Search results for: continuous learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9238

Search results for: continuous learning

1018 Acoustic Radiation Force Impulse Elastography of the Hepatic Tissue of Canine Brachycephalic Patients

Authors: A. C. Facin, M. C. Maronezi , M. P. Menezes, G. L. Montanhim, L. Pavan, M. A. R. Feliciano, R. P. Nociti, R. A. R. Uscategui, P. C. Moraes

Abstract:

The incidence of brachycephalic syndrome (BS) in the clinical routine of small animals has increased significantly giving the higher proportion of brachycephalic pets in the last years and has been considered as an animal welfare problem. The treatment of BS is surgical and the clinical signs related can be considerably attenuated. Nevertheless, the systemic effects of the BS are still poorly reported and little is known about these when the surgical correction is not performed early. Affected dogs are more likely to develop cardiopulmonary, gastrointestinal and sleep disorders in which the chronic hypoxemia plays a major role. This syndrome is compared with the obstructive sleep apnea (OSA) in humans, both considered as causes of systemic and metabolic dysfunction. Among the several consequences of the BS little is known if the syndrome also affects the hepatic tissue of brachycephalic patients. Elastography is a promising ultrasound technique that evaluates tissue elasticity and has been recently used with the purpose of diagnosis of liver fibrosis. In medicine, it is a growing concern regarding the hepatic injury of patients affected by OSA. This prospective study hypothesizes if there is any consequence of BS in the hepatic parenchyma of brachycephalic dogs that don’t receive any surgical treatment. This study was conducted following the approval of the Animal Ethics and Welfare Committee of the Faculdade de Ciências Agrárias e Veterinárias, UNESP, Campus Jaboticabal, Brazil (protocol no 17944/2017) and funded by Sao Paulo Research Foundation (FAPESP, process no 2017/24809-4). The methodology was based in ARFI elastography using the ACUSON S2000/SIEMENS device, with convex multifrequential transducer and specific software as well as clinical evaluation of the syndrome, in order to determine if they can be used as a prognostic non-invasive tool. On quantitative elastography, it was collected three measures of shear wave velocity (meters per second) and depth in centimeters in the left lateral, left medial, right lateral, right medial and caudate lobe of the liver. The brachycephalic patients, 16 pugs and 30 french bulldogs, were classified using a previously established 4-point functional grading system based on clinical evaluation before and after a 3-minute exercise tolerance test already established and validated. The control group was based on the same features collected in 22 beagles. The software R version 3.3.0 was used for the analysis and the significance level was set at 0.05. The data were analysed for normality of residuals and homogeneity of variances by Shapiro-Wilks test. Comparisons of parametric continuous variables between breeds were performed by using ANOVA with a post hoc test for pair wise comparison. The preliminary results show significant statistic differences between the brachycephalic groups and the control group in all lobes analysed (p ≤ 0,05), with higher values of shear wave velocities in the hepatic tissue of brachycephalic dogs. In this context, the results obtained in this study contributes to the understanding of BS as well as its consequences in our patients, reflecting in evidence that one more systemic consequence of the syndrome may occur in brachycephalic patients, which was not related in the veterinary literature yet.

Keywords: airway obstruction, brachycephalic airway obstructive syndrome, hepatic injury, obstructive sleep apnea

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1017 International Tourists’ Travel Motivation by Push-Pull Factors and Decision Making for Selecting Thailand as Destination Choice

Authors: Siripen Yiamjanya, Kevin Wongleedee

Abstract:

This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: decision making, destination choice, international tourist, pull factor, push factor, Thailand, travel motivation

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1016 Maximizing the Role of Companion Teachers for the Achievement of Professional Competencies and Pedagogics Workshop Activities of Teacher Professional Participants in the Faculty of Teaching and Education of Mulawarman University

Authors: Makrina Tindangen

Abstract:

The problems faced by participants of teacher profession program in Faculty of teaching and education Mulawarman University is professional and pedagogic competence. Professional competence related to the mastery of teaching materials, while pedagogic competence related with the ability to plan and to implement learning. Based on the problems, the purpose of the research is to maximize the role of companion teacher for the achievement of professional and pedagogic competencies in the workshop of the participants of teacher professional education in the Faculty of Teaching and Education of Mulawarman University. Qualitative research method with interview guidance and document to get in-depth data on how to maximize the role of companion teachers in the achievement of professional and pedagogic competencies in the workshop participants of professional education participants. Location of this research is on the Faculty of Teaching and Education of Mulawarman University, Samarinda City, East Kalimantan Province. Research respondents were 12 teachers of workshop facilitator. Descriptive data analysis is through interpretation of interview data. The conclusion of the research result, how to maximize the role of assistant teachers in workshop activities for the professional competence and pedagogic competence of professional teacher training program participants, through facilitation activities conducted by teachers of companion related to real problems faced by students in school, so that the workshop participants have professional competence and pedagogic as an initial competence before carrying out practical activities of field experience in school.

Keywords: companion teacher, professional and pedagogical competence, activities, workshop participants

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1015 On the Existence of Homotopic Mapping Between Knowledge Graphs and Graph Embeddings

Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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1014 Becoming a Teacher in Kazakhstan

Authors: D. Shamatov

Abstract:

Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

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1013 Low Students' Access to University Education in Nigeria: Causes and Remedy

Authors: Robert Ogbanje Okwori

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The paper explained the causes low students’ access to university education in Nigeria and how it can be remedied. It is discovered that low students’ access to university education in Nigeria is evident despite these number of universities in the country. In 2006/2007 academic session, 806,089 sat for Joint Unified Matriculation Board Examination (JAMB) into Nigerian universities and only 123,626 (15.3%) were admitted while 2011/2012 academic session, a total of 1,493,604 candidates sat for Joint Unified Matriculation Board Examination (JAMB) into Nigerian universities and only 65,073 (43.57%) were admitted. This necessitates for the research. Therefore, the study posed the following research questions. What are causes of low students’ access to university education in Nigeria? What are the challenges of students’ access to university education in Nigeria? How can students’ access to university education in Nigeria be improved? Sample survey research design was adopted for the study. A structured questionnaire was used to gather data for the study. Six hundred and eighty (680) respondents which comprised of 100 level university students; JAMB Officers and University administrators (Vice Chancellors, Registrars and Admission Officers) were used for the study. Stratified random sampling was applied for adequate representation of respondents from universities in the six geopolitical zones of Nigeria. Mean was used to answer research questions while Kuder-Richardson formula 20 was used to check the internal consistency of the instrument. The correlation coefficient of the instrument was 0.87. The major findings include the carrying capacity of each university contributes to low students’ access to university education and academic staff were inadequate. From the analysis of the study, it is concluded that the rate of access to university education is low, therefore, every university should establish distance learning programme to reduce university admission crisis. The training infrastructure in the universities should be improved upon by the owners to increase the carrying capacity of each university.

Keywords: access, causes, low, university

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1012 Neuroecological Approach for Anthropological Studies in Archaeology

Authors: Kalangi Rodrigo

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The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

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1011 Vehicle Speed Estimation Using Image Processing

Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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1010 Awareness on Department of Education’s Disaster Risk Reduction Management Program at Oriental Mindoro National High School: Basis for Support School DRRM Program

