Content Areas Research Articles

The Socratic Method in Leadership Positions: Teaching, Psychotherapy and Supervision

Leadership can play an important role in classroom teaching, psychotherapy sessions and supervisory meetings. Recent work on the Socratic method has identified useful strategies derived from an integration of ancient philosophy and contemporary psychology. The nine core elements of the Socratic method can be organized into process and content. The five process elements include the use of systematic questioning, inductive reasoning, a disavowal of knowledge, guided discovery, and brief sequences. The four content areas include a focus on universal definitions, self-Improvement, virtue ethics, and core beliefs. Finally, the Socratic method has been useful for leadership skills in three different areas: classroom teaching, psychotherapy sessions, and supervisory meetings. Each leadership style will be discussed long with a metaphor to help clarify the Socratic style of leadership.

Startup Design of Biomass Gasification Reactors

As a fundamental step for open and closed-loop design and operation, the problem of designing the initial temperature profile for the startup operation of a spatially distributed throated gasifier (described by 10 to 20 nonlinear ordinary and partial differential equations) so that the high energetic yield steadystate is robustly reached is addressed. The problem is solved with efficient partial-to-ordinary differential equation discretization and approximation of the initial torch-induced temperature profile with a rectangular one with: (i) the same sensible heat content (area) as the torch one, and (ii) the pulse start-endheight triplet as design degree of freedom. A sampled search yields the start-end-height triplet that describes the experimental data and explains the manufacturer’s specifications and operation guide, systematizing (with scalability) the startup operation.

#Opioids: A Mixed Methods Examination of Top Opioid-Related Content on TikTok.

Despite an abundance of public discourse about the opioid crisis in the media, there is little research characterizing opioid-related content on TikTok, a popular video-based social media platform. This study sought to examine how opioids are portrayed on TikTok. This study used mixed-methods to analyze top opioid-related posts marked with the hashtag "#opioids" collected in May 2023. Holistic coding was used to topically categorize multimedia content in posts and to quantify the frequency of mentioning opioid-related content areas (eg. overdose, pain, fentanyl). Template analysis methods were then used to develop themes. 115 posts were analyzed. The most frequently used opioid-related topic codes include prescription opioids (58.3% of posts), pain (47.0%), overdose (35.7%), and fentanyl (34.8%). Posts were most commonly about challenges to accessing prescription opioids for pain management (37.4%), opioid policy (36.5%), and negative consequences of using opioids (32.2%). Qualitative analysis yielded themes about the potential dangers associated with using opioids, treatment and recovery from opioid use disorder, and barriers to obtaining prescription opioids for pain management. This study revealed polarizing opinions within opioid-related content on TikTok. The two main stances, dangers of non-medical opioid use and advocacy for availability of prescription opioids for pain management, represent nationwide tensions between the opioid and chronic pain crises. The vast audience TikTok garners presents an opportunity for disseminating opioid education, harm reduction strategies, and opioid use disorder treatment options that were largely absent among the posts analyzed.

Challenges In Designing A Business English Course

The paper presents the Business English course at the University of Zadar, focusing on teachers’ observations regarding the suitability of the course materials and possible improvements. Recent literature considers the customization and alignment of such materials with content area topics to be highly beneficial. Consequently, the aim of this paper is to explore and propose an alternative approach to course material development for a Business English course that aligns more closely with specific business content areas and provides current, relevant topics reflecting recent developments in the field. The methodology incorporates teachers' classroom experiences, highlighting the need for up-to-date materials in Business English as a prominent teaching issue. The coursebook is reassessed, and relevant literature on authentic material development is examined. Finally, an exemplary Business English lesson is designed for first-year Management students, utilizing authentic materials and supplemented with interactive tasks in an e-course. During this process, advice is sought from the content area teacher to ensure coordination between lesson content and topic relevance. This type of customized course material is expected to positively impact students’ motivation and enhance their classroom participation by bringing real-world business situations into the classroom.

