Search results for: self-regulated learning theory

Authors: Kevin Chan, Kevin K. H. Chung, Patcy P. S. Yeung, H. L. Ip, Bill T. C. Chung, Karen M. K. Chung

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Purpose: Recent evidence shows that reading self-efficacy and students perceived difficulty in reading are significantly associated with word reading and reading fluency. However, little is known about these relationships among students learning to read English as a second language, particularly in Chinese students. This study examined the contributions of reading self-efficacy, perception of difficulty in reading, and cognitive-linguistic skills to performance on English word reading and reading fluency in Chinese students. Method: A sample of 122 second-and third-grade students in Hong Kong, China, participated in this study. Students completed the measures of reading self-efficacy and perception of difficulty in reading. They were assessed on their English cognitive-linguistic and reading skills: rapid automatized naming, nonword reading, phonological awareness, word reading, and one-minute word reading. Results: Results of path analysis indicated that when students’ grades were controlled, reading self-efficacy was a significant correlate of word reading and reading fluency, whereas perception of difficulty in reading negatively predicted word reading. Conclusion: These findings underscore the importance of taking students’ reading self-efficacy and perception of difficulty in reading and their cognitive-linguistic skills into consideration when designing reading intervention and instructions for students learning English as a second language.

Keywords: self-efficacy, perception of difficulty in reading, english as a second language, word reading

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Jin Lam, Joe Au

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This study aims to investigate the impact of practicing expressive textile arts on the underprivileged people namely, ex-offenders after taking a three-month textile arts and fashion creativity workshops from a service-learning subject, offered by the Hong Kong Polytechnic University in May 2016. In this service-learning subject, the subject lecturers, students and ex-offenders co-designed various expressive textile artworks together. During the creative process, the ex-offenders could enhance their self-confidence and rebuild a satisfactory identity through practicing expressive textile arts and fashion creativity. Ten textile arts prototypes in the format of fashion garments were presented in a mini fashion show and an exhibition, both at the Hong Kong Polytechnic University in July 2016. A quantitative research method was adopted and a questionnaire survey was conducted in this study. The research findings suggest that positive impacts are found on the ex-offenders’ perceptions of ‘feelings and thoughts before attending the workshops’, ‘feelings and thoughts during the workshops’, ‘attitude toward the textile arts materials’, and ‘attitude toward the expressive textile artworks’.

Keywords: creativity, design, expressive textile arts, fashion, underprivileged people

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Anandita Mitro, Archana Srivastava, Bidisha Banerjee

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The present paper attempts to analyze the hierarchy and interconnection of factors responsible for the uptake of BCG vaccination in India. The study uses National Family Health Survey (NFHS-5) data which was conducted during 2019-21. The univariate logistic regression method is used to understand the univariate effects while the interconnection effects have been studied using the Categorical Inference Tree (CIT) which is a non-parametric Machine Learning (ML) model. The hierarchy of the factors is further established using Conditional Inference Forest which is an extension of the CIT approach. The results suggest that BCG vaccination coverage was influenced more by system-level factors and awareness than education or socio-economic status. Factors such as place of delivery, antenatal care, and postnatal care were crucial, with variations based on delivery location. Region-specific differences were also observed which could be explained by the factors. Awareness of the disease was less impactful along with the factor of wealth and urban or rural residence, although awareness did appear to substitute for inadequate ANC. Thus, from the policy point of view, it is revealed that certain subpopulations have less prevalence of vaccination which implies that there is a need for population-specific policy action to achieve a hundred percent coverage.

Keywords: vaccination, NFHS, machine learning, public health

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Authors: Eftah Bte Moh, Hj Abdullah Izazol Binti Idris, Abd. Aziz Bin Abd. Shukor

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This study aimed to identify the alignment of understanding and assessment practices among secondary school teachers. The study was carried out using quantitative descriptive study. The sample consisted of 164 teachers who taught Form 1 and 2 from 11 secondary schools in the district of North Kinta, Perak, Malaysia. Data were obtained from 164 respondents who answered Expectation Alignment Understanding and Practices of School Assessment (PEKDAPS) questionnaire. The data were analysed using SPSS 17.0 +. The Cronbach alpha value obtained through PEKDAPS questionnaire pilot study was 0.86. The results showed that teachers' performance in PEKDAPS based on the mean value was less than 3, which means that perfect alignment does not occur between the understanding and practices of school assessment. Two major PEKDAPS sub-constructs of articulation across grade and age and usability of the system were higher than the moderate alignment of the understanding and practices of school assessment (Min=2.0). The content was focused on PEKDAPs sub-constructs which showed lower than the moderate alignment of the understanding and practices of school assessment (Min=2.0). Another two PEKDAPS sub-constructs of transparency and fairness and the pedagogical implications showed moderate alignment (2.0). The implications of the study is that teachers need to fully understand the importance of alignment among components of assessment, learning and teaching and learning objectives as strategies to achieve quality assessment process.

