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Purpose: Utilizing social constructivist learning theory and a conceptual framework for Social and Emotional Learning (SEL), this self-study explores how I as a teacher-researcher intentionally evolved my approach to teaching SEL in a high school Physical Education setting. Method: Data were collected over twenty 75-min lessons over 15 weeks. One critical friend interview, 20 postteaching reflections, 18 observations, and 22 journal entries were conducted. A deductive and inductive approach utilizing the Miles, Huberman, and Saldana Framework for Qualitative Data Analysis was implemented. Results: Findings demonstrate how aligning my teaching with a contemporary framework led to a more explicit and intentional focus on SEL within my already utilized repertoire of pedagogies. Discussion/Conclusion: Incorporating self-study structure as a teacher-researcher led me to understand how I evolved and felt better equipped to teach for targeted SEL competencies and skills to further compliment the teaching of core Physical Education content. [ABSTRACT FROM AUTHOR]

For an academic field to remain vital, it is necessary to reflect upon its conceptual foundations and learn from adjacent disciplines. On that note, aesthetics can provide significant insights into advertising. While aesthetic elements have received attention in advertising research, no systematic attempts have been made to provide a comprehensive overview of this literature. The purpose of this conceptual article is to bring different branches of aesthetic theory into advertising studies. Marketers have historically focused on product functionality and often appeal to consumers through explicit messages. This article fills an important gap by delineating and advocating the conceptual foundation of advertising aesthetics as a research area worthy of further attention. In short, we understand advertising aesthetics as the artlike properties of and sensory responses to ads. A review of 309 papers provides the thematic outline of the study. Seven key themes are identified: (1) the nature of advertising aesthetics, (2) advertising creativity, (3) textuality, (4) social aesthetics, (5) cross-cultural differences, (6) the role of media in creating aesthetic opportunities, and (7) aesthetic categories beyond the beautiful and sublime. These themes offer a novel way of exploring contemporary issues in advertising. The article concludes with suggestions for future research. [ABSTRACT FROM AUTHOR]

We have reanalyzed the rich plethora of ground state configurations of the asymmetric Wigner bilayer system that we had recently published in a related diagram of states [Antlanger et al., Phys. Rev. Lett. 117, 118002 (2016)], comprising roughly 60 000 state points in the phase space spanned by the distance between the plates and the charge asymmetry parameter of the system. In contrast to this preceding contribution where the classification of the emerging structures was carried out "by hand," we have used for the present contribution machine learning concepts, notably based on a principal component analysis and a k-means clustering approach: using a 30-dimensional feature vector for each emerging structure (containing relevant information, such as the composition of the configuration as well as the most relevant order parameters), we were able to reanalyze these ground state configurations in a considerably more systematic and comprehensive manner than we could possibly do in the previously published classification scheme. Indeed, we were now able to identify new structures in previously unclassified regions of the parameter space and could considerably refine the previous classification scheme, thereby identifying a rich wealth of new emerging ground state configurations. Thorough consistency checks confirm the validity of the newly defined diagram of states. [ABSTRACT FROM AUTHOR]

This study sought to determine the effectiveness of utilizing game-based strategies in learning mathematics in the junior school specifically grade 10 students. In this study, embedded mixed methods research design was used to gather both quantitative and qualitative data from the participants in which the second served as supporting data to supplement the first. The results of the study revealed that game-based strategies provided a strong influence in maximizing learning mathematics and retention was also evident in the result of students' test performance allowing them to recall concepts learned and skillfully solve problems from the different activities they experienced with the use of the game-based strategies. Moreover, the participants shared meaningful experiences learning mathematics after the intervention. With the use of such strategies, they were able to recognize how lessons were discussed in a different manner with full of insights and realization that learning can be both engaging and rewarding. Moreover, the test performance result analyzed using mean showed an increasing average score indicating that the participants could still recall how to solve mathematical problems which took place after the intervention was utilized. Furthermore, results in the inferential statistics analyzed using Repeated Measures ANOVA also revealed that there were significant differences in the pretest, post-test, and retention test of the participants specifically majority on pretest and post-test, and pretest and retention test using post-hoc analysis. These results imply that with constant practice of utilizing teaching strategies like integrating games in class, it can improve learning outcomes, increase engagement, provide short-term retention, and promote pedagogical innovation. In education, these long-term knowledge and skills in mathematics will lead to higher test performance while aligning the 21st century skills essential in the success of teaching and learning. [ABSTRACT FROM AUTHOR]

An enigma for human languages is that children learn to understand words in their mother tongue extremely fast. The cognitive sciences have not been able to fully understand the mechanisms behind this highly efficient learning process. In order to provide at least a partial answer to this problem, I have developed a cognitive model of the semantics of natural language in terms of conceptual spaces. I present a background to conceptual spaces and provide a brief summary of their main features, in particular how it handles learning of concepts. I then apply the model to give a geometric account of the semantics of different word classes. In particular, I propose a “single‐domain hypotheses” for the semantics of all word classes except nouns. These hypotheses provide a partial answer to the enigma of how words are learned. Next, a dynamic cognitive model of events is introduced that replaces and extends the function of thematic roles. I apply it to analyze the meanings of different kinds of verbs. I argue that the model also explains some aspects of syntactic structure. In particular, I propose that a sentence typically refers to an event. Some further applications of conceptual spaces are briefly presented. [ABSTRACT FROM AUTHOR]

Background Aims Sample Methods Results Conclusion Learning to write the complex academic language (AL) associated with a discipline (like science) is a critical task in education, with middle school being a key developmental period. However, we need more research to guide how we assess students' learning to write AL, especially if we want to create assessment that guides more effective instruction.We evaluated middle school students' informational writing for six different measures of AL to determine which ones were most strongly related to writing quality and were most indicative of the unique features of informational writing. We also examined which metrics were sensitive to growth across middle school.Our sample consists of informational compositions from 285 students in Grade 5 (n = 175) and Grade 8 (n = 110) in a Midwestern state in the United States.Path modelling was used to determine the degree to which the AL metrics are associated with writing quality and narrativity in each grade.Overall, the six measures of AL explained 70% of the variance in students' writing quality. We found that a new measure, number of long words, outperformed other more established measures at the word level and should be used in assessment of informational writing quality. We also found that automated scores at the sentence level better detected development across middle school grade levels than typical rubrics of writing quality.Results provide promising avenues for the assessment of malleable aspects of AL in middle school informational writing. [ABSTRACT FROM AUTHOR]