Hyperspectral Remote Sensing Estimation of Rice Canopy LAI and LCC by UAV Coupled RTM and Machine Learning

Leaf chlorophyll content (LCC) and leaf area index (LAI) are crucial for rice growth and development, serving as key parameters for assessing nutritional status, growth, water management, and yield prediction. This study introduces a novel canopy radiative transfer model (RTM) by coupling the radiation transfer model for rice leaves (RPIOSL) and unified BRDF model (UBM) models, comparing its simulated canopy hyperspectra with those from the PROSAIL model. Characteristic wavelengths were extracted using Sobol sensitivity analysis and competitive adaptive reweighted sampling methods. Using these wavelengths, rice phenotype estimation models were constructed with back propagation neural network (BPNN), extreme learning machine (ELM), and broad learning system (BLS) methods. The results indicate that the RPIOSL-UBM model’s hyperspectra closely match measured data in the 500–650 nm and 750–1000 nm ranges, reducing the root mean square error (RMSE) by 0.0359 compared to the PROSAIL model. The ELM-based models using the RPIOSL-UBM dataset proved most effective for estimating the LAI and LCC, with RMSE values of 0.6357 and 6.0101 μg · cm−2, respectively. These values show significant improvements over the PROSAIL dataset models, with RMSE reductions of 0.1076 and 6.3297 μg · cm−2, respectively. The findings demonstrate that the proposed model can effectively estimate rice phenotypic parameters from UAV-measured hyperspectral data, offering a new approach to assess rice nutritional status and enhance cultivation efficiency and yield. This study underscores the potential of advanced modeling techniques in precision agriculture.

Functional responses of Mediterranean flora to fire: A community‐scale perspective

Abstract Fire regime is predicted to change, particularly in Mediterranean climate regions, towards more severe and frequent fire events. From a predictive perspective, trait‐based ecology offers a comprehensive framework to characterize vegetation responses to fire. Since fires induce erosion and decrease soil nutrients, species' functional traits and their distribution at community level should reflect these changes. Despite a vast literature focused on plant traits involved in resistance to fire, quantification of community trait responses to fire is lacking, particularly for traits that are linked to resource strategies. Here, we emphasis on plant traits related to morphology (height, specific leaf area, stem and wood density) and resource acquisition strategies (leaf nitrogen, leaf dry mass, seed dry mass). We compiled three different databases compiling vegetation, fire and functional traits for the flora of Southern France. We analysed the relationships between these three components at both species and community levels. Fire numbers and area burnt did not impact species trait distributions. At community level, a clear pattern emerged between the number of fires and the distribution of different traits considered, with two main axes: on the positive PC2 axis vegetative height and seed mass; and on negative PC1 axis leaf carbon and positive PC1 axis nitrogen content and leaf area. We also showed that vegetative height is positively correlated to the aridity index distribution in the region studied. Synthesis: We analysed the relationships among fire, vegetation and functional traits, at both species and community levels. Altogether, there are highly significant direct relationships between the number of fires and leaf area (negatively) as well as seed mass (positively). For woody communities, wood density is also highly positively significant related to the number of fires. Overall, these findings suggest that fire may have an important impact on the functional response of plant communities, while not apparent when looking at individual species. Further, this research paves new ground to better understand the mechanisms behind trait convergence and the way plant communities respond to different environmental pressures.

Sprach- und Sprachmittlungskompetenz in Translationswissenschaft und Sprachdidaktik

In this article, I will compare the concept of mediation competence, its modelling and its relationship to language competence in Translation Studies and Language Teaching. While competence modelling has a long tradition in Translation Studies and focuses on describing the competences of professional translators (often opposed to bilinguals’ competence), mediation is a relatively new concept in Language Teaching, which was put on the map in the CEFR 2001. For my analysis, I will first describe areas of interest and relevant models in each discipline and then analyse the overlaps and differences as well as areas of contention.