Authors: Nimrod Bantigue

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The Department of Education is continuously providing safe teaching-learning facilities and hazard-free environments to the learners. To achieve this goal, teachers’ awareness of DepEd’s DRRM programs and activities is extremely important; thus, this descriptive correlational quantitative study was conceptualized. This research answered four questions on the profile and level of awareness of the 153 teacher respondents of Oriental Mindoro National High School for the academic year 2018-2019. Stratified proportional sampling was employed, and both descriptive and inferential statistics were utilized to treat data. The findings revealed that the majority of the teachers at OMNHS are female and are in the age bracket of 20-40. Most are married and pursue graduate studies. They have moderate awareness of the Department of Education’s DRRM programs and activities in terms of assessment of risks activities, planning activities, implementation activities during disaster and evaluation and monitoring activities with 3.32, 3.12, 3.40 and 3.31 as computed means, respectively. Further, the result showed a significant relationship between the profile of the respondents such as age, civil status and educational attainment and the level of awareness. On the contrary, sex does not have a significant relationship with the level of awareness. The Support School DRRM program with Utilization Guide on School DRRM Manual was proposed to increase, improve and strengthen the weakest areas of awareness rated in each DRRM activity, such as assessment of risks, planning, and implementation during disasters and monitoring and evaluation.

Keywords: awareness, management, monitoring, risk reduction

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1009 A Multiple Case Study of How Bilingual-Bicultural Teachers' Language Shame and Loss Affects Teaching English Language Learners

Authors: Lisa Winstead, Penny Congcong Wang

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This two-year multiple case study of eight Spanish-English speaking teachers explores bilingual-bicultural Latino teachers’ lived experiences as English Language Learners and, more recently, as adult teachers who work with English Language Learners in mainstream schools. Research questions explored include: How do bilingual-bicultural teachers perceive their native language use and sense of self within society from childhood to adulthood? Correspondingly, what are bilingual teachers’ perceptions of how their own language learning experience might affect teaching students of similar linguistic and cultural backgrounds? This study took place in an urban area in the Pacific Southwest of the United States. Participants were K-8 teachers and enrolled in a Spanish-English bilingual authorization program. Data were collected from journals, focus group interviews, field notes, and class artifacts. Within case and cross-case analysis revealed that the participants were shamed about their language use as children which contributed to their primary language loss. They similarly reported how experiences of mainstream educator and administrator language shaming invalidated their ability to provide support for Latino heritage ELLs, despite their bilingual-bicultural expertise. However, participants reported that counter-narratives from the bilingual authorization program, parents, community and church organizations, and cultural responsive teachers were effective in promoting their language retention, pride, and feelings of well-being.

Keywords: teacher education, bilingual education, English language learners, emergent bilinguals, social justice, language shame, language loss, translanguaging

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1008 Evaluation of Ensemble Classifiers for Intrusion Detection

Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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1007 A Study of Challenges Faced and Support Systems Available for Emirati Student Mothers Post-Childbirth

Authors: Martina Dickson, Lilly Tennant

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The young Emirati female university students of today are the first generation of women in the UAE for whom higher education as become not only a possibility, but almost an expectation. Young women in the UAE today make up around 77% of students in higher education institutes in the country. However, the societal expectations placed upon these women in terms of early marriage, child-bearing and rearing are similar to those placed upon their mothers and grandmothers in a time where women were not expected to go to university. A large proportion of female university students in the UAE are mothers of young children, or become mothers whilst at the university. This creates a challenging situation for young student mothers, where two weeks’ maternity leave is typical across institutions. The context of this study is in one such institution in the UAE. We have employed a mixed method approach to gathering interview data from twenty mothers, and survey data from over one hundred mothers. The main findings indicate that mothers have strong desires for their institution to support them more, for example by the provision of nursery facilities and resting areas for new mothers, and giving them greater flexibility over course selections and schedules including the provision of online learning. However, the majority felt supported on a personal level by their tutors. The major challenges which they identified in returning to college after only two weeks’ leave included the inevitable health and lack of sleep issues when caring for a newborn, struggling to catch up with missed college work and handling their course load. We also explored the women's’ home support systems which were provided from a variety of extended family, spouses and paid domestic help.

