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This study examines the mediating role of teachers' perceived administrator support in the relationship between principals' social justice leadership behaviors and teachers' trust in principals. The sample of the study, which was designed in the relational survey model, consists of 903 teachers working in public schools in a metropolitan city in Southeast Türkiye. In the context of the research model, the SPSS Process Macro (Model-4) application developed by Hayes (2018) was used to determine the mediation effect. Because of the analysis of the research data, it was determined that the social justice leadership behaviors exhibited by school principals predicted both teachers' trust in the principal and teachers' perceived administrator support positively and statistically significantly. On the other hand, it was concluded that perceived administrator support plays a mediating role in the relationship between principals' social justice leadership behaviors and teachers' trust in principals. In this context, it can be staded that if school administrators' social justice leadership behaviors increase, both the administrator support perceived by teachers and their trust in the principal will increase.

The development, use, and timely promotion of Open Education (OE) has been effective in addressing myriad educational concerns, including inclusivity, accessibility and learning achievement, among many others. However, limited information exists in the literature concerning how OE could enhance Generative Artificial Intelligence (GenAI), which is receiving extensive interest and criticism at this time. To address this research gap, this study relies on the Open Educational Practices (OEP) framework of Huang et al. (2020) to provide various OEP scenarios that could help to promote and facilitate the effective and safe adoption of GenAI in education. The findings of this study could provide guidelines on how relying on OEP when adopting GenAI could help in ensuring quality education which is the sustainable development goal (SDG 4) of the United Nations (UN).

This study was conducted to determine the perceptions of children, one of whose relatives was undergoing chemotherapy treatment and who participated in education at the House of Compassion, about the patient and hospital perceptions and their views on the House of Compassion. Case study design, one of the qualitative research designs, was used. Criterion sampling, one of the purposeful sampling types, was used to determine the study group. The study group consisted of 20 children who participated in the training at the House of Compassion in a hospital in Ankara and one of whose relatives was undergoing chemotherapy treatment. In the study, "Demographic Information Form" was used to collect information about children and parents, "Child Interview Form" and "Children's Pictures" were used to determine children's perceptions of patients, hospital and House of Compassion. The data obtained were analyzed using the descriptive analysis technique. As a result of the research, it was observed that children knew the definition of the hospital, the personnel working in the hospital, and the practices carried out, and emphasized the healing and therapeutic aspects of the hospital. Children reported coming to the House of Compassion to play games, have fun, and have a good time. It was determined that children felt happy and sound in the House of Compassion and that they liked the House of Compassion. As a result, it can be said that the House of Compassion has positive effects on children's perceptions of the patient and the hospital.

This study investigated the role of administrative support in the correlation between teachers' perceptions of organizational support and their levels of leadership. This study adopts a relational screening model. The study population consisted of teachers in elementary, middle, and high schools. The sample consisted of 304 teachers selected through convenience sampling. Data were collected using the "Organizational Support Scale," "Administrative Support Scale" and the "Teacher Leadership Scale." The findings indicate significant positive relationships between teachers' perceptions of organizational support, perceptions of administrative support, and their levels of leadership. When examining whether administrative support mediated the impact of organizational support on teacher leadership, significant effects were observed on the paths connecting organizational support, administrative support, and teacher leadership. Specifically, the paths from organizational support to teacher leadership through administrative support were significant, whereas the direct pathway from organizational support to teacher leadership was not, suggesting that administrative support fully mediated this model. Considering these research findings and the existing literature, it is advisable to structure organizational support and administrative practices that foster teacher leadership in both in-school and out-of-school settings by legal regulations.

This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of GenAI-powered ChatBots in educational interactions, their capability to enrich social learning, and their dual role as both support and assistance within educational settings. This research further highlights the impact of human-GenAI interaction in education from social, psychological, and cultural perspectives, focusing on social presence as a fundamental component of the teaching and learning process. It discusses the integration of GenAI and ChatBots into education and considers whether this marks the dawn of an algorithmic renaissance that elevates educational experiences or an apocalypse that threatens the very essence of human learning and interaction.

In this study, the design, implementation and evaluation processes of the 4MAT teaching model activity, which is designed in accordance with the holistic brain model for teaching the graphic representation of data at the 8th grade level and making the appropriate transformations between these representations, are presented in this study. The implementation of the event took place in two village secondary school in the central district of a province in the south of Turkey in the 2021-2022 academic year. The activity was applied to 42 eighth grade students in two separate classes. A student opinion form was created by the researcher to see how the activity was perceived by the students. Content analysis was carried out in the light of the data obtained from the applied student opinion form. At the end of the research, it was seen that the students stated positive statements about the activity such as realizing permanent learning, prompting thinking, finding original ideas, giving various examples, and providing fun and understandable. At the end of the research, students commented on the activity as providing permanent learning, encouraging thinking, allowing original ideas to be found, and providing fun and understandable learning by giving various examples.

