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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]

AbstractObjectiveDesign and settingMethodResultsConclusionThe aim of this study is to explore general practice staff perspectives regarding a teaching concept based on instructional videos for conducting DR screenings. Furthermore, this study aims to investigate the competencies acquired by the staff through this teaching concept.Qualitative cross-sectional study conducted in general practice clinics in the North Denmark Region.A teaching concept was developed based on instruction videos to teach general practice staff to conduct diabetic retinopathy screenings with automated grading through artificial intelligence. Semi-structured interviews were performed with 16 staff members to investigate their perspectives on the concept and acquired competencies.This study found no substantial resistance to the teaching concept from staff; however, participants’ satisfaction with the methods employed in the instruction session, the progression of learning curves, screening competencies, and their acceptance of a known knowledge gap during screenings varied slightly among the participants.This study showed that the teaching concept can be used to teach general practice staff to conduct diabetic retinopathy screenings. Staffs’ perspectives on the teaching concept and acquired competencies varied, and this study suggest few adjustments to the concept to accommodate staff’s preferences and establish more consistent competencies. [ABSTRACT FROM AUTHOR]

Concept-cognitive learning and two-way concept-cognitive learning have been widely used to learn concepts from given cues, and fruitful results have been obtained. However, there are still some limitations: (i) The existing two-way concept-cognitive learning methods based on competences focused on dichotomous skills, but they did not consider the proficiency of skills in the concept-cognitive learning process and ignored the dynamic learning of skills. (ii) The existing necessary and sufficient information granules based on competences cannot be learned directly from any information granule. (iii) Most of the other existing two-way concept-cognitive learning models in fuzzy formal context have been studied through an antitone Galois connection, but they cannot directly deal with an isotone Galois connection between items and fuzzy skills. To overcome these issues, we propose a novel two-way concept-cognitive learning model based on fuzzy skills to learn fuzzy skill-based cognitive concepts (i.e. necessary and sufficient fuzzy skill-based information granules) from a perspective of skill proficiency. And we optimize the two-way concept-cognitive learning model to learn directly fuzzy skill-based cognitive concepts from any information granule and save time for learning concepts. Furthermore, a progressive learning mechanism is explored to deal with dynamic data. The experimental results of 12 UCI data sets show that the proposed concept-cognitive learning models in this paper are feasible and effective. [ABSTRACT FROM AUTHOR]

Backward transfer, defined as the influence that learning about new concepts has on individuals' reasoning about previously learned concepts, is a relatively new topic in mathematics education. Our exploratory study compared the backward transfer produced in a mathematics enrichment programme that emphasised covariational reasoning to that produced in real algebra classrooms that did not emphasise a particular type of reasoning. Quadratic and linear functions were the new concepts being learned about and the concepts previously learned about, respectively. One theme that emerged from our comparisons was that quadratic instruction that emphasised covariational reasoning had less, but more consistent, backward transfer than quadratic instruction that did not have a strong emphasis on a particular type of reasoning. This and other findings led us to new insights about backward transfer, as well as tentative new ideas about backward transfer more generally, that can be tested in future studies.. [ABSTRACT FROM AUTHOR]

Student evaluation of teaching (SET) involves numerous conceptual and methodological problems. This paper focuses on a specific methodological dilemma: whether to conduct SET surveys before or after the final examination. This decision is a critical administrative and practical issue that can affect the level and quality of SET results. To address this problem, a systematic literature search was initially performed. However, it found only 17 studies and inconclusive results. In the empirical component, a replication survey (n = 5,077) was conducted. It posed seven course-related questions to the same students before and after their final examination. A slightly higher but statistically significant (p < 0.001) average score was obtained in the after-examination survey (a 0.06 difference on a 1–5 scale). This increase was partly attributed to a positive examination experience. The overall test–retest correlation (r = 0.61) indicated relatively low reliability, suggesting that the before-examination survey better reflected students' attitudes. The data quality was also higher in the before-examination survey, although the before-examination survey could not properly assess the examination-related aspects of the course. From a methodological perspective, the most comprehensive insight seems to be derived from conducting SET surveys before the examination and following up with a brief after-examination survey. [ABSTRACT FROM AUTHOR]

Context-based STEM learning has been proven to be useful as interdisciplinary storylines to regulate the flow and sequencing of lessons to obtain expected outcomes. This case study pilot project aims to contextualise scientific learning to local culture. Student groups sampled from two schools in distinct social backgrounds, reflected varied Indian population. Pre-service middle school science and social studies teachers conducted eight lessons as an interdisciplinary storyline with a few natural and social science concepts utilising an artefact representing the cultural history of India for seventh-graders. Data were collected through manually recording of students' responses and products made during class activities; researchers' observations and pre-service teachers' feedback about finding solutions to the difficulties faced. In order to address three research questions about socio-cultural context in science-curriculum design, student adoption of 3D learning, and overcoming teachers' challenges, a thematic analysis of data through the lens of five science practices and one crosscutting concept was performed. This study supported context-based STEM learning for the twenty-first century and strengthened cultural anchoring from an early stage implying the need for teacher professional development, curricular reform, and school infrastructure improvements to support policy implementation. Such researches may be extended to varied sociocultural contexts and discipline combinations to offer broader perspectives. [ABSTRACT FROM AUTHOR]