Estimating Tetrachloroethene Sorption Coefficients Based on Soil Properties in Organic-Poor Soils

In the context of contaminated site remediation, the fate of chlorinated solvents in the subsurface and subsequent groundwater contamination is influenced by soil properties governing sorption. The solid–water distribution coefficient (Kd) is a key parameter for modeling contaminant distribution and transport, essential for risk assessment and remediation planning. This study evaluated tetrachloroethene sorption isotherms in 34 low-organic-carbon soils from the Czech Republic, assessing the influence of soil properties on Kd. Soil samples exhibited variability in organic carbon content (˂0.05–0.81%), with clay ranging from 0% to 64.9%, silt 5.1% to 71.2%, and sand 5.2% to 88.9%, specific surface area (0.41–64.39 m2 g−1), particle density (2.05–4.09 g cm−3), and porosity (43.5–67.3%). Batch experiments were conducted using standard procedures, with Kd values ranging from 0.379 to 2.272 L kg−1. Statistical analysis grouped the soils into three textural classes: sandy, clayey fine, and silty loam. The findings reveal that organic carbon content and specific surface area are the primary predictors of Kd, while clay and sand also play a significant role in shaping sorption behavior. Multivariate regression models explained 63.6% to 98.5% of Kd variability with high accuracy, as indicated by low root means square error (0.070–0.329) and mean absolute percentage error (3.8–28.8%) values. These models offer reliable predictions of sorption behavior, providing valuable tools for risk assessment and remediation strategies.

Pirfenidone Downregulates eIF6, P311, and TGF-β Expression and Improves Liver Fibrosis Induced by Bile Duct Ligation in Wistar Rats: Evidence for Liver Regeneration.

Liver fibrosis (LF) is a clinical disorder characterized by inflammation and excessive accumulation of extracellular matrix (ECM). This study investigates the effects of the antifibrotic compound pirfenidone (PFD) on improving LF through histological changes and modulation of eukaryotic translation initiation factor 6 (eIF6), P311, and transforming growth factor beta (TGF-β) in rats with bile duct ligation (BDL)-induced LF. Rats received daily doses of PFD (200 and 500 mg/kg) for 4 weeks. The study encompassed biochemical, pathological, and immunohistochemical (IHC) analyses. mRNA levels of eIF6, P311, TGF-β, ECM deposition, hepatic stellate cell (HSC) activation, and inflammatory mediator genes were measured by RT-qPCR. Protein levels of eIF6, P311, and TGF-β were detected by western blotting. Compared with the BDL group, PFD dose-dependently reduced hydroxyproline content, liver index, biochemical parameters, fibrosis score, and fibrosis area. PFD also modulated BDL-induced hepatic inflammation, ECM accumulation, and HSC activation. IHC staining of Ki-67 and hepatocyte paraffin-1 revealed that PFD enhanced liver regeneration. The research confirmed that PFD gradually downregulated elevated eIF6, P311, and TGF-β levels in BDL-induced LF. These findings suggest that PFD could be a potential treatment for LF, as it may help attenuate fibrosis and enhance liver regeneration, possibly through the modulation of these specific markers.

Effect of growth media and plant growth promoting rhizobacteria (PGPR) on growth and flowering indices of China Aster

Our work focused on applying different growth media and plant growth promoting rhizobacteria (PGPR) treatments on growth parameters of China Aster as a worldwide ornamental plant. This plant has many uses such as medicinal plant, seasonal and cut flower and green spaces or landscaping. The treatments included four types of growth media (soil (S), soil+perlite (SP), soil+cocopeat (SC) and soil+cocopeat +perlite (SCP)) and three types of incubation status included incubation with plant growth promoting rhizobacteria (PGPR) of Bacillus subtilis (B.subtilis) and Pseudomonas putida (P.putida), and no-bacterial incubation with three replicates. Regardless of growth media, P.putida had greater plant height than B.subtilis. SCP with or without bacterial incubation had the highest plant height and numbers of axillary shoots among the applied growth media. SCP with P.putida had the greatest chlorophyll content (1.29 mg.g-1 FW) and leaf area (1495.05 mm2). SCP with or without bacterial incubation had the highest number and diameters of flowers among other treatments. SCP plus P.putida showed maximum leaf nitrogen (N), SC and SP plus B.subtilis had highest leaf phosphorous (P) and potassium (K), respectively. Our results demonstrated that applying SCP as a compound growth media, with or without bacterial incubation, had best effects on growth and flowering indices.