Keywords: school based assessment, alignment, understanding, assessment practices

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Authors: Margareth S. Zanchetta, Kateryna Metersky, Valerie Tan, Charissa Cordon, Stephanie Lucchese, Yana Siganevich, Prasha Sivasundaram, Truong Binh Nguyen, Imran Qureshi

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Due to a new area of practice, Canadian nurses possess knowledge gaps regarding the use of cannabis-based therapies by clients/patients. Education related to medical cannabis (MC) and recreational cannabis (RC) is required to promote nurses’ competency and confidence in supporting clients/patients using MC/RC toward the improvement of health outcomes. A team composed of nursing researchers and undergraduate/graduate students implemented a national survey to explore this theme with the population of undergraduate, graduate (MN and NP), and Post-Diploma (RN Bridging) nursing students enrolled in Canadian Universities Nursing Programs. Upon Research Ethics Board approval, survey recruitment was supported by major nursing stakeholders. The research questions were : (a) Which are the most preferred sources of information on MC/RC for nursing students? (b) Which are the factors and preferred learning modalities that could increase interest in learning about MC/RC, and (c) What are the future career plans among nursing students, and how would they consider the prospective use of cannabis in their practice? The survey was available from Sept. 2022 to Feb. 2023, hosted by a remote platform. An original questionnaire (English-French) was composed of 18 multiple choice questions and 2 open-ended questions. Sociodemographic information and closed-ended responses were compiled as descriptive statistics, while narrative accounts will be analysed through thematic analysis. Respondents (n=153) were from 7 Canadian provinces, national (99%) and international students (1%); the majority of respondents (61%) were in the age range of 21-30 years old. Results indicated that respondents perceive a gap in the undergraduate curriculum on the topics of MC/RC (91%) and that their learning needs include regulations (90%), data on effectiveness (88%), dosing best practices (86%), contraindications (83%), and clinical and medical indications (76%). Respondents reported motivation to learn more about MC/RC through online lectures/videos (65%), e-learning modules or online interactive training (61%), workshops (51%), webinars (36%), and social media (35%). Their primary career-related motivations regarding MC/RC knowledge include enhancing nursing practice (76%), learning about this growing scope of practice (61%), keeping up-to-date responding to scientific curiosity (59%), learning about evidence-based practice (59%), and utilizing alternative forms of medical treatment (37%). Respondents indicated that the integration of topics on cannabis in any course in the undergraduate and/or graduate curriculum would increase their desire to learn about MC/RC as equally as exposure within a clinical setting (75%). The emerging trend in the set of narrative responses (n=130) suggests that respondents believe educational MC/RC content should be integrated into core nursing courses. Respondents also urged educators to be well-informed about evidence-based practice related to MC/RC and to reflect upon stigma and biases surrounding its use. Future knowledge dissemination and translation activities include scholarly products and presentations to stimulate discussion amongst nursing faculty and students, as well as nurses in clinical settings. The goal is to mobilise talents and build collaboration for the development of a socially responsive curriculum on MC/RC competency to address the education-related expectations of all these social actors.

Keywords: Canada, medical cannabis, nursing education, nursing graduate student, nursing undergraduate student, online survey, recreational cannabis

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Authors: Davut Disci

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Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance- Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling(SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: education, mobile behavior, mobile learning, technology, Turkey

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Authors: Miraç Savaş Turhan, Ali Danişman

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Recently scholars of new institutional theory have used institutional logics perspective to explain the contradictory practices in modern western societies. Accordingly, distinct institutional logics are embedded in central institutions such as the market, state, democracy, family, and religion. They guide individual and organizational actors and constraint their behaviors in a particular organizational field. Through this perspective, actors are assumed to have a situated, embedded, boundedly intentional, and adaptive role against the structure in social, cultural and political context. On the other hand, over a decade, there is an emerging attempt focusing on the role of actors on creating, maintaining, and changing the institutions. Such attempts brought out the concept of institutional entrepreneurs to explain the role of individual actors in relation to institutions. Institutional entrepreneurs are individuals, groups of individuals, organizations or groups of organizations that are able to initiate some actions to build, maintain or change institutions. While recent studies on institutional logics perspective have attempted to explain roles of entrepreneurial actors who have resources and skills, little is known about the effects of multiple institutional logics on the ability of institutional entrepreneurs. In this study, we aim to find out that how multiple institutional logics affect the ability of institutional entrepreneurs during the process of institutional change. We examine this issue in the Turkish Education Field. While institutional logics were identified based on the previous studies in the education field, the actions taken by Turkish National Education Ministry from 2003 to 2013 was examined through content analysis The early results indicate that there are remarkable shift and contradictions in the ability of institutional entrepreneur in taking actions to change the field in relationship to balance of power shift among the carriers of institutional logics.