To improve climate education in an introductory weather and climate course, an active-learning lab was developed around a climate decision support system. The Climate Analysis and Visualization for the Assessment of Species Status (CAnVAS) tool allows individuals to view various climate variables and select a particular location and species to analyze. Undergraduate participants used CAnVAS to answer questions about the climate data they were plotting and completed a concept map about how endangered species will be impacted by climate change. A pre- and post-assessment was also given to participants, during three separate semesters, to measure knowledge changes that may have been affiliated with the CAnVAS intervention. When CAnVAS was implemented, increases in pre-to-post-assessment performance were measured (approximately 10% in Fall 2021, 7% in Fall 2022, and 6% in Fall 2023). The concept maps revealed that on average, participants drew approximately seven relevant lines and circles. This study demonstrated the efficacy of the CAnVAS tool through a pedagogical intervention deployed in an introductory weather and climate undergraduate classroom. The results contribute to the Scholarship of Teaching and Learning literature by testing the efficacy of a decision support system within the classroom setting using the e-learning theoretical framework. [ABSTRACT FROM AUTHOR]

Vehicle re-identification (Vehicle Re-ID) aims at retrieving and tracking the specified target vehicle with multiple other cameras, which can provide help in checking violations and catching fugitives, but there are still the following problems that need to be solved urgently. First, the existing collected Vehicle Re-ID data often have low resolution and blur in local regions, so that the Vehicle Re-ID algorithm cannot accurately extract subtle feature representations. In addition, small features are easy to cause the disappearance of features under the operation of a large convolution kernel, which makes the model unable to capture and learn subtle features, resulting in inaccurate judgment of vehicles. In this study, we propose a Vehicle Re-ID method based on super resolution and pyramidal convolution residual network. Firstly, a super-resolution image generation network leveraging generative adversarial networks (GANs) is proposed. This network employs both content loss and adversarial loss as optimization criteria, ensuring an efficient transformation from a low-resolution image into a super-resolution counterpart, while meticulously preserving intricate high-frequency details. Then, multi levels of pyramidal convolution operations are designed to generate multi-scale features, which can capture information on different scales. Moreover, the concept of residual learning is applied between the multi levels of pyramidal convolution operations to expedite model optimization and enhance recognition capabilities. Ultimately, the double pyramidal convolutions are meticulously employed on both the original image and the super-resolution image, yielding low-noise feature representations and intricate semantic information respectively. By seamlessly fusing these two diverse sources of information, the resultant combined features exhibit heightened discrimination capabilities and significantly bolster the robustness of image features. In order to verify the effectiveness of the proposed method, extensive experiments are carried out on VeRi-776 and VehicleID datasets. The experimental results show that the method proposed in this paper effectively captures the detail information of vehicle images, accurately distinguishes the subtle differences between different vehicles of the same type, and is superior to state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This study addresses the gap in the literature in terms of the lack of guidelines for organisations that would like to use social media to facilitate organisational learning (OL). This study presents an overarching conceptual theoretical framework that can assist organisations in integrating social media and OL. The framework helped explore at what level and what type of OL occurred from employees' use of social media in organisations. The study used the interpretive research philosophy/paradigm, inductive approach and case studies to determine how employees use Web 2.0 tools in organisations and how that use leads to OL. The data were collected using semi-structured, in-depth interviews with three different companies and seven industry experts. The research findings were used to develop a conceptual theoretical framework with key concepts that explain how the use of social media could facilitate OL. The conceptual theoretical framework was tested and reviewed by experts. This resulted in a significant contribution to existing theory by offering guidelines on how organisations could use social media to facilitate effective OL. [ABSTRACT FROM AUTHOR]

This study used a quasirandomized within-classroom design to investigate whether prior knowledge about physics gained in elementary school prepares students for future learning in related content areas in secondary school. A total of 433 children (intervention group) received four basic curriculum units on physics from their elementary school teachers. The units dealt with floating and sinking, air and atmospheric pressure, the stability of bridges, and sound and the spreading of sound. These children entered 60 newly composed classes in early secondary school that completed an advanced curriculum unit on hydrostatic pressure and buoyancy force with their secondary school teachers. A total of 942 students (control group) in these classes had not received the four basic physics curriculum units. On a conceptual knowledge test about hydrostatic pressure and buoyancy force, the intervention group outperformed the control group in the pretest (d = 0.28) and in the posttest (d = 0.25). Students in the intervention group showed similar learning gains as those in the control group, but when controlling for pretest performance, they achieved higher learning outcomes. Regression analyses within the intervention group revealed that this advantage resulted from the content-specific transfer of conceptual knowledge from topically related basic curriculum units. The basic physics instruction also prepared male and female students equally for future learning. Educational Impact and Implications Statement: Our study shows that students who have received early physics instruction in elementary school benefit slightly more from later, more advanced physics instruction in secondary school. This finding provides first evidence that the idea of a spiral curriculum, in which learners first build basic knowledge that is later on expanded in more demanding instruction, can work, although it is yet to be further examined how this process can be optimized in school instruction. [ABSTRACT FROM AUTHOR]

A central goal of education is to provide students with knowledge they: (a) can successfully apply within the domain of learning and (b) can transfer, as appropriate, to new and different domains. Yet, much research has shown that learners frequently fail to access and use applicable stored knowledge when the circumstances at retrieval differ from those at encoding. Recent laboratory studies have revealed that encoding instances of a concept as members of a relational category considerably attenuates such failures of access. In the present work, we evaluate the efficacy of one such technique (category construction) applied in conjunction with direct instruction in the authentic educational setting of middle-school classrooms. Across two experiments, category construction is evaluated relative to a standard classroom practice of a worksheet with comprehension questions in order to assess how well each promotes mastery and transfer of a target concept. In addition, potential supports to improve learning outcomes are assessed: practice with category construction (Experiment 1) and partial precompletion of the category construction task (Experiment 2). Overall, we find favorable evidence that category construction leads to greater sensitivity to the underlying conceptual structure of targeted concepts and delivers transfer advantages over a worksheet control. Educational Impact and Implications Statement: A key goal of education is not only to support mastery of complex content but also to enable students to access and apply what has been learned to new settings and domains. Results from multiple inclass experiments show that supporting initial learning through category construction can enhance performance relative to a control group on assessments of mastery and transfer. This work highlights a lightweight classroom activity that could be implemented broadly to enhance educational outcomes. [ABSTRACT FROM AUTHOR]

Forty-five years ago, Patrick Wall published his John J Bonica lecture “On the relation of injury to pain.” In this lecture, he argued that pain is better classified as an awareness of a need-state than as a sensation. This need state, he argued, serves more to promote healing than to avoid injury. Here I reframe Wall’s prescient proposal to pain in early life and propose a set of different need states that are triggered when injury occurs in infancy. This paper, and my own accompanying Bonica lecture, is dedicated to his memory and to his unique contribution to the neuroscience of pain. The IASP definition of pain includes a key statement, “through their life experiences, individuals learn the concept of pain.” But the relation between injury and pain is not fixed from birth. In early life, the links between nociception (the sense) and pain (the need state) are very different from those of adults, although no less important. I propose that injury evokes three pain need states in infancy, all of which depend on the state of maturity of the central nervous system: (1) the need to attract maternal help; (2) the need to learn the concept of pain; and (3) the need to maintain healthy activity dependent brain development. [ABSTRACT FROM AUTHOR]