Nanoscience and Nanotechnology (NST) education is at the forefront of an emerging interdisciplinary frontier, ready to address global challenges. In this context, our research adopts a distinctive approach—using software applications in digital games to introduce young children to NST concepts and analyse resulting learning outcomes. The three-step research unfolds strategically, aiming to assess the effectiveness of two distinct digital technologies (computers and tablets) at an introductory level, influencing children's understanding of Nanotechnology concepts. One hundred fifty second-grade students, divided into experimental and control groups, participated in an exploration facilitated by the Test for the NANOtechnology Elementary Knowledge Assessment (TENANO). This tool meticulously measures the depth of children's knowledge about size, a fundamental aspect of NST. The experimental groups, especially the tablet group, significantly outperformed their post-test control counterparts. This marks a pioneering stride in early primary education. By leveraging children's familiarity with digital technology, this research harnesses the recent health crisis to advance NST education through interactive games, leaving a distinctive mark on early-primary NST education and paving the way for transformative educational methodologies. [ABSTRACT FROM AUTHOR]

Helping students to understand complex processes is one of the core challenges in teaching biology courses. Concept mapping is a flexible pedagogical method that enables students to learn the complexities of a given subject while at the same time being versatile enough that instructors can easily pivot between instructional modalities and/or update learning goals. In concept mapping the instructor chooses key terms (topics, subjects, words, ideas) from the course and the students draw labeled connections between these terms. The labels on these connections describe the relationship between the two terms. Here I describe my approach to concept mapping in teaching 'Climate Change Biology' at Rowan University: hybrid group concept mapping. This approach is suitable for virtually any course, can be employed as a stand-alone assignment or as the basis for the entire course, and is appropriate for virtual (synchronous) or in-person instructional modalities. [ABSTRACT FROM AUTHOR]

Hands-on activities are considered to be particularly suitable for generating long-term knowledge that increases environmentally friendly behaviour. Appropriate flagship species in a respective curricular context can enable high-quality education. We have developed a teaching concept and material for hands-on activities with bumblebees. This includes aspects of outdoor bumblebee-keeping in a teaching unit, together with the identification of bumblebee species and conservation activity in the context of biodiversity; bumblebees can act as umbrella species because their conservation needs incidentally protect other species. Moreover, the project involves keeping bumblebees indoors in a teaching unit that covers ethology and neurobiology. A total sample size of 188 German high school students from the fifth to seventh grade (lower and intermediate secondary-school levels) participated in the project. We measured students' knowledge about bumblebees in general and insect decline, as well as fear of bumblebees in a pre-test, post-test and follow-up test. Learning enjoyment was also measured in the post-test. Students acquired long-lasting knowledge and considerably enjoyed the learning experience. Fear of bumblebees decreased long-term, although knowledge that bumblebees can sting increased. [ABSTRACT FROM AUTHOR]

Due to the COVID-19 pandemic and the stay-at-home order implemented by the New York State Governor, the introductory undergraduate biology courses were changed to an at-home remote learning modality. To provide conceptual learning and hands-on experience, the second semester introductory biology laboratory course utilised a multi-modal learning approach through the use of take-home experiments with virtual labs and meetings. This study aims to determine whether learning outcomes in conceptual understanding, hands-on experience, writing skills, and critical thinking are enhanced. There is little data showing the impact of take-home experiments on learning and in combination with virtual labs. Although student preference is for face-to-face learning, the average lab report, exams, and final grades were significantly increased during remote learning. The grade increase may be due to the repetitive nature of instruction in combination with the independent at-home experiments. This multi-modal approach seems to enhance conceptual learning and suggests that the combination of take-home experiments with virtual learning improves the core learning objectives in the second semester introductory biology labs. [ABSTRACT FROM AUTHOR]

Background: The accuracy of decoding fine motor imagery (MI) tasks remains relatively low due to the dense distribution of active areas in the cerebral cortex. Methods: To enhance the decoding of unilateral fine MI activity in the brain, a weight-optimized EEGNet model is introduced that recognizes six types of MI for the right upper limb, namely elbow flexion/extension, wrist pronation/supination and hand opening/grasping. The model is trained with augmented electroencephalography (EEG) data to learn deep features for MI classification. To address the sensitivity issue of the initial model weights to classification performance, a genetic algorithm (GA) is employed to determine the convolution kernel parameters for each layer of the EEGNet network, followed by optimization of the network weights through backpropagation. Results: The algorithm's performance on the three joint classification is validated through experiment, achieving an average accuracy of 87.97%. The binary classification recognition rates for elbow joint, wrist joint, and hand joint are respectively 93.92%, 90.2%, and 94.64%. Thus, the product of the two-step accuracy value is obtained as the overall capability to distinguish the six types of MI, reaching an average accuracy of 81.74%. Compared to commonly used neural networks and traditional algorithms, the proposed method outperforms and significantly reduces the average error of different subjects. Conclusions: Overall, this algorithm effectively addresses the sensitivity of network parameters to initial weights, enhances algorithm robustness and improves the overall performance of MI task classification. Moreover, the method is applicable to other EEG classification tasks; for example, emotion and object recognition. [ABSTRACT FROM AUTHOR]

Many U.S. school districts now rely on instructional coaching to promote reform. Yet facets of coaching policy remain vague, and there is considerable variation in the structures and practices of coaching. We use longitudinal, qualitative data to analyze changes in instructional coaching, as a capacity building policy instrument, in one mid-sized urban-emergent school district from 2014 to 2019. Applying concepts of organizational learning theory, this paper documents how district leaders designed and implemented three distinct forms of coaching. We argue coaching shifted from a tool for teacher support, to a resource for school improvement, and lastly to a lever for boosting coherence. Further, we demonstrate how particular problems and leaders triggered different degrees of organizational learning on–and changes to–coaching. In sum, the paper explains how a district alters the definitions and structures of instructional coaching. By illuminating how educational leaders tinker with capacity building instruments, this paper contributes to the instructional reform literature and advances the field's understanding of the evolution of capacity-building instruments. [ABSTRACT FROM AUTHOR]