Keywords: institutional theory, institutional logics, institutional entrepreneurs, Turkish national education

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Authors: Karima Kimouche

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In this paper, we consider the asymptotic problems in spectral analysis of stationary causal random fields. We impose conditions only involving (conditional) moments, which are easily verifiable for a variety of nonlinear random fields. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given.

Keywords: spatial nonlinear processes, spectral estimators, GMC condition, bootstrap method

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Authors: Hao Huang

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INTRODUCTION: The Association of American Colleges and Universities (AACU) recommends the development of ‘high-impact practices,’ in an effort to increase rates of student retention and student engagement at undergraduate institutions. To achieve these goals, the Scripps College Humanities Institute and HI Fellows Seminar not only featured distinguished academics presenting their scholarship about current immigration policy and its consequences in the USA and around the world but integrated socially significant community leaders and creative activists/artivists in public talks, student workshops and collaborative art events. Students participated in experiential learning that involved guest personal presentations and discussions, oral history interviews that applied standard oral history methodologies, detailed cultural documentation, collaborative artistic interventions, and weekly posts in Internet Digital Learning Environment Sakai collaborative course forums and regular responses to other students’ comments. Our teaching pedagogies addressed the four learning styles outlined in Kolb’s Learning Style Inventory. PROJECT DESCRIPTION: Over the academic year 2017-18, the Scripps College Humanities Institute and HI Fellows Seminar presented a Fall 2017 topic, ‘The World at Our Doorsteps: Immigration and Deportation in Los Angeles’. Our purpose was to address how current federal government anti-immigration measures have affected many students of color, some of whom are immigrants, many of whom are related to and are friends with people who are impacted by the attitudes as well as the practices of the U.S. Citizenship and Immigration Services. In Spring 2018, we followed with the topic, ‘Exclusive Nationalisms: Global Migration and Immigration’. This addresses the rise of white supremacists who have ascended to position of power worldwide, in America, Europe, Russia, and xenophobic nationalisms in China, Myanmar and the Philippines. Recent scholarship has suggested the existence of categories of refugees beyond the political or social, who fit into the more inclusive category of migrants. ASSESSMENT METHODOLOGIES: Assessment methodologies not only included qualitative student interviews and quantitative student evaluations in standard rubric format, but also Outcome Assessments, Formative Evaluations, and Outside Guest Teacher feedback. These indicated that the most effective educational practices involved collaborative inquiry in undergraduate research, community-based learning, and capstone projects. Assessments of E-portfolios, written and oral coursework, and final creative projects with associated 10-12 page analytic paper revealed that students developed their understanding of how government and social organizations work; they developed communication skills that enhanced working with others from different backgrounds; they developed their ability to thoughtfully evaluate their course performance by adopting reflective practices; they gained analytic and interpretive skills that encouraged self-confidence and self- initiative not only academically, but also with regards to independent projects. CONCLUSION: Most importantly, the Scripps Humanities Institute experiential learning project spurred on real-world actions by our students, such as a public symposium on how to cope with bigots, a student tutoring program for immigrant staff children, student negotiations with the administration to establish meaningful, sustainable diversity and inclusion programs on-campus. Activism is not only to be taught to and for our students– it has to be enacted by our students.

Keywords: immigration, migration, human rights, learning assessment

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Maria T. Cruz, Scott N. Thompson

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In recent years, Canadian federal and provincial law enforcement organizations have implemented numerous mental health strategies in an attempt to address officers’ mental health and wellness needs. Despite these reforms, however, mental illness continues to persist in these populations. Whereas workplace stressors continue to be factored into the development of mental health initiatives, it is proposed that aspects of masculine culture have been overlooked as contributing to the prevalence of mental illness among Canadian officers. By drawing on Michel Foucault’s theory of discourse, this study was conducted to determine if elements of masculine discourse exist as a socio-cultural barrier for officers seeking mental health assistance. This research supported the above hypothesis, and furthermore, identified how masculine discourse works in competition with mental health-related help-seeking discourses. To answer the research question, semi-structured phone interviews with active and retired male officers from Western provincial and municipal policing organizations, and the Royal Canadian Mounted Police were employed. Through thematic analysis of the transcripts, the data revealed three themes: i) masculinity in law enforcement is a determinant of workplace competency; ii) the dominance of masculine culture in law enforcement is problematic for mental health, and iii) improved help-seeking policies complicate how masculinity is expressed in law enforcement organizations. These findings suggest that within the reviewed Canadian law enforcement organizations, aspects of masculinity act as a socio-cultural barrier to officers seeking mental health services, and that the two conflicting discourses of masculinity and mental health-related help-seeking appear to be in competition with each other.