Environmental determinants of intraspecific variation in five functional traits of Pinus yunnanensis Franch.

Pinus yunnanensis Franch. is a native species in southwestern China, characterized by high polymorphism. However, the environmental drivers of intraspecific variation in its functional traits remain poorly understood. In this study, we examined the relationships between five functional traits (bark thickness, tree height, leaf dry matter content, leaf length, and specific leaf area) and habitat conditions across 20 populations, representing three varieties: var. yunnanensis (the original variety), var. pygmaea, and var. tenuifolia. Our experiments aimed to determine whether the functional traits varied among the three varieties under different environmental conditions. As specific leaf area and leaf dry matter content showed no significant correlations with any environmental factors, we focused our analysis on the remaining three traits. Using random forest models, we assessed the significance of each environmental factor and found the following: Temperature seasonality was a key determinant of tree height; soil particle size (clay and sand) had the strongest influence on bark thickness; and for leaf length, precipitation during the driest quarter was the most important factor. These findings offer insights into the variation in functional traits of P. yunnanensis and enhance our understanding of its adaptation to diverse environments.

ChatGPT in foreign language lesson plan creation: Trends, variability, and historical biases

Abstract The advent of generative artificial intelligence (AI) models holds potential for aiding teachers in the generation of pedagogical materials. However, numerous knowledge gaps concerning the behavior of these models obfuscate the generation of research-informed guidance for their effective usage. Here, we assess trends in prompt specificity, variability, and weaknesses in foreign language teacher lesson plans generated by zero-shot prompting in ChatGPT. Iterating a series of prompts that increased in complexity, we found that output lesson plans were generally high quality, though additional context and specificity to a prompt did not guarantee a concomitant increase in quality. Additionally, we observed extreme cases of variability in outputs generated by the same prompt. In many cases, this variability reflected a conflict between outdated (e.g. reciting scripted dialogues) and more current research-based pedagogical practices (e.g. a focus on communication). These results suggest that the training of generative AI models on classic texts concerning pedagogical practices may bias generated content toward teaching practices that have been long refuted by research. Collectively, our results offer immediate translational implications for practicing and training foreign language teachers on the use of AI tools. More broadly, these findings highlight trends in generative AI output that have implications for the development of pedagogical materials across a diversity of content areas.

Building Math Skills with Computational Thinking

This elementary math intervention lesson plan integrates computational thinking (CT) and generative AI tools, focusing on addition strategies. It combines tech-enhanced experiences with hands-on activities to develop CT skills and content knowledge. This three-part lesson includes reviewing addition facts, engaging in interactive games, and creating digital content. Students practice pattern recognition, abstraction, problem decomposition, and step-by-step solution development. The plan emphasizes CT connections, engagement, and deepening understanding of addition strategies. This adaptable, multimedia approach offers a comprehensive learning experience blending traditional math instruction with modern tech tools across various grade levels and content areas.

Computational Thinking in Undergraduate Pre-Service Special Education Programs

In the 21st century, an increased emphasis on integrating computational literacy within classrooms occurred (Bouck & Yadav, 2020). This learning representation aims to equip preservice special education teachers (PSSETs) with tools to deliver inclusive computational thinking (CT) and computer science (CS) instruction, fostering an understanding of CT/CS concepts and promotes integration across content areas. This technology-rich learning representation employs robots, interactive whiteboards, and a blend of unplugged and plugged CT activities to demonstrate how CT can be integrated into a PK-12 classroom. This learning representation concludes with an assessment tasking PSSETs to create an activity integrating CT. This approach prepares PSSETs to provide equitable and accessible CT/CS education, aligning with current educational priorities.