This research aimed to scrutinize and delineate the figures of speech manifesting in English hit songs. A selection of songs from Spotify's Top 30 Hit Songs List was chosen as the study material. The study employed a qualitative content analysis approach to classify the type and calculate the frequency of the figures of speech within the corpus of English hit songs. The results of this study revealed 200 figurative speech examples in our small-scale corpus, which comprised 8352 words. This suggests a prevalence of figurative language use within English-language songs. While metaphors and hyperboles were the most frequently used figures of speech, apostrophes, and understatements were the least common. The results underscore the linguistic richness of hit songs, advocating their inclusion in English language teaching (ELT) classrooms, particularly for vocabulary instruction.

From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial intelligence (AI) on education and critical pedagogy. In this regard, the purpose of this research paper was to investigate the intersection of AI and critical pedagogy by critically assessing the potential of AI to promote or hamper critical pedagogical practices in the context of transhumanism. The article provides an overview of the concepts of transhumanism, artificial intelligence, and critical pedagogy. In order to seek answers to research questions, qualitative research design was adopted, and GPT-3 was used as a data collection resource. Noteworthy findings include the similarity of the dialogue with the GPT-3 davinci model to a conversation between two human beings, as well as its difficulty in understanding some of the questions presented from a critical pedagogy perspective. GPT-3 draws attention to the importance of the relationship between humans in education and emphasizes that AI applications can be an opportunity to ensure equality in education. The research provides suggestions indicating the relationship between AI applications and critical pedagogy.

In this study, the Mathematical Knowledge for Teaching-Elementary Patterns Functions and Algebra-Content Knowledge (MKT-PFA) test, originally developed in English as part of the "Learning Mathematics for Teaching Project" at Michigan University, was adapted into Turkish. The test comprises two equivalent forms, A and B, each translated into Turkish and culturally adapted through consultations with two mathematics education academics and five secondary school math teachers pursuing doctoral studies. A total of 328 preservice teachers at a Turkish public university's elementary school mathematics teaching department were administered form A (14 questions, 29 items) and form B (12 questions, 27 items) at a one-week interval. Psychometric analyses revealed high reliability (KR-20: A=0.712, B=0.735; Lord reliability: A=0.733, B=0.756), and strong correlations (r[subscript pbi]) with the original English forms, indicating suitable adaptation. Item difficulties analyzed using a one-parameter Item Response Theory model showed a normal distribution, affirming the tests' validity for assessing preservice teachers' algebra teaching knowledge in Türkiye.

With the precipitous changes of the platform formerly known as Twitter, brought on by the change of ownership in late 2022, many networked educators sought, and continue to seek, new digital spaces to continue fostering and developing their digital practice. The authors of this article had all been actively networked on Twitter, and wanted to explore these changes in their professional worlds. As we sought out these spaces we critically began to interrogate our own practices on this platform to gain a deeper understanding of our practice going forward. We've approached this exploration through three vectors: an examination of the terms we use to describe movement from platform to platform, digital identity formation and disruption, and building human connection in digital spaces. The findings from our exploration yielded the following conclusions: (1) With regard to metaphors of movement (i.e., "migration") we leave space open as to which metaphor to use as no metaphor is a perfect fit to explain the complexity of this phenomenon. (2) Digital identity/ies are multifaceted and sometimes place-specific, but some networked affordances seemed to encourage an ever-evolving digital identity more than other spaces. (3) Finally, digital spaces afford us the ability to carve out our own communities from the wider academic community, in the process developing a more owned and voiced identity. However as social media platforms are fleeting, those connections -- and identities -- are in danger of getting co-opted or deleted as platforms rise and fall.

Objectives: The aim of this study was to investigate the variables that may affect treatment continuation in children aged 6 to 12 years who were newly diagnosed with ADHD. Methods: A total of 132 children diagnosed with ADHD and their parents participated in the study. Sociodemographic and clinical risk factors affecting continuation of treatment were examined using logistic regression analysis. Results: Multiple model examination revealed that greater age increased the risk of treatment discontinuation 1.824 times (p = 0.003) while a lower total length of paternal education increased the risk of discontinuation (1/0.835) 1.198 times (p = 0.022). Other variables emerging as significant in the univariate model lost that significance in the multiple model. Conclusions: Understanding the variables associated with medication discontinuation in ADHD in different populations and taking these variables into account in the development of health policies, will be useful in improving the long-term devastating effects of the disorder.