Keywords: competing discourses, dominant discourses, Foucault’s theory of discourse, law enforcement, masculinity, mental health, police officers

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Authors: Clifford Irikefe Gbeyonron

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Applied linguists concur that there is low-level achievement in English language use among Nigerian secondary school students. One of the factors that exacerbate this is classroom feature of which large class size is obvious. This study investigated the impact of large classes on learning English as a second language (ESL) at junior secondary school (JSS) in Yobe State. To achieve this, Solomon four-group experimental design was used. 382 subjects were divided into four groups and taught ESL for thirteen weeks. 356 subjects wrote the post-test. Data from the systematic observation and post-test were analyzed via chi square and ANOVA. Results indicated that learners in large classes (LLC) attain lower linguistic progress than learners in small classes (LSC). Furthermore, LSC have more chances to access teacher evaluation and participate actively in classroom discourse than LLC. In consequence, large classes have adverse effects on learning ESL in Yobe State. This is inimical to English language education given that each learner of ESL has their individual peculiarity within each class. It is recommended that strategies that prioritize individualization, grouping, use of language teaching aides, and theorization of innovative models in respect of large classes be considered.

Keywords: large classes, achievement, classroom discourse

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Authors: Zhao Luqian, Wang Yafei

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Participation in music activities is beneficial for enhancing wellbeing, especially for aged people (Creech, 2013). Looking at percussion group in particular, it can facilitate a sense of belonging, relaxation, energy, and productivity, learning, enhanced mood, humanising, seems of accomplishment, escape from trauma, and emotional expression (Newman, 2015). In health literatures, group drumming is effective in reducing stress and improving multiple domains of social-motional behaviors (Ho et al., 2011; Maschi et al., 2010) because it offers a creative and mutual learning space that allows patients to establish a positive peer interaction (Mungas et al., 2014; Perkins, 2016). However, very few studies have investigated the effect of group drumming from the aspect of patients’ needs. Therefore, this study focuses on the discussion of patients' specific needs within mental health and explores how group percussion may meet their needs. Seligman’s (2011) five core elements of mental health were applied as patients’ needs in this study: (1) Positive emotions; (2) Engagement; (3) Relationships; (4) Meaning and (5) Accomplishment. 12 participants aged 57- 80 years were interviewed individually. The researcher also had observation in four drumming groups simultaneously. The results reveal that group drumming could improve participants’ mental wellbeing. First, it created a therapeutic health care environment extending beyond the elimination of boredom, and patients could focus on positive emotions during the session of group drumming. Secondly, it was effective in satisfying patients’ level of engagement. Thirdly, this study found that joining a percussion group would require patients to work on skills such as turn-taking and sharing. This equal relationship is helpful for releasing patients’ negative mood and thus forming tighter relationships between and among them. Fourthly, group drumming was found to meet patients’ meaning needs through offering them a place of belonging and a place for sharing. Its leaner-oriented approach engaged patients by a sense of belonging, accepting, connecting, and ownership. Finally, group drumming could meet patients’ needs for accomplishment through the learning process. The inclusive learning process, which indicates there is no right or wrong throughout the process, allowed patients to make their own decisions. In conclusion, it is difficult for patients to achieve positive emotions, engagement, relationships, meanings, and accomplishments in a hospital setting. Drumming can be practiced for enhancement in terms of reducing patients’ negative emotions and improving their experiences in a hospital through enriched social interaction and sense of accomplishment. Also, it can help patients to enhance social skills in a controlled environment.

Keywords: group drumming, hospital, mental health, music psychology

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Apisit Nawapanpong, Natthapat Boonjerm

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This project aims to analyze and identify the flight plan of low-altitude aviation in Thailand and other countries. The development of UAV technology has led the innovation and revolution in the aviation industry; this includes the development of new modes of passenger or freight transportation, and it has also affected other industries widely. At present, this technology is being developed rapidly and has been tested all over the world to make the most efficient for technology or innovation, and it is likely to grow more extensively. However, no flight plan for low-altitude operation has been published by the government organization; when compared with high-altitude aviation with manned aircraft, various unique factors are different, whether mission, operation, altitude range or airspace restrictions. In the study of the essential components of low-altitude operation measures to be practical and tangible, there were major problems, so the main consideration of this project is to analyze the components of low-altitude operations which are conducted up to the altitudes of 400 ft or 120 meters above ground level referring to the terrain, for example, air traffic management, classification of aircraft, basic necessity and safety, and control area. This research will focus on confirming the theory through qualitative and quantitative research combined with theoretical modeling and regulatory framework and by gaining insights from various positions in aviation industries, including aviation experts, government officials, air traffic controllers, pilots, and airline operators to identify the critical essential components of low-altitude flight operation. This project analyzes by using computer programs for science and statistics research to prove that the result is equivalent to the theory and be beneficial for regulating the flight plan for low-altitude operation by different essential components from this project and can be further developed for future studies and research in aviation industries.