This article explores the concept of co-production in student engagement in research. It emphasizes the collaboration between students and educators to improve educational experiences and curricula. The article addresses barriers to undergraduate research and proposes a collaborative approach to overcome these challenges. It also emphasizes the importance of diversity and inclusivity in research engagement and suggests offering funded internships to support equitable involvement. Practical guidance is provided for educators interested in implementing co-production, with a focus on design, delivery, and development stages. The article discusses the importance of engaging students in the design, delivery, and development of research through co-production principles. It highlights a case study of a workshop series that involved students and facilitators in brainstorming, generating research questions, and developing tangible internship projects. The workshops aimed to promote social interaction and mitigate hierarchical barriers. The article also discusses the evaluation of the program and the importance of selecting appropriate methodologies for project development. Feedback and suggestions for improvement were gathered from participants, leading to changes in subsequent cycles of the program. The authors plan to run the program annually and expand participation based on sustainable funding. The conclusion emphasizes the benefits of co-production in enhancing belonging, ownership, and responsibility among participants and driving effective educational innovation. [Extracted from the article]

This paper presents an ontology for AFDD (Automated Fault Detection and Diagnostics) of HVAC (Heating, Ventilation, and Air conditioning) systems in buildings called "AFDDOnto". Presently, the AFDD models are mainly data-centric and often lack semantic information such as contextual information and spatial information; additionally, configuration information, analysis, and results used for model development are lost once developed. This impedes an effective mechanism for tracking changes and updating the model for future developments and use cases. The Proposed ontology can be used for AFDD model development, tracking changes, analytics, visualization, and digital twinning by enabling integration of BIM with BAS/BMS (Building Automation System/Building Management System) concepts and secondly to store AFDD configuration and analytics in the AFDDOnto. Select competency questions are constructed using SPARQL queries to access the proposed knowledge model. The proposed ontology has been tested against different measures using multiple metrics and a case study and further validated using a semi-structured survey of experts. Applied AI engineers, Facility managers, Asset managers, and building owners aiming to develop AFDD models for HVAC systems can benefit from adopting this ontology for HVAC maintenance, including analysis, model development, and knowledge management. [ABSTRACT FROM AUTHOR]

Alternative grading methods, such as standards-based grading, provide students multiple opportunities to demonstrate their understanding of the learning outcomes in a course. These grading methods allow for more flexibility and help promote a growth mindset by embracing constructive failure for students. Implementation of these alternative grading methods requires developing specific, transparent, and assessable standards. Moving away from traditional methods also requires a mindset shift for how both students and instructors approach assessment. While providing multiple opportunities is important for learning in any course, these methods are particularly relevant to an upper level mathematical statistics course where topics covered often provide an additional challenge for students as they lie at the intersection of both theory and application. By providing multiple opportunities, students have the space for constructive failure as they tackle learning both a conceptual understanding of statistics and the supporting mathematical theory. In this article we share our experiences—including both challenges and benefits for students and instructors—in implementing standards-based grading in the first semester of a mathematical statistics course (i.e., focus primarily on probability). for this article are available online. [ABSTRACT FROM AUTHOR]

This paper examines underlying beliefs and values about nature within the early years education in Turkey, as reflected in the curricula and standards documents guiding instruction. Given that not every child has the opportunity for nature‐based education, it becomes essential to incorporate nature‐based learning into indoor classrooms. Employing a document analysis, we comprehensively analyse the Ministry of Education's Preschool Education Program (2013), Activity Book‐1 (2013a), and Activity Book‐2 (2018), which guides teachers in shaping their classroom practices, therefore providing in‐depth insights into the conceptualisations of nature. Our analysis reveals that 'nature' in these documents is characterised by its connection to and intersections of specific settings, concepts, and resources. Moreover, we found out that the identified patterns of relationships in the examined curriculum and standards documents demonstrate a purposeful initiative to engage preschool children in the realm of nature through various means, including conceptual comprehension, hands‐on interaction with materials, and direct involvement in natural surroundings. The intersections among these elements unveil a complex network of opportunities to promote an enhanced learning journey. By fostering a deeper understanding of the relationship between curriculum guidelines and nature activities, we aim to empower early childhood educators to embrace nature as an integral part of their classroom practices. [ABSTRACT FROM AUTHOR]

In the Czech Republic there has been a growing interest in education in nature [výchova v přírodě] in connection with accreditation as a field of study. Outdoor experiential educator Jan Neuman, who died in April 2021, was instrumental in the development and formalisation of Czech education in nature programmes over the past 50 years. The aim of this review is to highlight the culturally unique, holistic and multi-disciplinary approaches of the concept of education in nature within the Czech environment, comparing this term with outdoor education internationally. Such cross-referencing of different cultural and indigenous variants aims to enhance outdoor physical activity opportunities in natural environments. We define education in nature in the Czech Republic and highlight the historical development of education in nature, with a focus on turistika activities, summer camps [tábory], and holistic dramaturgy approaches that elaborate on the cultural heritage and unique Czech approach to education in nature. [ABSTRACT FROM AUTHOR]

The explosion of data volume has gradually transformed big data processing from the static batch mode to the online streaming model. Streaming data can be divided into instance streams (feature space remains fixed while instances increase over time), feature streams (instance space is fixed while features arrive over time), or both. Generally, online streaming data learning has two main challenges: infinite length and concept changing. Recently, feature stream learning has received much attention. However, existing feature stream learning methods focus on feature selection or classification but ignore the concept changing over time. To the best of our knowledge, this is the first work that studies concept evolution detection over feature streams. Specifically, we first give the formal definition of concept evolution over feature streams, which include three different types: concept emerging, concept drift, and concept forgetting. Then, we design a novel framework to detect the concept evolution over feature streams that consists of a sliding window, an improved density peak-based clustering algorithm, and a weighted bipartite graph-based concept detecting method. Extensive experiments have been conducted on several synthetic and high-dimensional datasets to indicate our new method's ability to cluster and detect concept evolution over feature streams. [ABSTRACT FROM AUTHOR]