Concept-cognitive learning (CCL) has been an active topic in artificial intelligence and cognitive computing. Two-way concept-cognitive learning (TCCL), an efficient cognitive mechanism to discover knowledge from an arbitrary information granule, has attracted attention to the problems of concept learning. Although TCCL has been widely adopted for cognitive and learning concepts, the existing studies still have some issues: learning concepts can only from the standard formal context, i.e., extent with discrete information, and ignoring the fuzziness of object information that is also important to precise cognitive and learning concepts. Hence, this paper proposes a novel L-fuzzy concept learning method via two-way concept-cognitive learning and fuzzy residual implication, namely, L-fuzzy concept-cognitive learning (LF-CCL). Specifically, we give the theoretical underpinnings of the L-fuzzy CCL method and a pair of dual cognitive operators are presented based on residual implication. Then L-fuzzy two-way granule spaces are constructed to explore the transformation of information granules and the generation of knowledge granules from arbitrary cognitive clues. Meanwhile, we analyze the CCL progress using L-fuzzy operators based on fixed points. Moreover, the corresponding algorithms are designed, and the decision value of this method in financial investment applications is explored through experimental analysis. Finally, numerical experiments verify the effectiveness and flexibility of the proposed method. [ABSTRACT FROM AUTHOR]

Pathology is a subject which demands deep understanding of the fundamentals. This entails regular reading, discussion, viewing the organs and slides to understand the evolution of the disease. For a sound understanding of the subject a robust clinicopathological correlation is a must. However, quite frequently students resort to rote learning of the concepts which over time leads to losing interest in the subject. In this pandemic induced circumstance, the challenge had suddenly increased. We embarked on this project with an aim to compare the effectiveness of the traditional didactic lecture (DL), Online web base learning which is the E learning (EL) and a mix of voice annotated/ audio video presentation followed by interactive large group discussion on the topic , which is a Blended learning (BL) and come to the best possible Teaching-Learning Method (TLM). 124 second year MBBS students participated in the study, of which 41 participated in the DL group, 42 were in EL group and 41 were in BL group. They were taught a topic on alcoholic liver disease. There was significant improvement in the scholastic performance of the BL group. The BL group perceived this method as more interesting and interactive. The study highlights the advantage of BL over EL and DL as the former provides an all round understanding and transforms the learning experience of the students. [ABSTRACT FROM AUTHOR]

In order to promote deep learning in physical education for students, guided by the concept of deep learning, the author integrates the concept of deep learning into flipped classrooms. The author proposes a flipped classroom design and classroom implementation process for promoting deep learning, and conducts a semester long experimental research based on basketball courses, continuously optimizing the design during this period. Through the analysis of various parameters appearing in the operation, the test results are satisfactory. The study found that students in three classes were physically trained by using the classroom teaching method of "deep learning". The classroom teaching mode based on deep learning achieved the best teaching results in the first stage. One habit that inspires real emotion in children is their pace: running in different directions. Classroom teaching based on deep learning can make students understand the importance of cross-movement. Thus, after experiment, there was no significant difference between the flipped classes and the traditional class teaching method in the cross run compared to before experiment. The effectiveness of flipped classroom design for promoting deep learning has been verified, achieving a promoting effect on students' deep learning. The flipped classroom designed by this research institute can effectively promote learners to achieve deep learning, specifically manifested as: The physical fitness level of students has improved, the level of cognitive structure has improved, and students are more able to learn independently. The goal of deep learning for students has been achieved. [ABSTRACT FROM AUTHOR]

Research-based practical applications are becoming increasingly important in providing valuable solutions to the challenges facing the construction industry. In this paper, we present a teaching concept that was implemented and evaluated in four courses, addressing the development of future-proof academic skills, particularly scientific working skills, in the field of civil engineering. The first evaluation results from a survey among the students who participated in the four courses are presented on the extent to which project-based and researchbased learning promote domain competences, planning, and study skills. The results indicate that, especially in master's degree courses, future skills are improved by paper-based learning. Additionally, student motivation increases due to the boost in creativity and group work facilitated by the teaching concept. On the other hand, the results suggest that guidelines are necessary to implement paper-based learning, especially in bachelor's degree courses. Furthermore, it is crucial that future-proof academic skills are relevant for success in the practical working context. [ABSTRACT FROM AUTHOR]

Advanced diagnostic methods are necessary for the prompt and reliable identification of tuberculosis (TB), which continues to be a worldwide health problem. Globally, there were projected to be 10 million new cases of tuberculosis in 2021, of which 9.8 million affected adults and 0.2 million children. About 15% of fatalities worldwide are attributable to tuberculosis (1.5 million deaths for every 10 million infections). To create a reliable model for tuberculosis (TB) identification using chest X‐ray pictures, we use deep learning approaches in this work, namely Convolutional Neural Networks (CNNs) and a combination of transfer learning and hyperparameter tuning. The dataset provides a varied selection of 3500 normal and 700 TB‐infected patients. It consists of 4200 photos that were obtained from the "Tuberculosis (TB) Chest X‐ray Database" on Kaggle. By utilizing the benefits of a trained model, the suggested methodological approach incorporates transfer learning. To maximize the performance of the suggested model, hyperparameter adjustment is also used. Using the VGG19 pre‐trained neural network, the model design is based on the concepts of transfer learning. The architecture makes use of task‐specific layers, regularization methods, and deliberate layer freezing to enable sophisticated categorization. Training and assessment stages demonstrate encouraging outcomes, with an accuracy of almost 98% attained on a different test dataset. A more thorough examination highlights the need for caution when interpreting high accuracy, nevertheless, by highlighting possible difficulties. [ABSTRACT FROM AUTHOR]

This study aims to explore the perceptions of elementary mathematics teachers regarding assessment for learning (AfL). The participants of this study included three elementary mathematics teachers, each with over 5 years of teaching experience at Sukkur IBA community colleges and schools in Sindh, Pakistan. These participants were selected using purposive sampling techniques. A qualitative exploratory case study research approach was used, with data collected through semi-structured interviews and observations. To ensure the trustworthiness of the study, the interview guide and observation checklist were reviewed by experts. The data were analyzed using thematic analysis. The findings of this study revealed that teachers had a limited understanding of the concept of assessment for learning. Based on these results, the study recommends several measures: the initiation of an assessment literacy program, an increase in class time, reducing the number of students per class, using moveable chairs to enhance classroom flexibility, and making amendments to the assessment policy. [ABSTRACT FROM AUTHOR]