Keywords: low-altitude aviation, UAV technology, flight plan, air traffic management, safety measures

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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Authors: Majed A. Alsalem

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Universal Design for Learning (UDL) is common theme in education across the US and an influential model and framework that enables students in general and particularly students who are deaf and hard of hearing (DHH) to access the general education curriculum. UDL helps teachers determine how information will be presented to students and how to keep students engaged. Moreover, UDL helps students to express their understanding and knowledge to others. UDL relies on technology to promote students' interaction with content and their communication of knowledge. This study included 120 DHH students who received daily instruction based on UDL principles. This study presents the results of the study and discusses its implications for the integration of UDL in day-to-day practice as well as in the country's education policy. UDL is a Western concept that began and grew in the US, and it has just begun to transfer to other countries such as Saudi Arabia. It will be very important to researchers, practitioners, and educators to see how UDL is being implemented in a new place with a different culture. UDL is a framework that is built to provide multiple means of engagement, representation, and action and expression that should be part of curricula and lessons for all students. The purpose of this study is to investigate the variables associated with the implementation of UDL in Saudi Arabian schools and identify the barriers that could prevent the implementation of UDL. Therefore, this study used a mixed methods design that use both quantitative and qualitative methods. More insights will be gained by including both quantitative and qualitative rather than using a single method. By having methods that different concepts and approaches, the databases will be enriched. This study uses levels of collecting date through two stages in order to insure that the data comes from multiple ways to mitigate validity threats and establishing trustworthiness in the findings. The rationale and significance of this study is that it will be the first known research that targets UDL in Saudi Arabia. Furthermore, it will deal with UDL in depth to set the path for further studies in the Middle East. From a perspective of content, this study considers teachers’ implementation knowledge, skills, and concerns of implementation. This study deals with effective instructional designs that have not been presented in any conferences, workshops, teacher preparation and professional development programs in Saudi Arabia. Specifically, Saudi Arabian schools are challenged to design inclusive schools and practices as well as to support all students’ academic skills development. The total participants in stage one were 336 teachers of DHH students. The results of the intervention indicated significant differences among teachers before and after taking the training sessions associated with their understanding and level of concern. Teachers have indicated interest in knowing more about UDL and adopting it into their practices; they reported that UDL has benefits that will enhance their performance for supporting student learning.

Keywords: deaf and hard of hearing, professional development, Saudi Arabia, universal design for learning

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Authors: Aldila Dyas Nurfitri

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Nowadays, leadership has became the one of main issues in forming organization groups even countries. The concept of a social contract between the leaders and subordinates become one of the explanations for the leadership process. The interests of the two parties are not always the same, but they must work together to achieve both goals. Based on the concept at the previous it comes “The Leader Member Exchange Theory”—well known as LMX Theory, which assumes that leadership is a process of social interaction interplay between the leaders and their subordinates. High-quality LMX relationships characterized by a high carrying capacity, informal supervision, confidence, and power negotiation enabled, whereas low-quality LMX relationships are described by low support, large formal supervision, less or no participation of subordinates in decision-making, and less confidence as well as the attention of the leader Application of formal supervision system in a low LMX behavior was in line with strict controls on toxic leadership model. Leaders must be able to feel toxic control all aspects of the organization every time. Leaders with this leadership model does not give autonomy to the staff. This behavior causes stagnation and make a resistant organizational culture in an organization. In Indonesia, the pattern of toxic leadership later evolved into a dysfunctional system that is growing rapidly. One consequence is the emergence of corrupt behavior. According to Kellerman, corruption is defined as a pattern and some subordinates behave lie, cheat or steal to a degree that goes beyond the norm, they put self-interest than the common good.According to the corruption data in Indonesia based on the results of ICW research on 2012 showed that the local government sector ranked first with 177 cases. Followed by state or local enterprises as much as 41 cases. LMX is defined as the quality of the relationship between superiors and subordinates are implications for the effectiveness and progress of the organization. The assumption of this theory that leadership as a process of social interaction interplay between the leaders and his followers are characterized by a number of dimensions, such as affection, loyalty, contribution, and professional respect. Meanwhile, the toxic leadership is dysfunctional leadership in organization that is led by someone with the traits are not able to adjust, do not have integrity, malevolent, evil, and full of discontent marked by a number of characteristics, such as self-centeredness, exploiting others, controlling behavior, disrespecting others, suppress innovation and creativity of employees, and inadequate emotional intelligence. The leaders with some characteristics, such as high self-centeredness, exploiting others, controlling behavior, and disrespecting others, tends to describe a low LMX relationships directly with subordinates compared with low self-centeredness, exploiting others, controlling behavior, and disrespecting others. While suppress innovation and creativity of employees aspect and inadequate emotional intelligence, tend not to give direct effect to the low quality of LMX.