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The Chimp Optimization Algorithm (ChOA) has emerged as a highly efficient optimization technique, demonstrating its prowess across diverse problem domains. However, its reliance on local search methods presents vulnerabilities, such as diminished diversity, susceptibility to premature convergence, and local minima. Thus, this study proposes two versions of enhancement the basic version of ChOA. The first version called ChOAO, integrates Opposition-based learning (OBL) to foster superior solution selection. The second version called ChOAORL, utilizes the concept of Reinforcement Learning (RL) to enhance the local search capabilities of ChOAO. It also effectively mitigates the risk of trapping the algorithm in local optima. The proposed versions are assessed utilizing the Friedman rank test on two sets of benchmark functions CEC 2017 and real-world problems CEC 2011. The results illustrate that ChOAORL achieved the best rank using CEC 2017 in both dimensions, 10 with a 1.48 mean rank and 30 with a 1.42 mean rank. Also, it outperformed other similar algorithms in terms of convergence precision and stability in all CEC 2011 real problems. [ABSTRACT FROM AUTHOR]

In the field of teaching college English, this study explores the integration of reinforcement learning concepts with Massive Open Online Courses (MOOCs). "LearnFlex," the suggested framework, is intended to support an environment that is dynamic and flexible for learning. By offering thorough English language courses and utilizing reinforcement learning techniques, LearnFlex leverages the inherent benefits of MOOCs to customize and enhance the learning process for every student. This study's main goal is to assess how well LearnFlex works in the context of teaching college English to improve student performance, engagement, and general satisfaction. Through the integration of educational technology, machine learning, and pedagogical methodologies, LearnFlex aims to offer significant insights that support the ongoing development of efficient and customized online learning. The study contributes to the larger objective of improving teaching strategies by utilizing cutting-edge technologies to build a learning ecosystem that is more adaptable and focused on the needs of students. This study aims to provide insights for future improvements in online education, specifically in the area of language training, by conducting a thorough examination of LearnFlex's effects. [ABSTRACT FROM AUTHOR]

Partial order formal structure analysis (POFSA) is an emerging theory in the field of concept cognitive learning (CCL). Attribute partial order structure diagram (APOSD) is the visual expression of the knowledge structure in POFSA. It has the advantages of explicit expression of the hierarchies of attributes and concise visual expression of the knowledge structure. This paper mainly focuses on the incremental CCL of APOSD in dynamic data circumstances. Firstly, the concept of location information coding of nodes in APOSD is proposed to express the position of nodes in the entire diagram as well as the relationships between nodes, which is an important tool throughout this paper. Secondly, by analyzing the relationship between new objects and objects in the original diagram, dynamic learning strategy for APOSD is proposed. Thirdly, in order to balance the efficiency and accuracy of dynamic learning, a dynamic-static alternating self-learning method for APOSD is proposed, which is an improved incremental learning strategy. Finally, comparative experiments illustrate that compared with non-incremental learning method of APOSD and concept lattice, the two proposed incremental learning methods of APOSD can effectively achieve dynamic self-updating of the knowledge base when processing dynamic data, and provide another perspective for discovering knowledge from the same data. Besides, the effectiveness of the improved incremental learning strategy is verified as well. [ABSTRACT FROM AUTHOR]

AbstractRecent data from across the globe suggest that more than 80% of both men and women play video games, and Gen Z spends 11 hours per week on average playing in 2022 (Westcott et al., 2022). Given the popularity of games as a global trend, we present teaching guides based on video games that could diversify the learning process and increase engagement in an economics classroom. Each guide includes videos and a brief description of the game to encourage educators who are unfamiliar with gaming to use games as a way to illustrate economic concepts. The paper provides an opportunity for educators to help students understand foundation-level economic concepts in an engaging way that resonates with students’ interests. [ABSTRACT FROM AUTHOR]

Background Purpose/Hypothesis Design/Method Results Conclusions 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.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 universityGrounded 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.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.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]

Background Methods Results Conclusion 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.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.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.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]

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]

AbstractBackgroundMethodsResultsConclusionThe role of artificial intelligence (AI) in teaching is a significant topic of discussion. One identified benefit from these resources is to provide novel ideas for instructional methods. Game-based learning has also been a developing topic in education with research suggesting it may improve knowledge retention. This case describes the use of an AI-suggested game for teaching human gait to physical therapy students.ChatGPT was asked for creative ideas related to teaching gait to physical therapy students. Of the proposed ideas, ‘Gait Charades’ was selected and implemented. The topic of gait was chosen specifically for this learning activity due to its complexity. In the activity, students drew papers with a phase of gait and took turns acting out the phase and with peers deciding which phase was being presented. The use of ‘Gait Charades’ has not been identified in previous literature.While this case focuses more on the process of creating and implementing the activity rather than on measured outcomes, 26 out of 29(89.6%) students agreed that it aided in their understanding of gait phases.This case serves as a reminder of the tools at educators’ disposal, such as the use of AI to provide students with immediate feedback, to provide different wording of a concept, and to create novel learning experiences. The gait activity described shows how movement-based learning can be easily integrated into instruction. Further research should investigate both the use of AI in PT education as well as the benefits of multimodal teaching. [ABSTRACT FROM AUTHOR]