Keywords: student mothers, challenges, supports, United Arab Emirates

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1006 Construction of an Assessment Tool for Early Childhood Development in the World of DiscoveryTM Curriculum

Authors: Divya Palaniappan

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Early Childhood assessment tools must measure the quality and the appropriateness of a curriculum with respect to culture and age of the children. Preschool assessment tools lack psychometric properties and were developed to measure only few areas of development such as specific skills in music, art and adaptive behavior. Existing preschool assessment tools in India are predominantly informal and are fraught with judgmental bias of observers. The World of Discovery TM curriculum focuses on accelerating the physical, cognitive, language, social and emotional development of pre-schoolers in India through various activities. The curriculum caters to every child irrespective of their dominant intelligence as per Gardner’s Theory of Multiple Intelligence which concluded "even students as young as four years old present quite distinctive sets and configurations of intelligences". The curriculum introduces a new theme every week where, concepts are explained through various activities so that children with different dominant intelligences could understand it. For example: The ‘Insects’ theme is explained through rhymes, craft and counting corner, and hence children with one of these dominant intelligences: Musical, bodily-kinesthetic and logical-mathematical could grasp the concept. The child’s progress is evaluated using an assessment tool that measures a cluster of inter-dependent developmental areas: physical, cognitive, language, social and emotional development, which for the first time renders a multi-domain approach. The assessment tool is a 5-point rating scale that measures these Developmental aspects: Cognitive, Language, Physical, Social and Emotional. Each activity strengthens one or more of the developmental aspects. During cognitive corner, the child’s perceptual reasoning, pre-math abilities, hand-eye co-ordination and fine motor skills could be observed and evaluated. The tool differs from traditional assessment methodologies by providing a framework that allows teachers to assess a child’s continuous development with respect to specific activities in real time objectively. A pilot study of the tool was done with a sample data of 100 children in the age group 2.5 to 3.5 years. The data was collected over a period of 3 months across 10 centers in Chennai, India, scored by the class teacher once a week. The teachers were trained by psychologists on age-appropriate developmental milestones to minimize observer’s bias. The norms were calculated from the mean and standard deviation of the observed data. The results indicated high internal consistency among parameters and that cognitive development improved with physical development. A significant positive relationship between physical and cognitive development has been observed among children in a study conducted by Sibley and Etnier. In Children, the ‘Comprehension’ ability was found to be greater than ‘Reasoning’ and pre-math abilities as indicated by the preoperational stage of Piaget’s theory of cognitive development. The average scores of various parameters obtained through the tool corroborates the psychological theories on child development, offering strong face validity. The study provides a comprehensive mechanism to assess a child’s development and differentiate high performers from the rest. Based on the average scores, the difficulty level of activities could be increased or decreased to nurture the development of pre-schoolers and also appropriate teaching methodologies could be devised.

Keywords: child development, early childhood assessment, early childhood curriculum, quantitative assessment of preschool curriculum

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1005 The Implementation of Educational Partnerships for Undergraduate Students at Yogyakarta State University

Authors: Broto Seno

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This study aims to describe and examine more in the implementation of educational partnerships for undergraduate students at Yogyakarta State University (YSU), which is more focused on educational partnerships abroad. This study used descriptive qualitative approach. The study subjects consisted of a vice-rector, two staff education partnerships, four vice-dean, nine undergraduate students and three foreign students. Techniques of data collection using interviews and document review. Validity test of the data source using triangulation. Data analysis using flow models Miles and Huberman, namely data reduction, data display, and conclusion. Results of this study showed that the implementation of educational partnerships abroad for undergraduate students at YSU meets six of the nine indicators of the success of strategic partnerships. Six indicators are long-term, strategic, mutual trust, sustainable competitive advantages, mutual benefit for all the partners, and the separate and positive impact. The indicator has not been achieved is cooperative development, successful, and world class / best practice. These results were obtained based on the discussion of the four formulation of the problem, namely: 1) Implementation and development of educational partnerships abroad has been running good enough, but not maximized. 2) Benefits of the implementation of educational partnerships abroad is providing learning experiences for students, institutions of experience in comparison to each faculty, and improving the network of educational partnerships for YSU toward World Class University. 3) The sustainability of educational partnerships abroad is pursuing a strategy of development through improved management of the partnership. 4) Supporting factors of educational partnerships abroad is the support of YSU, YSU’s partner and society. Inhibiting factors of educational partnerships abroad is not running optimally management.