Keywords: leader-member exchange, toxic leadership, leadership

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Authors: Ana Martins, Isabel Martins

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The purpose of this research is to ascertain whether students at HEIs cultivate distributed leadership and higher-level skills to inspire knowledge creation. Critical reflection of extant literature illustrates the need for a culture of innovation in organizational sustainability. New age leadership behaviors harmonize innovation. The leadership self-efficacy construct supports organizational learning. This exploratory study applies the pragmatic paradigm methodology using the survey research method for primary data collection. A questionnaire was distributed to a sample of university students based in the Southern Anatolian region of Turkey, from both under and postgraduate Business degree programs. An analysis of the findings reveals a greater connection in influencing behavior relying more on the task-centered perspective rather than with the people perspective. These results reveal the need for HEIs to instill a humanistic perspective in curricula enabling graduates to be capable leaders with the awareness soft skills to energize creativity and innovation. A limitation of this research is that one university makes it difficult to generalize to a broader population. This study is of added value for scholars and organizations in the current knowledge and innovation economy.

Keywords: distributed leadership, exploration, higher education institutions, innovation, knowledge creation, learning, self-efficacy

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Authors: Sakinah Idris, Femke Ten Hoeve, Kirstin Greaves-Lord

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Background: Social skills interventions are considered to be efficacious if social skills are improved as a result of an intervention. Nevertheless, the objective assessment of social skills is hindered by a lack of sensitive and validated measures. To measure the change in social skills after an intervention, questionnaires reported by parents, clinicians and/or teachers are commonly used. Observations are the most ecologically valid method of assessing improvements in social skills after an intervention. For this purpose, The Program for the Educational and Enrichment of Relational Skills (PEERS) was developed for adolescents, in order to teach them the age-appropriate skills needed to participate in society. It is an evidence-based intervention for adolescents with ASD that taught ecologically valid social skills techniques. Objectives: The current study aims to describe the development and psychometric evaluation of the Dutch Contextual Assessment of Social Skills (CASS), an observational outcome measure of social skills for adolescents with Autism Spectrum Disorder (ASD). Methods: 64 adolescents (M = 14.68, SD = 1.41, 71% boys) with ASD performed the CASS before and after a social skills intervention (i.e. PEERS or the active control condition). Each adolescent completed a 3-minute conversation with a confederate. The conversation was prompt as a natural introduction between two-unfamiliar, similar ages, opposite-sex peers who meet for the first time. The adolescent and the confederate completed a brief questionnaire about the conversation (Conversation Rating Scale). Results: Results indicated sufficient psychometric properties. The Dutch CASS has a high level of internal consistency (Cronbach's α coefficients = 0.84). Data supported the convergent validity (i.e., significant correlated with the Social Skills Improvement System (SSiS). The Dutch CASS did not significantly correlate with the autistic mannerism subscale from Social Responsiveness Scale (SRS), thus proved the divergent validity. Based on scorings made by raters who were kept blind to the time points, reliable change index was computed to assess the change in social skills. With regard to the content validity, only the learning objectives of the first two meetings of PEERS about conversational skills relatively matched with rating domains of the CASS. Due to this underrepresentation, we found an existing observational measure (TOPICC) that covers some of the other learning objectives of PEERS. TOPICC covers 22% of the learning objectives of PEERS about conversational skills, meanwhile, CASS is 45%. Unfortunately, 33% of the learning objectives of PEERS was not covered by CASS or TOPICC. Conclusion: Recommendations are made to improve the psychometric properties and content validity of the Dutch CASS.

Keywords: autism spectrum disorder, observational, PEERS, social skills

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Authors: Khanita Limhan

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Due to the fact that the instructional media is a very crucial implement in English as Foreign Language (EFL) teaching and learning because it simply motivates or demotivates the learners to learn English. Furthermore, it could enormously involve the learners in the real language. The mixed-method research investigates undergraduate student teachers at the Faculty of Education in aspects of the preferences and attitudes towards the use of instructional media in a Thai EFL classroom. Therefore, there were 21 female and 4 male students, who are being educated to be secondary English teachers in Thai educational system, participated in this study. Moreover, the data was gathered from six open-ended questions; obviously, all were given at least 30 - 45 minutes to express their preferences and thoughts in their native tongue at the end of the English for English teacher course. The results of this study indicated that 64 % of student teachers preferred to study English grammar through songs and music; 54% of them desire to learn English grammar through English movies; and 40% of them want to acquire English grammar by watching short documentaries. Since, the participants illustrated that they feel neither anxious nor bored; however, they feel very excited and fun while studying. In addition, they pointed out that they could improve their listening proficiency; obtain new vocabulary; and comprehend the cultural content authentically from the instructional media. It can be concluded that the use of instructional media affects students and teachers’ motivations and attitudes on English teaching and learning.