Exploring the impact of form and content feedback on EFL writing proficiency: A quasi-experimental study

With process-oriented approaches becoming the norm in writing classes, teacher-written feedback has gained significance in teaching, learning, and educational research. As a result, writing instructors dedicate a considerable amount of time to providing feedback. However, research on the impact of written feedback from teachers has produced inconsistent findings regarding its effectiveness. The primary objective of this study is to examine the effects of feedback targeting form and content on the writing proficiency of English as a Foreign Language (EFL) students in areas of content, organisation, vocabulary, grammar, and mechanics. For this study, we used a quasi-experimental design. We formed two groups: an experimental group that received feedback focused on content and a control group that received feedback focused on form. We collected both qualitative and quantitative data through writing tests as well as semi-structured interviews. The results showed significant improvement in writing for both groups. Qualitative analysis revealed that students still view grammar as important, strive for accuracy, and may resist feedback regarding the communication of information in their writing.

Transforming secondary teacher preparation for multilingual learners through translanguaging: Toward an integrated biliteracy and disciplinary learning framework

AbstractStudents designated as English learners and the broader group of multilingual learners continue to face restrictive learning environments in secondary classrooms despite existing research that demonstrates how integrating literacy development with authentic and relevant disciplinary learning benefits multilingual learners and all students. To address this issue, an interdisciplinary team of biliteracy and secondary content method scholars and teacher educators used funding through the U.S. Department of Education's National Professional Development Program to (1) articulate a cohesive framework that integrates biliteracy with disciplinary learning through research‐based instructional practices and (2) explore how English, math, and science secondary content method instructors apply this framework when working with preservice teachers. The researchers connected translanguaging pedagogy, content and language/literacy integrated approaches, and a practice‐based teacher education model to develop the Biliteracy and Content Area Integrated Preparation (BCAIP) Framework. They found that participating content area secondary method instructors made progress toward applying the BCAIP framework by building upon what they already do in support of diverse learners (i.e., foundational pedagogies) as they shifted toward biliteracy‐oriented pedagogy. The authors argue that situating translanguaging in a disciplinary learning context better positions secondary teacher educators to transform how they prepare preservice teachers to serve multilingual learners.

A Robust joint coverless image steganography scheme based on two independent modules

With the development of deep learning technology, great progress has been made in the field of coverless steganography based on deep learning technology, including some selection-based steganography methods that use deep learning technology and all generation-based steganography methods, however both of which have their limitations. The former is difficult to meet actual communication requirements in terms of communication capacity and completeness due to the limit of the algorithm. Due to the irreversibility of the process of generating secret images from message codeword, the recovery accuracy of the latter is very poor. To this end, this paper designs a robust joint coverless image steganography scheme called Joint Coverless Image Steganography (JoCS). Firstly, this paper proposes the Semantic Factorization Fitting module (SeFF) and the Transform Domain Steganography module (TrDS). The former adds the secret message to the input vector of the low resolution layer in the StyleGAN generator network, which establishs a mapping rule between message codeword and the coarse feature of the generated image, and then the extractor is used to fit the above mapping rule, which has excellent robustness and completeness; the latter encodes the main content area of the image based on the encoder in VQGAN, and then adds secret message to the latent vector of the encoded image, which achieves the steganography in the latent domain of the image. Secondly, we demonstrate the independence between two modules and the advantages of connecting two modules. By using the image generated in the SeFF module as the cover image in the TrDS module, secondary steganography of a single image is achieved, based on which we design the JoCS scheme. The results show that our scheme breaks through the communication capacity limit in the selection-based coverless methods while guaranteeing 100% completeness, excellent image quality and outstanding robustness against various image attacks. Moreover, our scheme exhibits strong security against detection by multiple steganalysis tools and excellent practicality in practical communication. Finally, this paper also discusses the following three points as further elaboration of the scheme: (1) the advantages of the mapping rule in the SeFF module (2) the verification of the independence between the two modules (3) the flexibility of the joint steganography scheme.