Keywords: partnership, education, YSU, institutions and faculties

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1004 A Pilot Study on Integration of Simulation in the Nursing Educational Program: Hybrid Simulation

Authors: Vesile Unver, Tulay Basak, Hatice Ayhan, Ilknur Cinar, Emine Iyigun, Nuran Tosun

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The aim of this study is to analyze the effects of the hybrid simulation. In this simulation, types standardized patients and task trainers are employed simultaneously. For instance, in order to teach the IV activities standardized patients and IV arm models are used. The study was designed as a quasi-experimental research. Before the implementation an ethical permission was taken from the local ethical commission and administrative permission was granted from the nursing school. The universe of the study included second-grade nursing students (n=77). The participants were selected through simple random sample technique and total of 39 nursing students were included. The views of the participants were collected through a feedback form with 12 items. The form was developed by the authors and “Patient intervention self-confidence/competence scale”. Participants reported advantages of the hybrid simulation practice. Such advantages include the following: developing connections between the simulated scenario and real life situations in clinical conditions; recognition of the need for learning more about clinical practice. They all stated that the implementation was very useful for them. They also added three major gains; improvement of critical thinking skills (94.7%) and the skill of making decisions (97.3%); and feeling as if a nurse (92.1%). In regard to the mean scores of the participants in the patient intervention self-confidence/competence scale, it was found that the total mean score for the scale was 75.23±7.76. The findings obtained in the study suggest that the hybrid simulation has positive effects on the integration of theoretical and practical activities before clinical activities for the nursing students.

Keywords: hybrid simulation, clinical practice, nursing education, nursing students

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1003 Real-Time Inventory Management and Operational Efficiency in Manufacturing

Authors: Tom Wanyama

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We have developed a weight-based parts inventory monitoring system utilizing the Industrial Internet of Things (IIoT) to enhance operational efficiencies in manufacturing. The system addresses various challenges, including eliminating downtimes caused by stock-outs, preventing human errors in parts delivery and product assembly, and minimizing motion waste by reducing unnecessary worker movements. The system incorporates custom QR codes for simplified inventory tracking and retrieval processes. The generated data serves a dual purpose by enabling real-time optimization of parts flow within manufacturing facilities and facilitating retroactive optimization of stock levels for informed decision-making in inventory management. The pilot implementation at SEPT Learning Factory successfully eradicated data entry errors, optimized parts delivery, and minimized workstation downtimes, resulting in a remarkable increase of over 10% in overall equipment efficiency across all workstations. Leveraging the IIoT features, the system seamlessly integrates information into the process control system, contributing to the enhancement of product quality. This approach underscores the importance of effective tracking of parts inventory in manufacturing to achieve transparency, improved inventory control, and overall profitability. In the broader context, our inventory monitoring system aligns with the evolving focus on optimizing supply chains and maintaining well-managed warehouses to ensure maximum efficiency in the manufacturing industry.