The medical world carries a major burden in terms of specialized human resource and infrastructure. The recent COVID-19 pandemics revealed an urgent need for specialized medical professionals in order to preempt future natural disasters. The aim of this review was to underline the best teaching model for training specialist nurses. Thus, the healthcare systems should work along with national agencies for designing and implementing complex curricula for training specialists in providing healthcare such as specialist nurses or advanced practice nurses involved in the decision-making process. The educational process for these nurses should be based on an international standard involving digital education techniques such as e-learning platform, interactive approaches of the course content, as well as an interactive teaching system based on figures, graphics or videos. Moreover, virtual reality based-medical models should also represent an important aspect of the training program in order to provide the future students with the opportunity to deal with real-life medical situations in advance. These techniques will formthe basis of the specialist nurses' up-skilling process resulting in crucial life savior medical competences. The trainers should embrace their new roles in the educational process being aware that the nowadays teaching concept is no longer based on a governance approach, but they should rather mediate, guide and organize the educational process becoming shadow partners of their students in achieving the desired skills. The assessment of the students should also comply to the digitalization process by including novel evaluation techniques such as quizzes, individual and team assignments, objective structured clinical examination in order to objectively mirror the student's progress during the training program. Therefore, this review synthetized current insights in learning and training techniques that should be implemented for addressing the needs of innovation in medical education. [ABSTRACT FROM AUTHOR]

AbstractThis paper explores personal and professional development (PPD) as a key learning domain for the future of medical education and person-centered care. Guided by existing curriculum development models and lessons learned in practice, scenarios from academic and clinical learning environments will guide a theory-driven discussion of concepts and competencies that humanize the practice of medicine, such as emotional intelligence, professional identity formation, lifelong learning and inclusive practice. Factors contributing to contemporary curriculum implementation will be informed by a case study of a PPD program delivered to post-graduate medical students in Australia and propose an action-focused series of next steps to connect past, current and future directions for medical schools and graduates. Through reflections on iterative stages of program development and the incorporation of emerging concepts in PPD, this paper advocates for the true valuing of personal growth and professional development in medical education. If future doctors are to graduate as compassionate, socially informed, and critically reflective practitioners, they need dedicated PPD learning, opportunities to practice and active encouragement to remain curious towards and beyond their own experience. [ABSTRACT FROM AUTHOR]

Over the past decade, deep learning has become the leading approach for various computer vision tasks and decision support systems. However, the opaque nature of deep learning models raises significant concerns about their fairness, reliability, and the underlying inferences they make. Many existing methods attempt to approximate the relationship between low-level input features and outcomes. However, humans tend to understand and reason based on high-level concepts rather than low-level input features. To bridge this gap, several concept-based interpretable methods have been developed. Most of these methods compute the importance of each discovered concept for a specific class. However, they often fail to provide local explanations. Additionally, these approaches typically rely on labeled concepts or learn directly from datasets, leading to the extraction of irrelevant concepts. They also tend to overlook the potential of these concepts to interpret model predictions effectively. This research proposes a two-stream model called the Cross-Attentional Fast/Slow Thinking Network (CA-SoftNet) to address these issues. The model is inspired by dual-process theory and integrates two key components: a shallow convolutional neural network (sCNN) as System-I for rapid, implicit pattern recognition and a cross-attentional concept memory network as System-II for transparent, controllable, and logical reasoning. Our evaluation across diverse datasets demonstrates the model's competitive accuracy, achieving 85.6%, 83.7%, 93.6%, and 90.3% on CUB 200-2011, Stanford Cars, ISIC 2016, and ISIC 2017, respectively. This performance outperforms existing interpretable models and is comparable to non-interpretable counterparts. Furthermore, our novel concept extraction method facilitates identifying and selecting salient concepts. These concepts are then used to generate concept-based local explanations that align with human thinking. Additionally, the model's ability to share similar concepts across distinct classes, such as in fine-grained classification, enhances its scalability for large datasets. This feature also induces human-like cognition and reasoning within the proposed framework. [ABSTRACT FROM AUTHOR]

AbstractMisconceptions in middle-school geography classes pose a considerable challenge to students' comprehension of geographical processes. Studies have indicated that numerous misconceptions exist within the student body regarding geography. Therefore, it is crucial to identify and rectify these misconceptions. To address this issue, interviews were conducted with middle-school students. A total of 155 pupils in grades five, six, and seven participated in this study. Semi-structured interviews were also conducted. Students' understanding of misconceptions was assessed using a descriptive content analysis. In general, the findings indicate that students possess various misconceptions regarding geography topics, which gradually decrease as they progress to higher grades. [ABSTRACT FROM AUTHOR]

Recent political events across the globe have illustrated a resurgence in people's intolerance to ideas different from their own. We mobilize the idea of intellectual humility to assess how extant psychological theories account for individual differences in people's tolerance for conflicting ideas. Then, we introduce concepts from the Learning Sciences to determine how alternative methodologies could augment research on intellectual humility and civic engagement. Last, we summarize these analyses by pointing to their relations with three intersecting challenges and solutions regarding studying IH in multiple contexts and with new multiple data sources. [ABSTRACT FROM AUTHOR]

Lithium‐sulfur batteries (LSBs) have attracted increasing attention in the past decades due to their great potential to the next‐generation high‐energy‐density storage systems. As important as electrodes, electrolytes that could strongly determine battery performance via component regulation have left big difficulties in clarifying their complex interactions caused by multicomponent as well as the intricate formation mechanism of passivation layers at the electrolyte‐electrode interfaces. Fortunately, machine learning (ML), which is time‐saving and highly efficient, has played an irreplaceable role in accelerating discovery, design, and optimization of novel electrochemical energy storage materials. In this concept, we summarize the complex issues present in multicomponent electrolytes and focus on optimization of electrolyte formulations based on ML in order to provide an outlook on the recent development and perspectives on LSBs from the viewpoint of high‐performance electrolytes. [ABSTRACT FROM AUTHOR]

Introduction: Musculoskeletal ultrasound (MSUS) is integral to routine clinical diagnostics for musculoskeletal and joint disorders. This study aims to establish and validate a sonography course tailored to undergraduate medical students acquiring MSUS-specific skills at a German university. Methods: A blended learning training concept, comprising 24 instruction sessions of 45 min each, was designed based on the current national guidelines of the German Society for Ultrasound in Medicine (DEGUM). This program was integrated into the clinical phase of the undergraduate students' medical education. The self-perceived improvement in competency and the effectiveness of the course design were evaluated using a a 7-point Likert scale questionnaire. Objective learning success was evaluated via a written test and a "Direct Observation of Practical Skills" practical exam. Control groups included medical students without MSUS training (control group 1) and doctors who had completed DEGUM-certified basic MSUS courses (control group 2). Both control groups completed the written test, while control group 2 also took the practical final exam. The study involved 146 participants: 56 were allocated to the study group, 44 to control group 1, and 46 to control group 2. Results: The study group rated their skills significantly higher after the course (p < 0.01). Participants expressed high satisfaction with the course design, the teaching materials, and the teachers. The study group's performance on the final written test was comparable to those of control group 2 (p = 0.06) and significantly superior to control group 1 (p < 0.001). Additionally, the study group's performance on the practical final exam was not significantly different from control group 2 (p = 0.28), with both groups achieving scores exceeding 80%. Conclusion: Both subjective and objective measures of learning suggest that an MSUS course designed for postgraduates can be effectively adapted for undergraduate medical students. Incorporating MSUS training into the clinical curriculum is recommended to enhance future medical professionals' educational experience and practical skills. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Methods Results Conclusion The objective of this study was to enhance the knowledge base of primary school children regarding earthquake preparedness through the implementation of an activity‐based earthquake awareness education program.The study was conducted as pre–posttest semi‐experimental design with one group of 333 children in a primary school between January and May 2024. A Descriptive Information Form and Earthquake Awareness Knowledge Level Form were the data collection tools. The children were provided with a 6‐week (modules) education program. Measurements were made before and after the education.The mean age of the children was 7.16 ± 0.73 years (6–9), 56.8% were girls, 43.2% were boys, and 25.8% were second‐grade children. Earthquake Awareness Knowledge Level Form total score was higher after the education (18.31 ± 1.52) than before (15.51 ± 3.73) (t = −16.144, p < 0.001). The study revealed an increase in children's knowledge regarding appropriate behaviors in the context of earthquakes, encompassing actions to be taken before, during, and after such events.Modular education and applied activities are effective in increasing children's knowledge levels in the context of teaching a concept such as earthquake preparedness, where the acquisition of life‐based skills is of paramount importance. [ABSTRACT FROM AUTHOR]