Keywords: attitudes, preferences, student teachers, instructional media

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Authors: C. Rajalakshmi, Vibin Ipe Thomas

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Sonogashira coupling reactions are widely employed in the synthesis of molecules of biological and pharmaceutical importance. Copper catalyzed Sonogashira coupling reactions are gaining importance owing to the low cost and less toxicity of copper as compared to the palladium catalyst. In the present work, a detailed computational study has been carried out on the Sonogashira coupling reaction between aryl halides and terminal alkynes catalyzed by Copper (I) species with trans-1, 2 Diaminocyclohexane as ligand. All calculations are performed at Density Functional Theory (DFT) level, using the hybrid Becke3LYP functional. Cu and I atoms are described using an effective core potential (LANL2DZ) for the inner electrons and its associated double-ζ basis set for the outer electrons. For all other atoms, 6-311G+* basis set is used. We have identified that the active catalyst species is a neutral 3-coordinate trans-1,2 diaminocyclohexane ligated Cu (I) alkyne complex and found that the oxidative addition and reductive elimination occurs in a single step proceeding through one transition state. This is owing to the ease of reductive elimination involving coupling of Csp2-Csp carbon atoms and the less stable Cu (III) intermediate. This shows the mechanism of copper catalyzed Sonogashira coupling reactions are quite different from those catalyzed by palladium. To gain further insights into the mechanism, substrates containing various functional groups are considered in our study to traverse their effect on the feasibility of the reaction. We have also explored the effect of ligand on the catalytic cycle of the coupling reaction. The theoretical results obtained are in good agreement with the experimental observation. This shows the relevance of a combined theoretical and experimental approach for rationally improving the cross-coupling reaction mechanisms.

Keywords: copper catalysed, density functional theory, reaction mechanism, Sonogashira coupling

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Authors: Zwelenkani Mdlalose

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From the moment Covid 19 was declared a pandemic it became clear that conspiracy theories would significantly impact our response to the crisis that the virus was to become. Central to the interest in conspiracy theories evoked by a pandemic is a more general concern for the impact they have on society and social harmony. The specific brand of Conspiracy Theory that is in question is not any and all theories about conspiracies but rather those conspiracy theories which contradict official accounts. For example, where the official account on the terrorist attacks of September 11 2001 is of a conspiracy involving 19 militants associated with the Islamic extremist group al-Qaeda against targets in the United States, the nature of conspiracy theory under study is the one contradicting this official account to the extent that its attributes the attacks not to al-Qaeda militants but to actors in the United States government itself. The study is not an investigation into the truth value of conspiracy theories but rather an attempt at observing the essential qualities of the type of belief that is belief in conspiracy theories compared to belief in official accounts provided by authoritative sources such as governments, experts and mainstream media. These qualities include the psychological, epistemic and socio-political foundations on which belief in conspiracy theories are established. Based on a foundational understanding of the sort of belief that are beliefs in conspiracy theories, we may then extrapolate implied ethical demands on both authoritative bodies and actors as well as believers in conspiracy theories. For example: in their unofficial ‘non-factual’ status, is there not some violation of epistemic right in the same way we observe in cases where people are prejudiced because of their religious beliefs? In other words, is there an epistemic injustice suffered by believers in conspiracy theories in the way their beliefs are rejected as illegitimate? Conversely, to what extent do believers bear an epistemic responsibility in their adoption of their beliefs in conspiracy theories. From this position, perhaps we can then develop responses to the problem that foster greater social harmony even in the midst of suspicion and distrust.

Keywords: conspiracy theories, subjugated knowledge, epistemic injustice, epistemic responsibility

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Catherine Mary Abou-Zaid, Sandra Goodwin

