assistants (TAs), on the Magnetism Conceptual Survey, highlighting the impact of peer collaboration on learning both content and pedagogy. Peer interaction significantly improved performance, driven by both construction of knowledge (where the group answered a question correctly but only one member had the correct individual response) and co-construction of knowledge (where the group succeeded despite both members initially answering incorrectly). Beyond improving content understanding, peer collaboration can also foster pedagogical skills by encouraging early educators such as TAs to use peers as learning resources and communicate ideas effectively to support mutual understanding. These dual benefits—enhancing both content mastery and teaching abilities—demonstrate that this approach holds value not only for the professional development of TAs but can also be adapted for pre-college professional development programs to improve teaching and learning outcomes. Full article

Background/Objectives: Strengthening antimicrobial stewardship (AMS) programs is an invaluable intervention in the ongoing efforts to contain the threat of antimicrobial resistance (AMR), particularly in low-resource settings. This study evaluates the impact of the Telementoring, Education, and Advocacy Collaboration initiative for Health through Antimicrobial Stewardship (TEACH AMS), which uses the virtual Extension for Community Healthcare Outcomes (ECHO) learning model to enhance AMS capacity in Kenya, Ghana, and Malawi. Methods: A mixed-methods approach was used, which included attendance data collection, facility-level assessments, post-session and follow-up surveys, as well as focus group discussions. Results: Between September 2023 and February 2025, 77 virtual learning sessions were conducted, engaging 2445 unique participants from hospital-based AMS committees and health professionals across the three countries. Participants reported significant knowledge gain, and data showed facility improvements in two core AMS areas, including the implementation of multidisciplinary ward-based interventions/communications and enhanced monitoring of antibiotic resistance patterns. Along those lines, participants reported that the program assisted them in improving prescribing and culture-based treatments, and also evidence-informed antibiotic selection. The evidence of implementing ward-based interventions was further stressed in focus group discussions, as well as other strengthened practices like point-prevalence surveys, and development or revision of stewardship policies. Substantial improvements in microbiology services were also shared by participants, particularly in Malawi. Other practices mentioned were strengthened multidisciplinary communication, infection prevention efforts, and education of patients and the community. Conclusions: Our findings suggest that a virtual case-based learning educational intervention, providing structured and tailored AMS capacity building, can drive behavior change and strengthen healthcare systems in low resource settings. Future efforts should aim to scale up the engagements and sustain improvements to further strengthen AMS capacity. Full article

This study examined the effectiveness of professional development for inclusive education and best practices through a short-term technical assistance (TA) model across 15 schools. The professional development was structured to enhance school professionals’ knowledge about inclusion as a concept, as well as best practices in inclusive education. Topics included the use of accommodations and modifications, differentiation and Universal Design for Learning (UDL), building an inclusive school culture, and co-teaching. Pre- and post-test measures were utilized to measure participants’ growth in the knowledge of these topics. Descriptive statistics and dependent t-tests were utilized to analyze data across all topic areas. The findings indicate that short-term TA models of professional development prove beneficial for improving attitudes and beliefs in inclusive education for content knowledge and building an inclusive school culture. Short-term TA did not yield statistically significant increases for classroom strategies or implementation, suggesting that more intensive professional development models need to be incorporated as a wider professional development plan for using best practices in inclusive education by school professionals. Full article

Theory and practice related to computing education with racially/ethnically and linguistically diverse groups of preschoolers remain in nascent stages. Accordingly, early childhood educators both require substantial support when integrating culturally responsive computing into curriculum and instruction and offer valuable perspectives on emerging practices. The purpose of this research study is to explore how educator voice-directed efforts support the implementation of a culturally relevant preschool robotics program through multi-year professional development. Through qualitative analyses, we examined how educator voice, conceptualized as perspectives and participation, guided the direction of professional learning situated within a larger research-practice partnership using design-based research (DBR) methodology. By comparing voice across these sessions, we were able to identify what roles educators assumed within the partnership and how those roles shifted over time. Further, we are able to identify the structural and systemic factors that may have affected their participation and implementation. Findings show a contrast in roles across the different stages of the partnership, suggesting implications for embedding professional learning within broader partnership work as a way to cultivate educator leadership and to realize culturally responsive computing education in sustainable ways. Full article