Keywords: industrial Internet of things, industrial systems integration, inventory monitoring, inventory control in manufacturing

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1002 Leadership Development for Nurses as Educators

Authors: Abeer Alhazmi

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Introduction: Clinical education is considered a significant part of the learning process for nurses and nursing students. However, recruiting high- caliber individuals to train them to be tomorrow’s educators/teachers has been a recurrent challenge. One of the troubling challenges in this field is the absent of proper training programmes to train educators to be future education professionals and leaders. Aim: To explore the impact of a stage 1 and stage 2 clinical instructor courses on developing leadership skills for nurses as educators.Theoretical Framework: Informed by a symbolic interactionist framework, this research explored the Impact of stage 1 and stage 2 clinical instructor courses on nurses' knowledge, attitudes, and leadership skills. Method: Using Glaserian grounded theory method the data were derived from 3 focus groups and 15 in-depth interviews with nurse educators/clinical instructors and nurses who attended stage 1 and stage 2 clinical instructor courses at King Abdu-Aziz University Hospital (KAUH). Findings: The findings of the research are represented in the core category exploring new identity as educator and its two constituent categories Accepting change, and constructing educator identity. The core and sub- categories were generated through a theoretical exploration of the development of educator’s identity throughout stage 1 and stage 2 clinical instructor courses. Conclusion: The social identity of the nurse educators was developed and changed during and after attending stage 1 and stage 2 clinical instructor courses. In light of an increased understanding of the development process of educators identity and role, the research presents implications and recommendations that may contribute to the development of nursing educators in general and in Saudi Arabia in specific.

Keywords: clinical instructor course, educators, identity work, clinical nursing

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1001 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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1000 Intelligent Fault Diagnosis for the Connection Elements of Modular Offshore Platforms

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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999 Learners’ Violent Behaviour and Drug Abuse as Major Causes of Tobephobia in Schools

Authors: Prakash Singh

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Many schools throughout the world are facing constant pressure to cope with the violence and drug abuse of learners who show little or no respect for acceptable and desirable social norms. These delinquent learners tend to harbour feelings of being beyond reproach because they strongly believe that it is well within their rights to engage in violent and destructive behaviour. Knives, guns, and other weapons appear to be more readily used by them on the school premises than before. It is known that learners smoke, drink alcohol, and use drugs during school hours, hence, their ability to concentrate, work, and learn, is affected. They become violent and display disruptive behaviour in their classrooms as well as on the school premises, and this atrocious behaviour makes it possible for drug dealers and gangsters to gain access onto the school premises. The primary purpose of this exploratory quantitative study was therefore to establish how tobephobia (TBP), caused by school violence and drug abuse, affects teaching and learning in schools. The findings of this study affirmed that poor discipline resulted in producing poor quality education. Most of the teachers in this study agreed that educating learners who consumed alcohol and other drugs on the school premises resulted in them suffering from TBP. These learners are frequently abusive and disrespectful, and resort to violence to seek attention. As a result, teachers feel extremely demotivated and suffer from high levels of anxiety and stress. The word TBP will surely be regarded as a blessing by many teachers throughout the world because finally, there is a word that will make people sit up and listen to their problems that cause real fear and anxiety in schools.

Keywords: aims and objectives of quality education, debilitating effects of tobephobia, fear of failure associated with education, learners' violent behaviour and drug abuse

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998 Sustainable Energy Supply through the Microgrid Concept: A Case Study of University of Nigeria, Nsukka

Authors: Christian Ndubisi Madu, Benjamin C. Ozumba, Ifeanyi E. Madu, Valentine E. Nnadi, Ikenna C. Ezeasor

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The ability to generate power and achieve energy security is one of the driving forces behind the emerging ‘microgrid’ concept. Traditional power supply often operates with centralized infrastructure for generating, transmitting and distributing electricity. The inefficiency and the incessant power outages associated with the centralized power supply system in Nigeria has alienated many users who frequently turn to electric power generator sets to power their homes and offices. Such acts are unsustainable and lead to increase in the use of fossil fuels, generation of carbon dioxide emissions and other gases, and noise pollution. They also pose significant risks as they entail random purchases and storage of gasolines which are fire hazards. It is therefore important that organizations rethink their relationships to centralized power suppliers in other to improve energy accessibility and security. This study explores the energy planning processes and learning taking place at the University of Nigeria Enugu Campus as the school lead microgrid feasibility studies in its community. There is need to develop community partners to deal with the issue of energy efficiency and also to create a strategic alliance to confront political, regulatory and economic barriers to locally-based energy planning. Community-based microgrid can help to reduce the cost of adoption and diversify risks. This study offers insights into the ways in which microgrids can further democratize energy planning, procurement, and access, while simultaneously promoting efficiency and sustainability.