Background: Medical students experience high levels of stress and related mental health problems. Students' autonomous and controlled motivation and their mental well-being are interconnected. This study aimed to investigate whether an innovative teaching concept based on self-determination theory (SDT) could improve students' motivation and thereby reduce their stress levels, ultimately providing a healthier framework for learning. Methods: In a week-long practical psychiatry course for medical students, a new didactic concept was implemented in half the groups (n = 73) and compared with the preexisting concept (n = 75) as a randomized controlled trial (RCT). To promote the SDT-target factors of perceived autonomy, competence, and relatedness, the methods used included team building, exclusively positive feedback, group discussions, and choice in task distribution. Significant group differences in motivation, stress, performance, and their relationships were analyzed through t-tests, multiple linear regression analyses, mediation analyses, and hierarchical linear modeling (HLM) using questionnaires collected before (t0) and after (t1) the course, and students' exam results (t2). Results: In the innovation group (n = 53), intrinsic motivation/interest (d = 0.41; p =.019) and perceived choice/autonomy (d = 0.33; p =.048) were greater than in the control group (n = 52). While autonomous regulation remained stable, the innovation group showed reduced controlled regulation (d = -0.36; p =.033) and reported significantly lower stress (d = -0.55; p =.003). The observed changes in motivation collectively mediated the stress reduction. However, students in the innovation group achieved lower exam scores, which seemed to result from the absence of critical feedback, but not from the observed differences in motivation or stress. Conclusions: This study demonstrated that enhancing intrinsic motivation through SDT-based teaching can effectively reduce stress in medical students. Exclusively strengths-based positive feedback may have hindered exam performance, but optimizing educational concepts to promote motivation and reduce stress will be a valuable step toward improving medical students' mental well-being. [ABSTRACT FROM AUTHOR]

Engaging ecological resource users in intervention to protect resources is challenging for governments due to the self-interest of users and uncertainty about intervention consequences. Focusing on a case of forest insect infestations, we addressed questions of resource protection and environmentally responsible behavior promotion with a conceptual model. We coupled a forest infestation model with a social model in which a governing agent applies a mechanism for the recognition and promotion of environmentally responsible behavior among several user agents. We ran the coupled model in various scenarios with a reinforcement-learning algorithm for the governing agent as well as best-case, worst-case, and random baselines. Results showed that a proper recognition policy facilitates emergence of environmentally responsible behavior. However, ecosystem health may deteriorate due to temporal differences between the social and ecological systems. Our work shows it is possible to gain insight about complexities of social–ecological systems with conceptual models through scenario analysis. [ABSTRACT FROM AUTHOR]

Pedestrian action prediction is crucial for many applications such as autonomous driving. However, state-of-the-art methods lack the explainability needed for trustworthy predictions. In this paper, a novel framework called MulCPred is proposed that explains its predictions based on multi-modal concepts represented by training samples. Previous concept-based methods have limitations, including the following: (1) they cannot be directly applied to multi-modal cases; (2) they lack the locality needed to attend to details in the inputs; (3) they are susceptible to mode collapse. These limitations are tackled accordingly through the following approaches: (1) a linear aggregator to integrate the activation results of the concepts into predictions, which associates concepts of different modalities and provides ante hoc explanations of the relevance between the concepts and the predictions; (2) a channel-wise recalibration module that attends to local spatiotemporal regions, which enables the concepts with locality; (3) a feature regularization loss that encourages the concepts to learn diverse patterns. MulCPred is evaluated on multiple datasets and tasks. Both qualitative and quantitative results demonstrate that MulCPred is promising in improving the explainability of pedestrian action prediction without obvious performance degradation. Moreover, by removing unrecognizable concepts, MulCPred shows improved cross-dataset prediction performance, suggesting its potential for further generalization. [ABSTRACT FROM AUTHOR]

A new platform for learning in a mobile environment was established by improvements in e-learning technologies. However, probably because of the low level of interactive learning content, many of the concepts in mobile-based learning environments have begun struggling to engage students. Therefore, this study paper proposes an augmented reality (AR) technique for the enhanced interactive learning experience for the students. A new platform for learning in a mobile environment was established by innovations in e-learning technologies. Unsurprisingly, owing to a tiny amount of interactive learning content, many of the concepts in mobile-based learning environments are now underperforming to engage students. To erect the mapping process for mobile task learners and empower the software of AR through mobile with the parameter, the deployment of mobile learning parameters is also appreciated. This study analyzes how AR could impact traditional learning methodologies by using mobile devices to combine digital information with actual surroundings. It achieves this by carrying out an in-depth evaluation of the most current research and an analysis of case studies. In regards to considerable accomplishments, AR in mobile learning might improve student engagement, boost experiential learning, and support better knowledge retention. The publication additionally includes implementation-related diffi- culties for AR, such as technological barriers and the prerequisite for revised instructional schemes. The study finalizes with proposals for future research to advance our comprehension of and enhance the value of AR applications in educational contexts and additionally suggests to educators and developers how to fully utilize the beneficial features of AR in mobile learning. [ABSTRACT FROM AUTHOR]

This article reflects on the complexity of co-generative learning processes between a university and regional actors, drawing on the author's experience facilitating an action research course. The course engages students in collaborating with regional practitioners on real-life territorial development challenges. Through glimpses into the co-generation process from student exam papers, the article highlights the challenges students face in navigating ambiguity and complexity when exposed to real-life territorial issues. Concepts such as regional complexity, Bildung, interiority, and democratic dialogue are used to analyze how structured reflection and facilitation through participation with regional actors can enhance students' critical capacities for reflection and action. The main theoretical contribution is extending the concept of co-generative learning of Morten Levin and action research for territorial development by integrating students as reflective, facilitative actors in educational and regional development processes. Action research for territorial development provides a framework for accompanying the social transformations needed to address complex challenges. The article shows that by engaging in real-life issues through participatory, reflective processes, students develop crucial skills for facilitating collective territorial development efforts. Despite limitations related to geographic context and the course structure, the insights gained offer valuable implications for applying Levin's legacy in other contexts. [ABSTRACT FROM AUTHOR]