Gamification and game-based learning provide the opportunity to acquire knowledge and skills on a given subject in a practical and interactive way. They are an innovative teaching methodology that could be used for competence acquisition in a variety of fields. This study focuses on two domains: technology (including robotics) and care. This study evaluates the usability of RobotCareMaker^®, a board game designed to teach care robotics, a branch of robotics oriented towards the study of human care. RobotCareMaker^® consists of 106 elements. The playing cards are the engine of the game and the element of interaction between players. A convenience sample was selected. Usability was evaluated by the System Usability Scale (SUS) questionnaire modified for the game, and three questions about the game experience were used. Using a modified SUS questionnaire, 21 participants rated it with an excellent score of 80.36. Over 90% found the instructions clear and error-free. RobotCareMaker^® allows teachers, professionals, and nursing students to integrate curricular competencies in novel topics such as care robotics. The result suggests that RobotCareMaker^® enhances learning in assistive robotics, improving competencies in education and healthcare. Full article

Client-initiated workplace violence in educational settings is a global issue affecting both teaching and non-teaching employees, such as instructional assistants, counselors, and administrators, among other school workers. Although studies on violence in educational settings have primarily focused on students, there has been growing interest in examining violence against teachers and, more recently, against teaching assistants and other educational professionals. This systematic review aims to analyze studies from diverse educational settings to examine the characteristics, causes, effects, and coping strategies associated with violence perpetrated by students, parents, or guardians, with the goal of informing and advancing prevention strategies. Following the PRISMA 2020 guidelines, a systematic literature review was conducted, analyzing studies across various educational environments to examine the characteristics, causes, effects, and coping strategies of violence perpetrated by students, parents, or guardians. This review revealed a significant prevalence of physical, psychological, and verbal assaults. However, most studies originated from Anglo-Saxon contexts, limiting their generalizability to diverse cultural and educational settings. The lack of research in other languages and in underrepresented regions highlights critical gaps in understanding this issue globally. The revision conclude that workplace violence in educational settings demands urgent and comprehensive responses involving all stakeholders. Implementing targeted prevention strategies and fostering a culture of respect are essential to ensure safe and healthy learning environments. Full article

In light of the remarkable success of large language models (LLMs) in natural language understanding and generation, a trend of applying LLMs to professional domains with specialized requirements stimulates interest across various fields. It is desirable to further understand the level of intelligence that can be achieved by LLMs in solving domain-specific problems, as well as the resources that need to be invested accordingly. This paper studies the problem of generating high-quality test questions with specified knowledge points and target cognitive levels in AI-assisted teaching and learning. Our study shows that LLMs, even those as immense as GPT-4 or Bard, can hardly fulfill the design objectives, lacking clear focus on cognitive levels pertaining to specific knowledge points. In this paper, we explore the opportunity of enhancing the capability of LLMs through system design, instead of training models with substantial domain-specific data, consuming mass computing and memory resources. We propose a novel design scheme that orchestrates a dual-LLM engine, consisting of a question generation model and a cognitive-level evaluation model, built with fine-tuned, lightweight baseline models and prompting technology to generate high-quality test questions. The experimental results show that the proposed design framework, TwinStar, outperforms the state-of-the-art LLMs for effective test question generation in terms of cognitive-level adherence and knowledge relevance. TwinStar implemented with ChatGLM2-6B improves the cognitive-level adherence by almost 50% compared to Bard and 21% compared to GPT-4.0. The overall improvement in the quality of test questions generated by TwinStar reaches 12.0% compared to Bard and 2% compared with GPT-4.0 while our TwinStar implementation consumes only negligible memory space compared with that of GPT-4.0. An implementation of TwinStar using LLaMA2-13B shows a similar trend of improvement. Full article

Background/Objectives: Autism spectrum disorder (ASD) is a group of developmental disorders characterized by poor social skills, low motivation in activities, and a lack of interaction with others. Traditional intervention approaches typically require support under the direct supervision of well-trained professionals. However, teaching and training programs for children with ASD can also be enhanced by assistive technologies, artificial intelligence, and robotics. Methods: In this study, we examined whether robotics can improve the imitation skills of children with autism and support therapists during therapeutic sessions. We designed scenarios for training hand clapping imitation skills using the NAO robot and analyzed the interaction between children with autism and the robot. Results: We developed a deep learning approach based on the human action recognition algorithm for analyzing clapping imitation. Conclusions: Our findings suggest that integrating robotics into therapeutic practices can effectively enhance the imitation skills of children with ASD, offering valuable support to therapists. Full article