Background: Despite the central role of mixed methods in health research, studies evaluating online methods training in the health sciences are nonexistent. The focused goal was to evaluate online training by comparing the self-rated skills of scholars who experienced an in-person retreat to scholars in an online retreat in specific domains of mixed methods research for the health sciences from 2015–2023. Methods: The authors administered a scholar Mixed Methods Skills Self-Assessment instrument based on an educational competency scale that included domains on: "research questions," "design/approach," "sampling," "analysis," and "dissemination" to participants of the Mixed Methods Research Training Program for the Health Sciences (MMRTP). Self-ratings on confidence on domains were compared before and after retreat participation within cohorts who attended in person (n = 73) or online (n = 57) as well as comparing across in-person to online cohorts. Responses to open-ended questions about experiences with the retreat were analyzed. Results: Scholars in an interactive program to improve mixed methods skills reported significantly increased confidence in ability to define or explain concepts and in ability to apply the concepts to practical problems, whether the program was attended in-person or synchronously online. Scholars in the online retreat had self-rated skill improvements as good or better than scholars who participated in person. With the possible exception of networking, scholars found the online format was associated with advantages such as accessibility and reduced burden of travel and finding childcare. No differences in difficulty of learning concepts was described. Conclusions: Keeping in mind that the retreat is only one component of the MMRTP, this study provides evidence that mixed methods training online was associated with the same increases in self-rated skills as persons attending online and can be a key component to increasing the capacity for mixed methods research in the health sciences. [ABSTRACT FROM AUTHOR]

Learning from multiclass imbalanced data streams with concept drift and variable class imbalance ratios under a limited label budget presents new challenges in the field of data mining. To address these challenges, this paper proposes an adaptive active learning method for multiclass imbalanced data streams with concept drift (AdaAL-MID). Firstly, a dynamic label budget strategy under concept drift scenarios is introduced, which allocates label budgets reasonably at different stages of the data stream to effectively handle concept drift. Secondly, an uncertainty-based label request strategy using a dual-margin dynamic threshold matrix is designed to enhance learning opportunities for minority class instances and those that are challenging to classify, and combined with a random strategy, it can estimate the current class imbalance distribution by accessing only a limited number of instance labels. Finally, an instance-adaptive sampling strategy is proposed, which comprehensively considers the imbalance ratio and classification difficulty of instances, and combined with a weighted ensemble strategy, improves the classification performance of the ensemble classifier in imbalanced data streams. Extensive experiments and analyses demonstrate that AdaAL-MID can handle various complex concept drifts and adapt to changes in class imbalance ratios, and it outperforms several state-of-the-art active learning algorithms. [ABSTRACT FROM AUTHOR]

The teaching objectives of traditional approaches in higher education emphasize mostly students' mastery of knowledge and have insufficient directionality to social needs. In this study, we developed a BOPPPS (Bridge-in, Objectives, Pre-assessment, Participatory Learning, Post-assessment and Summary) teaching model combined with the OBE (Outcome Based Education) concept to enhance the teaching outcomes. Firstly, based on the graduation requirements and professional training objectives of students, we divided the course objectives into three dimensions (knowledge, ability and quality), and further specified into index points. Then, the teaching content of each chapter was set to correspond with the index points. Finally, the BOPPPS teaching model was used to meet each requirement. Clinical biochemistry testing course was used as a model to assess the effects of the teaching reform. After the class, the teaching effect was analyzed based on the questionnaire surveys from the students and their scores of both the chapter and final examinations. The results showed that compared with the traditional approach, the BOPPPS teaching model combined with the OBE concept has demonstrated a notable enhancement in student engagement, and significant improvement of their mastery of knowledge, application skills, and problem-solving abilities. The examination scores of the BOPPPS group were markedly higher than those of the traditional group. Moreover, the difference between the two groups diverse assessment scores was much bigger than that between the two group examination scores. Our study indicates that the BOPPPS teaching model combined with the OBE concept is a highly effective teaching model for enhancing the learning effectiveness of students. [ABSTRACT FROM AUTHOR]

STSE is an abbreviation of Science, Technology, Society and Environment, emphasizing the correlation and interaction between science, technology, society and ecological environment. Chemistry teaching in higher vocational colleges should attach importance to the selection and organization of STSE content topics, and closely connect with the reality of production and life, so that students can comprehensively use the knowledge to explain STSE related issues. Based on this, this paper adopts research methods such as literature, content analysis and questionnaire survey to investigate and analyze the application status and problems of STSE education concept in chemistry teaching in higher vocational colleges with the students and chemistry teachers in grade 1，2 and 3 of A higher vocational colleges as the research objects, and puts forward the teaching strategy of chemistry in higher vocational colleges based on STSE education concept in order to provide guidance and reference for teachers to infiltrate STSE education concept in chemistry classroom. [ABSTRACT FROM AUTHOR]

Early education helping young children manage prejudiced attitudes towards themselves and others is urgent. Early childhood (EC) teachers in Saudi Arabia are making significant changes by applying an anti-bias approach to deal with such issues with young children. In the study reported on here we used a quantitative approach to explore anti-bias education, including an analysis of approaches to the cultural environment, which includes teaching practices and associated learning resources. Many teachers (n = 142) in the cities of Jeddah and Riyadh in Saudi Arabia contributed to this study by completing a questionnaire. Teachers' classroom practices, such as role-play, pictures, books, toys, and materials in teaching children the concept of antibias, were deeply explored. The results of the study show that the greater the previous experience of teachers in teaching children from a culture different from their own, the greater the application of the concept of anti-bias in creating the classroom environment. There is a need for further studies on the extent to which anti-bias education is being implemented on a larger scale in primary schools in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field of view and phototoxicity. To overcome these limitations, data‐driven microscopes incorporate feedback loops between data acquisition and analysis. This review overviews how machine learning enables automated image analysis to optimise microscopy in real time. We first introduce key data‐driven microscopy concepts and machine learning methods relevant to microscopy image analysis. Subsequently, we highlight pioneering works and recent advances in integrating machine learning into microscopy acquisition workflows, including optimising illumination, switching modalities and acquisition rates, and triggering targeted experiments. We then discuss the remaining challenges and future outlook. Overall, intelligent microscopes that can sense, analyse and adapt promise to transform optical imaging by opening new experimental possibilities. [ABSTRACT FROM AUTHOR]