This systematic review examines the landscape of extracellular vesicle (EV)-related clinical trials to elucidate the field's trends in clinical applications and EV-related methodologies, with an additional focus on the acknowledgement of EV subpopulations. By analysing data from public reporting repositories, we catalogued 471 EV-related clinical trials to date, with indications for over 200 diseases. Diagnostics and companion diagnostics represented the bulk of EV-related clinical trials with cancer being the most frequent application. EV-related therapeutics trials mainly utilized mesenchymal stromal cell (MSC) EVs and were most frequently used for treatment of respiratory illnesses. Ultracentrifugation and RNA-sequencing were the most common isolation and characterization techniques; however, methodology for each was not frequently reported in study records. Most of the reported characterization relied on bulk characterization of EV isolates, with only 11% utilizing EV subpopulations in their experimental design. While this may be connected to a lack of available techniques suitable for clinical implementation, it also highlights the opportunity for use of EV subpopulations to improve translational efforts. As academic research identifies more chemically distinct subpopulations and technologies for their enrichment, we forecast to more refined EV trials in the near future. This review emphasizes the need for meticulous methodological reporting and consideration of EV subpopulations to enhance the translational success of EV-based interventions, pointing towards a paradigm shift in personalized medicine.

This document describes performance measures for heart failure that are appropriate for public reporting or pay-for-performance programs and is meant to serve as a focused update of the "2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures." The new performance measures are taken from the "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines" and are selected from the strongest recommendations (Class 1 or Class 3). In contrast, quality measures may not have as much evidence base and generally comprise metrics that might be useful for clinicians and health care organizations for quality improvement but are not yet appropriate for public reporting or pay-for-performance programs. New performance measures include optimal blood pressure control in patients with heart failure with preserved ejection fraction, the use of sodium-glucose cotransporter-2 inhibitors for patients with heart failure with reduced ejection fraction, and the use of guideline-directed medical therapy in hospitalized patients. New quality measures include the use of sodium-glucose cotransporter-2 inhibitors in patients with heart failure with mildly reduced and preserved ejection fraction, the optimization of guideline-directed medical therapy prior to intervention for chronic secondary severe mitral regurgitation, continuation of guideline-directed medical therapy for patients with heart failure with improved ejection fraction, identifying both known risks for cardiovascular disease and social determinants of health, patient-centered counseling regarding contraception and pregnancy risks for individuals with cardiomyopathy, and the need for a monoclonal protein screen to exclude light chain amyloidosis when interpreting a bone scintigraphy scan assessing for transthyretin cardiac amyloidosis.

This document describes performance measures for heart failure that are appropriate for public reporting or pay-for-performance programs and is meant to serve as a focused update of the "2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures." The new performance measures are taken from the "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines" and are selected from the strongest recommendations (Class 1 or Class 3). In contrast, quality measures may not have as much evidence base and generally comprise metrics that might be useful for clinicians and health care organizations for quality improvement but are not yet appropriate for public reporting or pay-for-performance programs. New performance measures include optimal blood pressure control in patients with heart failure with preserved ejection fraction, the use of sodium-glucose cotransporter-2 inhibitors for patients with heart failure with reduced ejection fraction, and the use of guideline-directed medical therapy in hospitalized patients. New quality measures include the use of sodium-glucose cotransporter-2 inhibitors in patients with heart failure with mildly reduced and preserved ejection fraction, the optimization of guideline-directed medical therapy prior to intervention for chronic secondary severe mitral regurgitation, continuation of guideline-directed medical therapy for patients with heart failure with improved ejection fraction, identifying both known risks for cardiovascular disease and social determinants of health, patient-centered counseling regarding contraception and pregnancy risks for individuals with cardiomyopathy, and the need for a monoclonal protein screen to exclude light chain amyloidosis when interpreting a bone scintigraphy scan assessing for transthyretin cardiac amyloidosis.

While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are provided in an attempt to identify emerging themes and discuss their implications for education in the 21st century. Affordances of (using) AI in Education (AIEd) and possible adverse effects are identified and discussed which emerge from the narratives. It is argued that now is the best of times to define human vs AI contribution to education because AI can accomplish more and more educational activities that used to be the prerogative of human educators. Therefore, it is imperative to rethink the respective roles of technology and human educators in education with a future-oriented mindset.