Keywords: microgrid, energy efficiency, sustainability, energy security

Procedia PDF Downloads 375
997 Exploring Data Stewardship in Fog Networking Using Blockchain Algorithm

Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

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IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

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996 Magnesium Nanoparticles for Photothermal Therapy

Authors: E. Locatelli, I. Monaco, R. C. Martin, Y. Li, R. Pini, M. Chiariello, M. Comes Franchini

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Despite the many advantages of application of nanomaterials in the field of nanomedicine, increasing concerns have been expressed on their potential adverse effects on human health. There is urgency for novel green strategies toward novel materials with enhanced biocompatibility using safe reagents. Photothermal ablation therapy, which exploits localized heat increase of a few degrees to kill cancer cells, has appeared recently as a non-invasive and highly efficient therapy against various cancer types; anyway new agents able to generate hyperthermia when irradiated are needed and must have precise biocompatibility in order to avoid damage to healthy tissues and prevent toxicity. Recently, there has been increasing interest in magnesium as a biomaterial: it is the fourth most abundant cation in the human body, and it is essential for human metabolism. However magnesium nanoparticles (Mg NPs) have had limited diffusion due to the high reduction potential of magnesium cations, which makes NPs synthesis challenging. Herein, we report the synthesis of Mg NPs and their surface functionalization for the obtainment of a stable and biocompatible nanomaterial suitable for photothermal ablation therapy against cancer. We synthesized the Mg crystals by reducing MgCl2 with metallic lithium and exploiting naphthalene as an electron carrier: the lithium–naphthalene complex acts as the real reducing agent. Firstly, the nanocrystal particles were coated with the ligand 12-ethoxy ester dodecanehydroxamic acid, and then entrapped into water-dispersible polymeric micelles (PMs) made of the FDA-approved PLGA-b-PEG-COOH copolymer using the oil-in-water emulsion technique. Lately, we developed a more straightforward methodology by introducing chitosan, a highly biocompatible natural product, at the beginning of the process, simultaneously using lithium–naphthalene complex, thus having a one-pot procedure for the formation and surface modification of MgNPs. The obtained MgNPs were purified and fully characterized, showing diameters in the range of 50-300 nm. Notably, when coated with chitosan the particles remained stable as dry powder for more than 10 months. We proved the possibility of generating a temperature rise of a few to several degrees once MgNPs were illuminated using a 810 nm diode laser operating in continuous wave mode: the temperature rise resulted significant (0-15 °C) and concentration dependent. We then investigated potential cytotoxicity of the MgNPs: we used HN13 epithelial cells, derived from a head and neck squamous cell carcinoma and the hepa1-6 cell line, derived from hepatocellular carcinoma and very low toxicity was observed for both nanosystems. Finally, in vivo photothermal therapy was performed on xenograft hepa1-6 tumor bearing mice: the animals were treated with MgNPs coated with chitosan and showed no sign of suffering after the injection. After 12 hours the tumor was exposed to near-infrared laser light. The results clearly showed an extensive damage to tumor tissue after only 2 minutes of laser irradiation at 3Wcm-1, while no damage was reported when the tumor was treated with the laser and saline alone in control group. Despite the lower photothermal efficiency of Mg with respect to Au NPs, we consider MgNPs a promising, safe and green candidate for future clinical translations.