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This study was conducted in a cardiac center in Bahrain. The rise in the amount of obese patients’ both men and women, being admitted for surgical procedures has become an issue to the nurses and doctors as these patients pose a high risk of major complications arising from their problem. The cessation of obesity in the country is very high and obesity-related diseases has been the cause of concern among men and women, also related individual diseases such as cardiovascular, diabetes and chronic respiratory diseases are rising dramatically within Bahrain in the last 10 years. Rationale for the Study: The ontological approach will help to understand and assess the true nature of the social world and how the world looks at obesity. Obesity has to be looked at as being a realistic ongoing issue. The epistemological approach will look at the theory of the origins of the nature of knowledge, set the rule of validating and learning in the social world of what can be done to curb this concept and how this can help prevent otherwise preventable diseases. Design Methodology: The qualitative design methodology took the form of an ontological/epistemological approach using phenomenology as a framework. The study was based on a social research issue, therefore, ontological ‘realism and idealism’ will feature as the nature of the world from a social and natural context. Epistemological positions of the study will be how we as researchers will find the actual social world and the limiting of that knowledge. The one-to-one interviews will be transcribed and the taped verbatim will be coded and charted giving the thematic analytic results. Recommendations: The significance of the research brought many recommendations. These recommendations were taken from the themes and sub-themes and were presented to the centers management and the necessary arrangements for updating knowledge and attitudes towards obesity in cardiac patients was then presented to the in-service education department. Workshops and training sessions on promoting health education were organized and put into the educational calendar for the next academic year. These sessions would look at patient autonomy, the patients’ rights, healthy eating for patients and families and the risks associated with obesity in cardiac disease processes.

Keywords: cardiac patients, diabetes, education & training, obesity cessation, qualitative

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Authors: Fan Yang, Ye-Lu Wang, Yang Zhao

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The dynamic load allowance, as an application result of the vehicle-bridge coupled vibration theory, is an important parameter for bridge design and evaluation. Based on the coupled vehicle-bridge vibration theory, the current work establishes a full girder model of a dynamic load allowance, selects a planar five-degree-of-freedom three-axis vehicle model, solves the coupled vehicle-bridge dynamic response using the APDL language in the spatial finite element program ANSYS, selects the pivot point 2 sections as the representative of the negative moment section, and analyzes the effects of parameters such as travel speed, unevenness, vehicle frequency, span diameter, span number and forced displacement of the support on the negative moment dynamic load allowance through orthogonal tests. The influence of parameters such as vehicle speed, unevenness, vehicle frequency, span diameter, span number, and forced displacement of the support on the negative moment dynamic load allowance is analyzed by orthogonal tests, and the influence law of each influencing parameter is summarized. It is found that the effects of vehicle frequency, unevenness, and speed on the negative moment dynamic load allowance are significant, among which vehicle frequency has the greatest effect on the negative moment dynamic load allowance; the effects of span number and span diameter on the negative moment dynamic load allowance are relatively small; the effects of forced displacement of the support on the negative moment dynamic load allowance are negligible.

Keywords: continuous T-girder bridge, dynamic load allowance, sensitivity analysis, vehicle-bridge coupling

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Authors: Michal Wolk, Bat-Sheva Hadad, Orly Rubinsten

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Objective: The visuospatial perception system process that allows us to decompose and recompose small quantities into a whole is often called “groupitizing.” Previous studies have been found that adults use groupitizing processes in quantity estimation tasks and link this ability of subgroups recognition to arithmetic proficiency. This pilot study examined if adults with math difficulties benefit from visuospatial grouping cues when asked to estimate the quantity of a given set. It also compared the tipping point in which a significant improvement occurs in adults with typical development compared to adults with math difficulties. Method: In this pilot research, we recruited adults with low arithmetic abilities and matched controls. Participants were asked to estimate the quantity of a given set. Different grouping cues were displayed (space, color, or none) with different visual configurations (different quantities-different shapes, same quantities- different shapes, same quantities- same shapes). Results: Both groups showed significant performance improvement when grouping cues appeared. However, adults with low arithmetic abilities benefited from the grouping cues already in very small quantities as four. Conclusion: impaired perceptual groupitizing abilities may be a characteristic of low arithmetic abilities.

Keywords: groupitizing, math learning disability, quantity estimation, visual perception system

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Authors: Sheila Santharamohana, Susan Bennett

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Historically, the attrition rates in secondary schools of Indigenous people or Orang Asli of Malaysia have been a cause for nationwide concern. Efforts to increase student engagement focusing on curriculum re-design and aid have not had the targeted impact. The scope of the research explored a change model incorporating project-based learning and wrap-around support through school-community partnerships to increase Orang Asli engagement, student outcomes and improve cultural connectedness. The evaluation methodology was mixed-method comprising a student questionnaire, interviews, and document analysis. Data and evidence were gathered from school staff, community, the Orang Asli governmental authority (JAKOA) and external agencies. Findings from the year-long research suggests shared values and goals in school-community partnerships foster responsive leadership and is key to safeguarding vulnerable Orang Asli, resulting in improved student outcomes. The research highlighted the barriers to the recognition and distinct needs and unique values of the Orang Asli that impact their educational equity and outcomes.

Keywords: Indigenous Education, Cultural Connectedness, School-Community Partnership, Student Outcomes

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