Medical education is an ever-evolving realm, continuously striving for innovative methods to improve learning outcomes and nurture competent healthcare practitioners. Concept mapping has emerged as a valuable tool in this drive, aiding in the organization and synthesis of intricate information. This review delves into the infusion of Islamic teachings into concept map teaching and curriculum development within medical education. By drawing on Islamic principles related to knowledge acquisition, ethics, and comprehensive healthcare, this examination offers strategies for integrating Islamic perspectives into concept map-based teaching approaches. Through harmonizing educational practices with Islamic ethos, medical educators can cultivate an environment that is culturally attuned and ethically rooted, fostering the development of healthcare professionals who embody compassion and integrity in serving their communities. [ABSTRACT FROM AUTHOR]

Background: Tests are commonly and heavily used in fundamental engineering courses (FECs) to assess student learning of concepts. With existing literature presenting mixed benefits and disadvantages of testing to students' motivation to learn and documenting widely alternative assessments, the lack of questioning of heavy and common test usage must be addressed to diversify classroom assessment and promote intentionality in test usage. Purpose/Hypothesis: This study begins to address the lack of questioning by exploring and uncovering test usage beliefs and behaviors of seven FEC instructors from two engineering departments in a land‐grant, public, Research 1 university Design/Method: Grounded in the Situated Expectancy–Value Theory (SEVT), we conducted a multicase study. Data include two interviews, course syllabi, and sample tests provided by the participants, and public documents from the institution and departments. We conducted a priori and emergent coding and thematic analysis to identify the beliefs and behaviors before developing individual case summaries for cross‐case analysis to identify groupings. Results: Three test usage groups emerged: enthusiastic, default, and questioning. All test usage groups featured tests heavily in their FECs, resulting in varying alignment between these participants' test usage beliefs and behaviors. Conclusions: Our findings reveal the various factors that can shape FEC instructors' test usage beliefs and behaviors, and the complexity in terms of alignment. This work lays important implications, including laying the foundations for future scholarship on testing in engineering education research and leveraging findings to begin efforts in diversifying assessment approaches and promoting intentional test usage in FECs. [ABSTRACT FROM AUTHOR]

Introduction: Public health systems worldwide face increasing challenges in addressing complex health issues and improving population health outcomes. This experience report introduces the concept of a Learning Public Health System (LPHS) as a potential solution to transform public health practice. Building upon the framework of a Learning Health System (LHS) in healthcare, the LPHS aims to create a dynamic, data‐driven ecosystem that continuously improves public health interventions and policies. This report explores the definition, benefits, challenges, and implementation strategies of an LPHS, highlighting its potential to revolutionize public health practice. Methods: This report employs a comparative analysis approach, examining the similarities and differences between an LPHS and an LHS. It also identifies and elaborates on the potential benefits, challenges, and barriers to implementing an LPHS. Additionally, the study investigates promising national initiatives that exemplify elements of an LPHS in action. Results: An LPHS integrates data from diverse sources to inform knowledge generation, policy development, and operational improvements. Key benefits of implementing an LPHS include improved disease prevention, evidence‐informed policy‐making, and enhanced health outcomes. However, several challenges were identified, such as interoperability issues, governance concerns, funding limitations, and cultural factors that may impede the widespread adoption of an LPHS. Conclusions: Implementation of an LPHS has the potential to significantly transform public health practice. To realize this potential, a call to action is issued for stakeholders across the public health ecosystem. Recommendations include investing in informatics infrastructure, prioritizing workforce development, establishing robust data governance frameworks, and creating incentives to support the development and implementation of a LPHS. By addressing these key areas, public health systems can evolve to become more responsive, efficient, and effective in improving population health outcomes. [ABSTRACT FROM AUTHOR]

Background: Processes of self‐reflection and the learning they allow are crucial before, during, and after acute emergencies, including infectious disease outbreaks. Tools—such as Action Reviews—offer World Health Organization (WHO) member states a platform to enhance learning. We sought to better understand the value of these tools and how they may be further refined and better used. Methods: We searched the publicly available WHO Strategic Partnership for Health Security website for paired reports of Action Reviews, that is, reports with a comparable follow‐up report. We complemented the paired action reviews, with a literature search, including the gray literature. The paired action reviews were analyzed using the "Learning Health Systems" framework. Results: We identified three paired action reviews: Lassa Fever After Action Reviews (AARs) in Nigeria (2017 and 2018), COVID‐19 Intra‐Action Reviews (IARs) in Botswana (2020 and 2021), and COVID‐19 IARs in South Sudan (2020 and 2021). Action Reviews allowed for surfacing relevant knowledge and, by engaging the right (in different contexts) actors, asking "are we doing things right?" (single loop learning) was evident in all the reports. Single loop learning is often embedded within examples of double loop learning ("are we doing the right things?"), providing a more transformative basis for policy change. Triple loop learning ("are we learning right"?) was evident in AARs, and less in IARs. The range of participants involved, the level of concentrated focus on specific issues, the duration available for follow through, and the pressures on the health system to respond influenced the type (i.e., loop) and the effectiveness of learning. Conclusion: Action Reviews, by design, surface knowledge. With favorable contextual conditions, this knowledge can then be applied and lead to corrective and innovative actions to improve health system performance, and in exceptional cases, continuous learning. [ABSTRACT FROM AUTHOR]

Simulation-based teaching can be a valuable method for learning statistical concepts. Its practical implementation for health-related subjects is seldomly evaluated. We propose a simulation-based approach to teach interaction effects in a postgraduate biostatistics course. We describe the steps involved in organizing and implementing a simulation-based activity and evaluate its execution. Mainly master and doctoral students in medical sciences (public health/epidemiology) participated to a 3-hr long online workshop on interaction effects. We presented one main learning activity, broken down into six progressive steps, from visualizing an interaction effect to investigating samples leading to erroneous inference. A total of 85 people attended of which 53 filled out an evaluation survey. Most (89%) of the respondents reported that the proposed activities helped them better understand interaction effects. A qualitative content analysis of free-text answers indicated that learning activities focusing on interaction effects in this way were useful for developing an understanding of both the meaning of statistical models and their interpretations. We conclude that a simulation-based approach can be a useful and interactive tool to create a valuable learning experience. The materials provided in this article can serve as a starting point for teachers who wish to implement such a method. [ABSTRACT FROM AUTHOR]