Pre-service Teacher Perceptions of ChatGPT for Lesson Plan Generation

This study explores preservice education student perceptions on ChatGPT's ability to write lesson plans through the use of a guided analysis process with 59 undergraduate and graduate students enrolled in STEM, TESOL, and Social studies methods courses for grades PreK-12. A pre- post-survey and a reflection on the strengths and weaknesses of ChatGPT were written by participants. Statistically significant findings were revealed regarding student perceptions of ChatGPT's ability to write a complete lesson plan in their content area and ChatGPT's ability to write a detailed lesson plan for a substitute teacher. In both cases, students’ perceptions of ChatGPT to complete these tasks decreased after they engaged in analysis of the content. Students shared that they plan to use ChatGPT for lesson planning as a practicing educator, but indicated that revision of output is necessary. A call for future work is explored.

Teacher noticing skills in mathematics education: A meta-synthesis of recent studies

The present study examines articles published internationally from 2002 to 2023 that pertain to the skill of noticing in mathematics education. A thorough search was performed using the Web of Science and Scopus databases, focusing on article-type studies within this field. The purpose of the study was to systematically review and analyze research related to the noticing skill in mathematics education. Specifically, the study seeks to identify emerging trends, generate new research ideas, highlight underexplored areas within the field, and suggest potential research topics. The meta-synthesis method was employed to analyze various characteristics of the studies on noticing in mathematics education, including sample size, sample group, research methods, data collection tools, theoretical frameworks, content areas studied, objectives of the studies on noticing, and components of noticing. The analysis reveals that the majority of studies on teacher noticing have relied on small sample sizes and predominantly qualitative research designs, with a noticeable increase in the adoption of mixed-method approaches in recent years. The most commonly used data collection tools were video recordings and written notes, underscoring the importance of capturing real-time classroom interactions and reflective observations. The primary focus of these studies has been on teaching foundational concepts, particularly in the domain of numbers. Findings indicate that studies often integrate multiple components of noticing, reflecting a comprehensive approach to understanding how teachers observe, interpret, and respond to student behaviors. These findings indicated that researchers have diversified the field of noticing, resulting in a wide array of studies.

Transforming community-based primary health care delivery through comprehensive performance measurement and reporting: examining the influence of context

BackgroundCommunity-based primary health care represents various community-based health care (CBPHC) models that incorporate health promotion and community development to deliver first-contact health services. Learning health systems (LHSs) are essential for improving CBPHC in which feedback from relevant stakeholders is used to continuously improve health systems with the goal of achieving population health and health equity. Performance reporting is one way to present data to clinicians and decision makers to facilitate a process of reflection, participation, and collaboration among partners to improve CBPHC.MethodsOur objective was to obtain feedback on a regional CBPHC performance portrait through key informant interviews. We used purposive convenience sampling to recruit participants who were clinicians in primary care and/or decision-makers in primary care at a regional level. The performance portrait summarized results of survey questions asked of patients, providers, and primary care organizations. The portrait was organized by the 10 pillars of the Patient’s Medical Home (PMH) model. Interview questions specifically asked about portrait content, formatting, interpretability, utility, and dissemination strategies. Content analysis was used to analyze interview data.ResultsWe completed 19 interviews with key informants from the Canadian provinces of Nova Scotia (n = 8), Ontario (n = 6) and British Columbia (n = 5). We coded transcripts into four content areas: (1) Usability as influenced by content and interpretability, (2) Formatting, (3) Utility, and (4) Dissemination. Using data and reporting back to clinicians and decision-makers about how their practices and jurisdictions are performing in primary care in meaningful ways is important. Our results suggest having available methodology notes, including the analysis used to develop any scoring, sampling and sample sizes, and interpretation of the statistics is necessary.ConclusionsThis research was the first to create a comprehensive performance portrait using data driven by factors that are important to primary care partners. We obtained important feedback on the portrait in the context of usability, formatting, utility, and dissemination. This data needs to be used to provide feedback in continuous cycles to evaluate and improve CBPHC models as part of a LHS.