Background: The worldwide COVID-19 pandemic has initiated a change in medical education and the development of new teaching concepts has become inevitable to maintain adequate training. Objective: This pilot study aims to compare teledidactic teaching with traditional face-to-face teaching for abdominal, thoracic, and thyroid ultrasound. Design: Concurrently, a teledidactic and a face-to-face ultrasound course were held. The students completed seven 90-min modules using mobile ultrasound probes (Butterfly IQ). Each module consisted of a lecture, a demonstration of probe guidance, and independent training. Participants: A total of thirty medical students took part in the study and were randomly assigned to a teledidactic and a face-to-face group. Main Measures: An objective structured assessment of ultrasound skills (OSAUS) was performed as a pre-test and as the final exam and ultrasound images obtained during the exam were evaluated using the brightness mode quality ultrasound imaging examination (B-QUIET) scale. Key Results: No significant difference between the two cohorts on the OSAUS final exam was shown (p > 0.05 in all modules). There was a significant difference in the assessment of the images in the focused assessment with sonography for trauma (FAST) (p 0.015) and aorta (p 0.017) modules. Students in the teledidactic group performed better in both modules, scoring 33.59 (± 2.61) out of 44 in the module FAST (face-to-face group 30.95 (± 1.76)) and aortic images averaged 35.41 (± 2.61) points (face-to-face group 32.35 (± 3.08)). Conclusions: A teledidactic course for abdominal and thoracic ultrasound examinations is equally effective to traditional face-to-face teaching in this pilot study. Digital implementation with a portable ultrasound machine could be a great opportunity to promote ultrasound education worldwide and over great distances. [ABSTRACT FROM AUTHOR]

Objective: To distinguish infarct location and type with the utmost precision using the advantages of the Swin UNEt TRansformers (Swin UNETR) architecture. Methods: The research employed a two-phase training approach. In the first phase, the Swin UNETR model was trained using the Ischemic Stroke Lesion Segmentation Challenge (ISLES) 2022 dataset, which included cases of acute and subacute infarcts. The second phase involved training with data from 309 patients. The 110 categories result from classifying infarcts based on 22 specific brain regions. Each region is divided into right and left sides, and each side includes four types of infarcts (acute, acute lacunar, subacute, subacute lacunar). The unique architecture of Swin UNETR, integrating elements of both the transformer and u-net designs with a hierarchical transformer computed with shifted windows, played a crucial role in the study. Results: During Swin UNETR training with the ISLES 2022 dataset, batch loss decreased to 0.8885±0.1897, with training and validation dice scores reaching 0.4224±0.0710 and 0.4827±0.0607, respectively. The optimal model weight had a validation dice score of 0.5747. In the patient data model, batch loss decreased to 0.0565±0.0427, with final training and validation accuracies of 0.9842±0.0005 and 0.9837±0.0010. Conclusion: The results of this study surpass the accuracy of similar studies, but they involve the issue of overfitting, highlighting the need for future efforts to improve generalizability. Such detailed classifications could significantly aid physicians in diagnosing infarcts in clinical settings. [ABSTRACT FROM AUTHOR]

During mild or moderate exercise, alveolar ventilation increases in direct proportion to metabolic rate, regulating arterial CO2 pressure near resting levels. Mechanisms giving rise to the hyperpnoea of exercise are unsettled despite over a century of investigation. In the past three decades, neuroscience has advanced tremendously, raising optimism that the 'exercise hyperpnoea dilemma' can finally be solved. In this review, new perspectives are offered in the hope of stimulating original ideas based on modern neuroscience methods and current understanding. We first describe the ventilatory control system and the challenge exercise places upon blood‐gas regulation. We highlight relevant system properties, including feedforward, feedback and adaptive (i.e., plasticity) control of breathing. We then elaborate a seldom explored hypothesis that the exercise ventilatory response continuously adapts (learns and relearns) throughout life and ponder if the memory 'engram' encoding the feedforward exercise ventilatory stimulus could reside within the cerebellum. Our hypotheses are based on accumulating evidence supporting the cerebellum's role in motor learning and the numerous direct and indirect projections from deep cerebellar nuclei to brainstem respiratory neurons. We propose that cerebellar learning may be obligatory for the accurate and adjustable exercise hyperpnoea capable of tracking changes in life conditions/experiences, and that learning arises from specific cerebellar microcircuits that can be interrogated using powerful techniques such as optogenetics and chemogenetics. Although this review is speculative, we consider it essential to reframe our perspective if we are to solve the till‐now intractable exercise hyperpnoea dilemma. What is the topic of this review?This review reframes our perspective on the control of breathing during mild or moderate exercise, emphasising concepts of learning, memory and plasticity.What advances does it highlight?We propose that exercise hyperpnoea continuously adapts to ever‐changing life conditions/experiences. We question if the memory 'engram' encoding exercise hyperpnoea resides within the cerebellum and outline powerful new methods to test this hypothesis. It is our hope that this review generates new ideas and renewed study of exercise hyperpnoea in the 21st century. [ABSTRACT FROM AUTHOR]