The mutation-based grey-box protocol fuzzing methods are convenient and highly scalable. However, they lack the message format information of the protocol under test, resulting in most of the messages in test cases being rejected by the target protocol implementation, severely affecting the testing efficiency. To address this issue, this paper proposed a greybox fuzzing method for text protocol based on field perception. This method incorporated the concept of template learning into mutation-based protocol fuzzing. It used delimiters to segment message fields and utilized a field dictionary to obtain valid values for each field. Subsequently, this paper designed multiple field-level mutation strategies for the segmented messages and calculated the corresponding field mutation energy based on the number of valid values and coverage feedback. Moreover, this approach leveraged the results of message field segmentation to provide a more fine-grained characterization of the protocol implementation state. Experimental results demonstrate that this method can improve the proportion of test cases accepted by the target protocol implementation generated by the classic mutation-based protocol fuzzing framework AFLNET, thereby increasing testing efficiency over five times. It proves that the low acceptance rate of test cases in the commonly used mutation-based protocol fuzzing methods decrease the overall testing efficiency, and increasing the test case acceptance rate can improve the testing efficiency significantly. [ABSTRACT FROM AUTHOR]

This study aimed to determine the effectiveness of an ocean culture course using the TRIP learning model (Triggered situational interest-Reading-Inquiry-Presentation) in enhancing students' marine life concepts and learning interests. The participants consisted of 67 first-graders (six years old). A quasi-experimental design was employed, and the mixed methods analysis was used in this study. The results showed that the experimental group students' concepts of marine life were improved with a large effect size (d = 1.4), and they outperformed their counterparts with a large effect size (f =.40). The students' learning interest in marine ecological conservation concepts was improved with a medium effect size (d =.53), and they outperformed their counterparts with a large effect size (f =.54). The results revealed that using the TRIP learning model for ocean education improved the teaching of the teachers who taught the experiment group. Moreover, the model enhanced the effectiveness of students' learning interest in understanding marine life and marine ecological conservation concepts. Finally, some suggestions for further teaching and research were provided. [ABSTRACT FROM AUTHOR]

An intervention using the unplugged programming and storytelling (UPS) strategy was implemented in this study to cultivate students’ programming learning motivation and concepts. The participants were 49 second graders at a primary school in southern Taiwan. The course was conducted for 12 lessons (40 min each lesson). A quasi-experimental design was employed in this study. During the course, students in the experimental group were taught using the UPS strategy. Data collection included the Programming Concept Test and Programming Learning Motivation Scale supplemented by classroom observation and interview data. The results revealed that the experimental group outperformed the comparison group in programming learning motivation and concepts after the course with the UPS strategy. This teaching experiment obtained large effect sizes. Interviews showed that students perceived positively, which helped them develop their programming concepts. The implication is that the UPS strategy may contribute to primary school programming courses. [ABSTRACT FROM AUTHOR]

Background & Objective: Mentorship is essential for medical undergraduates' professional and personal development to enhance soft skills, knowledge, and academic performance. The present study analyzed the mentee's feedback about the program. Material & Methods: The present cross-sectional (retrospective) study, approved by the ethics committee, was conducted between January and March 2022. One hundred fifty feedback forms (open and closed-ended questions) of 2016-2019 MBBS students (at the end of one and a half years of implementation) were analyzed. Data were represented as mean ± SD and median. Qualitative data was coded and analyzed descriptively. Results: 58% and 50.66% of mentees agreed on easy approachability and communication with mentors. 52.67 % agreed strongly, and 52% agreed that mentors listened actively to their problems and provided constructive feedback. 68.67% agreed and 56.67% agreed strongly that important lessons about personal, college, and career life were learned. 78.66% agreed that research motivation was provided. 71, 33%, and 60% agreed that mentoring helped improve academics and develop a conceptual learning style. 70% and 51.33% agreed that mentors helped them solve medical life problems and develop skills (communication, interpersonal, and humane values). 46.66% agreed that mentors encouraged them to participate in sports or extracurricular activities. 52% agreed strongly that their mentors had a professional attitude, 47.33% agreed mentors were beneficial to them, and 46.67% agreed strongly to recommend their mentors for future professional and personal development activities. Open-ended analysis showed that, in decreasing order, the most beneficial developmental activities performed with their mentors were problem-solving (40.56%), guidance, counseling (34.26%), and soft skill development (13.85%). Menttes considered time constraints a hurdle and suggested scheduled, regular meetings and the use of social media for the program's effectiveness. Conclusion: Regular feedback, evaluation, and perceptions of mentees are vital for the mentorship program. [ABSTRACT FROM AUTHOR]

In upper-secondary chemistry education, the concept of 'Amount of Substance' occupies a central position within the computation framework. However, comprehending this concept often poses a challenge for students. To address this issue, our study aimed to design and implement a computation skills test to assess the varying levels of students' computation skills in understanding Amount of Substance. The test was administered to a total of 214 first-year students at the secondary schools. To analyse the test scores and unveil students' comprehensive and mastery levels of computation skills, the SOLO Taxonomy was employed for scoring the levels. Additionally, interviews were conducted to identify the underlying reasons for their learning difficulties. Findings revealed that the majority of students demonstrated proficiency in solving relatively straightforward problems and applying basic formulas. Only a small fraction of students reached the advanced relational level, showcasing their ability to apply chemical concepts and methodologies to solve complex problems. Moreover, students exhibited varying degrees of proficiency when dealing with different types of knowledge and problems associated with computations involving solutions and the quantification of microscopic particles. Interviews uncovered students' major learning difficulties. These findings inform the teachers' teaching of Amount of Substance in chemistry education. [ABSTRACT FROM AUTHOR]

A range of stakeholder groups are involved with fostering Education for Sustainable Development (ESD). It is crucial that their views on the aims of ESD are aligned. This is a prerequisite for coordinated integration of ESD into the formal education system. However, research has not explored whether stakeholder groups have similar ideas about the aims and learning outcomes of ESD. This study investigates the differences and similarities in stakeholders' opinions on the sustainability key competencies students should develop. We conducted 15 interviews with German experts in ESD practice, policy, and science, analyzing the results deductively using Qualitative Content Analysis within the UNESCO framework of Key Competencies for Sustainability. An inductive approach was used to identify aspects and concepts of competence that went beyond this framework. Most of the competencies mentioned could be assigned to the UNESCO framework, but we identified the additional competency of participating at the political level as being important for ESD. The experts also identified several other concepts. The three stakeholder groups emphasized different competencies and concepts, probably due to their differing professional backgrounds. However, similarities predominated, and the experts largely agreed on which competencies should be developed. Structural difficulties with integrating ESD into the education system are therefore not likely to be the result of fundamental differences in perspective between the three stakeholder groups on the aims of ESD. However, their different frames of reference might lead to miscommunication and misunderstanding, which could impede integration. This aspect needs thorough examination in the future. [ABSTRACT FROM AUTHOR]