Traditional engineering education cannot effectively respond to the demand for talents in the construction of smart cities. The application of digital twin technology in education is mostly based on case studies and lacks empirical tests. This study takes the practical teaching of a project-based course on smart city parks as an example to explore the action intention of graduate students to use digital twin technology consistently, and to provide a theoretical basis and teaching practice guidance to promote the rational application of digital twin technology in engineering education. This study set up a quasi-experimental design through the digital twin learning system, grouping 24 graduate students with 4 faculty members. The experimental group is digital twin-assisted practical teaching, and the control group is traditional teaching method, the experimental cycle is 12 weeks, and the total lesson time is 24 h. Secondly, combined with UTAUT2 model and TTF theory, the variable factor hypothesis was adopted as the scale design means, and the experimental validity was improved through questionnaire data analysis. Meanwhile, the influencing factors in the use of digital twin platform were recorded in detail through the process of data collection, data processing and modeling, as well as the application practice of digital twin platform. Finally, the results of the comprehensive survey data show that the graduate students in the experimental group are significantly better than the control group in terms of self-confidence, skill enhancement, learning outcomes, and learning experience. All these results provide information for course teaching practice, training professional teaching teams, optimizing innovative teaching paths, and promoting the cultivation and delivery of smart city technology talents. Full article

The current study investigates the perceptions of four student teachers of implementing AI tools for designing ELT lessons into their microteaching sessions. The professional development of student teachers achieved via adapting AI tools has not been widely investigated, since the majority of available studies focus on the students’ learning of language skills with AI tools. This study follows the appreciative inquiry approach that emphasises positive teaching practices, aiming to foster sustainable professional development. The participants of the study were MA student teachers studying the Advanced Teaching Practicum course at a Saudi university over one academic semester. Their experiences of designing ELT lessons for their microteaching sessions were reflected upon in reflective journals and a BlackBoard forum. The qualitative analyses of the journals, the forum and lesson plans revealed that the participants appreciated using AI tools, despite the few challenges that occurred. This study demonstrates the participants’ independent efforts that led them to use AI tools that have not been addressed by ELT researchers. The authors hope that this study will enrich ELT practices, assist AI designers in developing their designs by understanding teachers’ experiences and contribute to a sustainable educational future. Full article

As artificial intelligence (AI) becomes increasingly prevalent, it has become a topic of interest in education. The use of AI in education poses complex issues, not only in terms of its impact on teaching and learning outcomes but also in terms of the ethical considerations regarding personal data and the individual needs of each student. Our study systematically analyzed empirical research on the use of AI in primary education, specifically for children aged 4–12 years old. We reviewed 35 articles indexed in SCOPUS, filtered them according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzed them, and categorized the findings. The research focused on the studies’ objectives, learning content, learning outcomes, learning activities, and the pedagogy of activities or the AI tools. Our categorization resulted in three main categories of research objectives regarding the creation, implementation, and evaluation of AI tools and five categories for learning content: AI and ML (machine learning) concepts in STEM and STEAM, language learning, mathematics, arts, and various other subjects. The learning activities were split into four categories: apply, engage, interact, use; project-based learning with multiple activities; experience and practice; and students as tutors. The learning outcomes were split into three levels: cognitive, affective, and psychomotor. The pedagogy of AI tools falls into four categories: constructivism, experiential learning, AI-assisted learning, and project-based learning. The implications for teacher professional development are discussed. Full article

Accurate and efficient flower identification holds significant importance not only for the general public—who may use this information for educational, recreational, or conservation purposes—but also for professionals in fields such as botany, agriculture, and environmental science, where precise flower recognition can assist in biodiversity assessments, crop management, and ecological monitoring. In this study, we propose a novel flower recognition method utilizing a masked autoencoder, which leverages the power of self-supervised learning to enhance the model’s feature extraction capabilities, resulting in improved classification performance with an accuracy of 99.6% on the Oxford 102 Flowers dataset. Consequently, we have developed a large-scale masked autoencoder pre-training model specifically tailored for flower identification. This approach allows the model to learn robust and discriminative features from a vast amount of unlabeled flower images, thereby enhancing its generalization ability for flower classification tasks. Our method has been applied successfully to flower target detection, achieving a Mean Average Precision (mAP) of 71.3%. This result underscores the versatility and effectiveness of our approach across various flower-related tasks, including both detection and recognition. Simultaneously, we have developed a straightforward, user-friendly flower recognition and classification software application, which offers convenient and reliable references for flower education, teaching, dataset annotation, and other uses. Full article

This study aimed to analyze the communication process of healthcare professionals for the promotion of health literacy. It is a qualitative study that utilized individual online interviews with 46 healthcare professionals working in Brazil. The thematic content analysis technique proposed by Bardin was employed, and Atlas Ti software assisted in the assessment and interpretation of the texts. Content categorization revealed 26 sub-themes, and the coding of these identified nine themes and three categories. The communication process in health literacy education was composed of a set of interdependent and interrelated variables termed emotions, professional preparedness, interprofessional collaboration, patient needs assessment, building rapport, family inclusion in the educational process, environmental aspects, strategies, and resources for teaching and learning. These data may support the analysis of health communication in healthcare services, the creation of data collection instruments, and the development of training programs to enhance skills within the context of the identified variables. Full article