Metaphor generation is both a creative act and a means of learning. When learning a new concept, people often create a metaphor to connect the new concept to existing knowledge. Does the manner in which people generate a metaphor, via sudden insight (Aha! moment) or deliberate analysis, influence the quality of generation and subsequent learning outcomes? According to some research, deliberate processing enhances knowledge retention; hence, generation via analysis likely leads to better concept learning. However, other research has shown that solutions generated via insight are better remembered. In the current study, participants were presented with science concepts and descriptions, then generated metaphors for the concepts. They also indicated how they generated each metaphor and rated their metaphor for novelty and aptness. We assessed participants' learning outcomes with a memory test and evaluated the creative quality of the metaphors based on self‐ and crowd‐sourced ratings. Consistent with the deliberate processing benefit, participants became more familiar with the target science concept if they previously generated a metaphor for the concept via analysis compared to via insight. We also found that metaphors generated via analysis did not differ from metaphors generated via insight in quality (aptness or novelty) nor in how well they were remembered. However, participants' self‐evaluations of metaphors generated via insight showed more agreement with independent raters, suggesting the role of insight in modulating the creative ideation process. These preliminary findings have implications for understanding the nature of insight during idea generation and its impact on learning. [ABSTRACT FROM AUTHOR]

In this artistic essay using (re)photography, we analyse two interactions in a Washington DC, classroom that features a play-based approach to child development. The pioneers of early childhood education helped frame play as a method of learning. However, the racial memory of a place continuously disturbs this pioneering conceptualisation of the play-based approach. Adopting Avery Gordon's (2008) notion of haunting, this essay unsettles the play-based approach to learning by evoking our sense of unease, which derives from articulating children's play with the racial history of the local community. We invite the readers into our affective connections with the place to show how child's play becomes a gesture by which to create a space to remember or honour a ghost. In doing so, we hope to show how we critically mobilised the pioneering conceptualisation of the play-based approach. [ABSTRACT FROM AUTHOR]

We compose and gather stories to bewilder 'pioneering' concepts in early childhood education (ECE) that operate from the unquestioned objectivity of settler futurity. These developmentalist notions speculate that childhood is separate from adulthood. They invisibilize ontologies, especially Indigenous ontologies, that view children as complete beings. Through art-based work, we consider Montessori's pioneering concept 'control of error' from an intersectional framework that proposes implications for honouring error in ECE. We explore the cultural meanings and potentials of error, both intentional and unintentional, from our own positionalities and our shared perspective that children are always-already in deep and present relationship with the worlds that surround and compose them. One author, enrolled in the Citizen Potawatomi Nation, creates beadwork. His elders taught him that errors in beadwork are kept in as a reminder that people are imperfect. The other author, a white cisgender woman, and an infertile mother in a blended family with five children, considers both the joy and shame of errors from her perspectives as a feminist new materialist motherscholar and Montessori-trained educator. The intentional (mis)telling of a story is how we, a gay citizen of the Citizen Potawatomi Nation and a cisgender white woman, conceptualise pioneering concepts in ECE. [ABSTRACT FROM AUTHOR]

Purpose: Informative image selection in laryngoscopy has the potential for improving automatic data extraction alone, for selective data storage and a faster review process, or in combination with other artificial intelligence (AI) detection or diagnosis models. This paper aims to demonstrate the feasibility of AI in providing automatic informative laryngoscopy frame selection also capable of working in real-time providing visual feedback to guide the otolaryngologist during the examination. Methods: Several deep learning models were trained and tested on an internal dataset (n = 5147 images) and then tested on an external test set (n = 646 images) composed of both white light and narrow band images. Four videos were used to assess the real-time performance of the best-performing model. Results: ResNet-50, pre-trained with the pretext strategy, reached a precision = 95% vs. 97%, recall = 97% vs, 89%, and the F1-score = 96% vs. 93% on the internal and external test set respectively (p = 0.062). The four testing videos are provided in the supplemental materials. Conclusion: The deep learning model demonstrated excellent performance in identifying diagnostically relevant frames within laryngoscopic videos. With its solid accuracy and real-time capabilities, the system is promising for its development in a clinical setting, either autonomously for objective quality control or in conjunction with other algorithms within a comprehensive AI toolset aimed at enhancing tumor detection and diagnosis. [ABSTRACT FROM AUTHOR]

Background Aim Methods Results Conclusions Although caring is a core principle of the nursing profession, students often lack the knowledge, comprehension and ability to integrate care into all aspects of nursing practice. Students may have few opportunities to practise caring behaviours on patients who create the impression of providing care and elicit a feeling of receiving care. Studies of strategies to enhance caring behaviours in nursing education are limited.This experimental study aimed to examine the effect of nursing caring behaviours course based on interactive learning strategies on the caring behaviours and decision‐making abilities of nursing students.A purposive sample of 50 undergraduate students was recruited from a faculty of nursing. Students in the intervention group (n = 24) received 2 h of training per week for 14 weeks in accordance with caring behaviours course based on interactive learning strategies including discussion, brainstorming, concept mapping, reflection and simulation training. Nursing students in the control group (n = 26) received training according to other elective courses in the curriculum. Data were measured at the baseline time point, 7th week and 14th week with the Caring Behaviours Inventory and Nursing Decision‐Making Instrument. Chi‐square test, Mann–Whitney U‐test, Friedman test and mixed repeated measures ANOVA were used to assess the data.No significant difference was determined in terms of baseline caring behaviours and decision‐making scores between the intervention and control groups (p > 0.05). A significant difference in caring behaviours between the two groups and time effect was not found (p > 0.05). However, there was a significant interaction between time and groups (F = 3.484, p = 0.047). There was a significant increase in the decision‐making in intervention groups over time (F = 9.372, p < 0.001) and interaction between time and groups (F = 4.160, p = 0.019).A deliberate strategy to raise students' awareness of caring behaviours and incorporate interactive learning methods into education enhances both caring behaviours and clinical decision‐making. [ABSTRACT FROM AUTHOR]

Copyright of Gazi University Journal of Gazi Educational Faculty (GUJGEF) is the property of Gazi University Journal of Gazi Educational Faculty (GUJGEF) 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.)