This study to investigate the effect of using transformative learning theory (TLT) -based teaching model on a conceptual change and developing mental motivation in Physics for secondary school students. The study follows the descriptive, analytical, and experimental method with a quasi-experimental design for experimental and control groups. sample consisted of (70) students from 1st-grade secondary school who are divided into two groups: the experimental group (34) students and the control group (36) students. To achieve the objectives of the study, A Conceptual Change Test (CCT) and A Mental Motivation Scale (MMS) were constructed. The results revealed that a TLT-based teaching model has effects on changing concepts and developing mental motivation in Physics. Moreover, there is a statistically significant correlation (r= 0.358) between the growth of mental motivation and the inducing of a conceptual change in physics for secondary school students. In light of the results, the study recommended conducting further studies on transformational learning theory (TLT) and conceptual change and mental motivation in various fields and learning stages. [ABSTRACT FROM AUTHOR]

• Need innovative teaching to improve clinical judgment and RN practice readiness. • Adds new perspective to traditional clinical care plan and concept map utilization. • Clinical care worksheets followed by concept maps ideal to build clinical judgment. Nursing faculty must develop innovative strategies to foster pre-licensure student development of clinical judgment and improve practice readiness. Clinical care worksheets are traditionally long, linear assignments to help students identify various elements of patient care. Clinical concept map assignments help student identify relationships and prioritize care needs. Comparison of clinical concept maps and clinical care worksheets was performed with pre-licensure nursing students in their first clinical course. Student and faculty perceptions on clinical judgment development, learning, time spent, and preference of assignment were evaluated. Both assignment types were beneficial to student learning but in different ways. Most students perceived that concept maps contained less busywork and were more helpful to improve learning, thus preferring this assignment. Students and faculty recognized the value of building base knowledge with clinical care worksheets followed by incorporation of clinical concept maps to connect the entire patient care picture and maximize learning. We recommend using clinical care worksheets then advancing to clinical concept maps to help build clinical judgment and learning most efficiently and effectively. [ABSTRACT FROM AUTHOR]

Adaptive learning support provided by kindergarten teachers before and after (macro-adaptive learning support) as well as during mathematical learning activities (micro-adaptive learning support) is a cross-cutting concept of teaching quality. Effective adaptive learning support enhances children's learning. However, providing it is challenging and teachers need professional development (PD) to improve the quality of their support. This study investigates the mediating role of teaching quality between PD programs for kindergarten teachers and the development of children's mathematical competency. 122 kindergarten teachers and their 825 pupils participated in the study. The teachers were randomly assigned to three groups. Two groups attended PD sessions designed to foster either macro- or micro-adaptive learning support. The third was the materials-only control group. The data was analyzed using a self-developed rating instrument focusing on generic and domain-specific elements of teaching quality related to macro- and micro-adaptive learning support. The multilevel latent change model analysis revealed that the PD programs had positive and significant effects on the teaching quality of kindergarten teachers. A significant positive relationship was also found between micro-adaptive learning support and changes in children's mathematical competency. However, an indirect effect of teaching quality could not be detected, and the PD programs did not have a total effect on children's mathematical competency. The study reinforces the importance of PD that specifically targets macro- and micro-adaptive learning support for kindergarten teachers. The mediation between PD and mathematical competency development requires further investigation. [ABSTRACT FROM AUTHOR]

Copyright of Modern Educational Technology is the property of Editorial Board of Modern Educational Technology, Tsinghua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ethnoscience is a science learning approach that implements local wisdom (regional culture) using certain cultural products. Local wisdom can be in the form of foods, drinks, traditional ceremonies, dances, games, and languages. One of the local wisdom-based traditional foods is Papeda, a traditional food from North Maluku made from sago flour. The main problems addressed in this research are: 1) How is the the reconstruction of indigenous knowledge related to the process of making papeda into scientific knowledge? and 2) What chemical concepts are contained in the process of making papeda, and how is their relevance for science learning among students?. The purpose of this research is to reconstruct the indigenous knowledge into scientific knowledge and examine the chemical concepts in the process of making papeda for science learning. The research method used is descriptive qualitative research through interviews and literature studies. The results of this study indicate that the reconstruction of indigenous knowledge into scientific knowledge from the process of making Papeda can be used as a learning resource for students because it has relevance to various chemical concepts in science learning. The chemical concepts contained in the process of making papeda are substances and their changes, colloids, physical and chemical changes, thermochemistry, macromolecules (especially carbohydrates), and nutrients with their relationship to the digestive system. [ABSTRACT FROM AUTHOR]

Predicting the onset of cardiovascular disease (CVD) has been a hot topic for researchers for years, and recently, the concept of transfer learning has been gaining traction in this field. Transfer learning (TL) is a process that involves transferring information gained from one task or domain to another related task or domain. This paper comprehensively reviews recent advancements in pre-trained TL models for CVD, focusing on electrocardiogram (ECG) signals. Forty-three articles were chosen from Scopus and Google Scholar sources and reviewed, focusing on the type of CVD detected, the database used, the ECG input format, and the pre-training model used for transfer learning. The results show that more than 80% of the studies utilize 2-dimensional (2D) ECG input from the two most utilized available ECG datasets: MIT-BIH arrhythmia (ARR) and MIT-BIH normal sinus rhythm. alexnet, visual geometry group (VGG), and residual network (ResNet) are among the pre-trained TL models with the highest number used among reviewed articles. Additionally, the development of pre-trained TL models over time has made it possible to detect CVD with ECG signals. It can also address limited data problems, promote the development of more dependable and resilient detection systems, and aid medical professionals in diagnosing CVD and other diseases. [ABSTRACT FROM AUTHOR]

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Introduction: The study on self-regulated learning in blended learning (BL) environments highlights its crucial relevance for both the academic development of students and the evolution of contemporary educational methods. This research focused on conceptualizing self-regulated learning in university contexts with a BL modality, using direct student perceptions. Methods: An inductive qualitative approach with a phenomenological design was employed. Responses from 312 undergraduate students who had completed their first or second year were analyzed; 65 participated in 10 focus groups (two per area of knowledge according to OECD classification), and 247 participated through a survey. Descriptive analysis was used to obtain a range of content and meanings associated with students' perceptions of SRL-BL. Results: The study conceptualized SRL-BL as a process where students structure, monitor, and evaluate their learning using self-reflection and digital technologies, with particular emphasis on planning. Significant differences were identified between SRL-BL and traditional SRL; in face-to-face education, teacher supervision is greater, while in SRL-BL, students take on more responsibility and autonomy, developing self-management skills. Although SRL-BL fosters autonomy and responsibility, students face obstacles such as distractions from social media and leisure technologies, which affect their concentration and study planning. Discussion: It is essential to address the new challenges students face to maintain a high level of SRL in Blended Learning environments (SRL-BL) and the strategies they use to overcome them. The need to update the concept of self-regulated learning (SRL) in the current educational context, influenced by technological advances, is concluded. [ABSTRACT FROM AUTHOR]