The teaching of physical sciences primarily relies on the use of experimental activities to explain the phenomena and physical concepts taught theoretically in class. Nevertheless, this conventional approach faces various challenges and problems, which limit its ability to achieve the different pedagogical objectives set by teachers. In this study, we evaluated the effectiveness of virtual laboratories ("VLABs") as an alternative tool to traditional practices for teaching physics concepts in Moroccan secondary schools. The methodology followed in this study is quantitative and based on two questionnaires. The first is intended for teachers to evaluate the experimental activities on VLABs based on a socio-technical and pedagogical heuristic study and to verify their conformity with the expectations and characteristics of each type of learner according to the Felder-Silverman learning style preferences. The second was administered in the form of an evaluation to compare the performance of the control group with the experimental group that integrated the opportunities offered by the VLAB LABSTER. The results show that VLABs are not only comparable to conventional experimental activities in terms of applicability, ease of use, and effectiveness in achieving the learning objectives for which they were initially designated but surpass them in terms of performance, as evidenced by the significant improvement of the mean obtained by the group that integrated the experimental activities on the VLAB. Thus, VLABs can be used not only as an alternative to traditional experimental activities in distance learning but also as a viable option for potential adoption even in traditional face-to-face physics instruction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Education Research (1680-6360) is the property of Angle Publishing Co., Ltd. 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.)

Dynamic multimodal networks are networks with node attributes from different modalities where the attributes and network relationships evolve across time, i.e., both networks and multimodal attributes are dynamic; for example, dynamic relationship networks between companies that evolve across time due to changes in business strategies and alliances, which are associated with dynamic company attributes from multiple modalities such as textual online news, categorical events, and numerical financial-related data. Such information can be useful in predictive tasks involving companies. Environmental, social, and governance (ESG) ratings of companies are important for assessing the sustainability risks of companies. The process of generating ESG ratings by expert analysts is, however, laborious and time-intensive. We thus explore the use of dynamic multimodal networks extracted from the web for forecasting ESG ratings. Learning such dynamic multimodal networks from the web for forecasting ESG ratings is, however, challenging due to its heterogeneity and the low signal-to-noise ratios and non-stationary distributions of web information. Human analysts cope with such issues by learning concepts from past experience through relational thinking and scanning for such concepts when analyzing new information about a company. In this article, we propose the Dynamic Multimodal Slot Concept Attention-based Network (DynScan) model. DynScan utilizes slot attention mechanisms together with slot concept alignment and disentanglement loss functions to learn latent slot concepts from dynamic multimodal networks to improve performance on ESG rating forecasting tasks. DynScan is evaluated on forecasting tasks on six datasets, comprising three ESG ratings across two sets of companies. Our experiments show that DynScan outperforms other state-of-the-art models on these forecasting tasks. We also visualize the slot concepts learned by DynScan on five synthetic datasets and three real-world datasets and observe distinct and meaningful slot concepts being learned by DynScan across both synthetic and real-world datasets. [ABSTRACT FROM AUTHOR]

Mathematics is a fundamental subject with wide-reaching importance in education, providing students with the tools to apply mathematical principles in diverse contexts. This study examines the abilities of 60 pre-service mathematics teachers (PSTs) in identifying content and context within mathematical word problems. Utilizing a case study approach, the study employed the mathematics word problems test and the content and context questionnaire. The findings reveal that PSTs generally struggle with error detection and content comprehension in mathematical word problems, as demonstrated by their inability to recognize inaccuracies in two of three test questions. The failure of PSTs to identify errors in mathematical word problems often stems from their tendency to rely solely on the solutions they obtain, without first understanding the entire question presented. In essence, they may focus on finding a solution rather than critically evaluating the problem, which can lead to the oversight of errors or inaccuracies within the problem statement itself. This study emphasizes the need for PSTs to grasp mathematical concepts and contextualize them in everyday life scenarios. Challenges were observed in linking computational results to real-world contexts. Thus, the study calls for future research in pre-service teacher education to explore strategies for enhancing critical thinking, error detection, and the integration of practical context in mathematical problemsolving. Furthermore, the study suggests that assessing the ability of PSTs to formulate problem-solving questions evaluates their capacity to answer questions and their ability to construct questions that can enhance students’ cognitive abilities. [ABSTRACT FROM AUTHOR]

Computer networks are one of the skills that require mastering concepts, but a weak comprehension of these concepts can cause cognitive and psychomotor challenges for students. Several studies showed that a group of information technology education students at a university struggled with basic network practical exercises, signifying the importance of addressing conceptual understanding. Therefore, this study aimed to enhance students’ comprehension of high-level abstract computer network materials. To achieve the desired outcome, a pre-test post-test control group design was conducted on two groups of 29 students each. The results showed a positive impact on strengthening the conceptual understanding of students. Consequently, the experimental class achieved higher test scores compared to the control class, with a difference of 11.6. Data processing also showed higher N-gain values in the experimental class, indicating that analogies had a positive influence on students’ conceptual understanding of computer network materials. [ABSTRACT FROM AUTHOR]