Keywords: chitosan, magnesium nanoparticles, nanomedicine, photothermal therapy

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995 A Review of Research on Pre-training Technology for Natural Language Processing

Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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994 Entrepreneurship Education as an Enhancement of Skills for Graduate Employability: The Case of the University of Buea

Authors: Akumeyam Elvis Akum, Njanjo Thecla Anyongo Mukete, Fonkeng George Epah

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Globally, the goal of higher education is to enhance graduate employability skills. Paradoxically, Cameroon’s graduate employability rate is far below the graduation rate. This worrisome situation caused the researcher to hypothesize that the teaching and learning experiences account for this increasing disparity. The study sought to investigate the effect on graduate employability of the teaching of organizational, problem-solving, innovation, and risk management skills on graduate employability. The study adopted a descriptive survey design with a quantitative approach. Data was collected by quantitative techniques from a random sample of 385 graduates using closed-ended structured questionnaire. Generally, findings revealed that entrepreneurship education does not sufficiently enhance graduate employability in the University of Buea. Specifically, the teaching of organizational skills does not significantly enhance their employability, as an average of 55% of graduates indicated that the course did not sufficiently help them develop skills for planning, management of limited resources, collaboration, and the setting of priorities. Also, 60% of the respondents indicated that the teaching of problem-solving skills does not significantly enhance graduate employability at the University of Buea. Contrarily, 57% of the respondents agreed that through their experiences in entrepreneurship education, their innovation skills were improved. The study recommended that a practical approach to teaching should be adopted, with attention to societal needs. A framework to ensure the teaching of entrepreneurship to students at the undergraduate level is recommended, such that those who do not continue with university studies after their Bachelor’s degree would have acquired the needed skills for employability.

Keywords: employability, entrepreneurship education, graduate, innovative skills, organizational skills, problem-solving skills, risk management skills

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993 Clustering for Detection of the Population at Risk of Anticholinergic Medication

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

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992 The Impact of the Macro-Level: Organizational Communication in Undergraduate Medical Education

Authors: Julie M. Novak, Simone K. Brennan, Lacey Brim

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Undergraduate medical education (UME) curriculum notably addresses micro-level communications (e.g., patient-provider, intercultural, inter-professional), yet frequently under-examines the role and impact of organizational communication, a more macro-level. Organizational communication, however, functions as foundation and through systemic structures of an organization and thereby serves as hidden curriculum and influences learning experiences and outcomes. Yet, little available research exists fully examining how students experience organizational communication while in medical school. Extant literature and best practices provide insufficient guidance for UME programs, in particular. The purpose of this study was to map and examine current organizational communication systems and processes in a UME program. Employing a phenomenology-grounded and participatory approach, this study sought to understand the organizational communication system from medical students' perspective. The research team consisted of a core team and 13 medical student co-investigators. This research employed multiple methods, including focus groups, individual interviews, and two surveys (one reflective of focus group questions, the other requesting students to submit ‘examples’ of communications). To provide context for student responses, nonstudent participants (faculty, administrators, and staff) were sampled, as they too express concerns about communication. Over 400 students across all cohorts and 17 nonstudents participated. Data were iteratively analyzed and checked for triangulation. Findings reveal the complex nature of organizational communication and student-oriented communications. They reveal program-impactful strengths, weaknesses, gaps, and tensions and speak to the role of organizational communication practices influencing both climate and culture. With regard to communications, students receive multiple, simultaneous communications from multiple sources/channels, both formal (e.g., official email) and informal (e.g., social media). Students identified organizational strengths including the desire to improve student voice, and message frequency. They also identified weaknesses related to over-reliance on emails, numerous platforms with inconsistent utilization, incorrect information, insufficient transparency, assessment/input fatigue, tacit expectations, scheduling/deadlines, responsiveness, and mental health confidentiality concerns. Moreover, they noted gaps related to lack of coordination/organization, ambiguous point-persons, student ‘voice-only’, open communication loops, lack of core centralization and consistency, and mental health bridges. Findings also revealed organizational identity and cultural characteristics as impactful on the medical school experience. Cultural characteristics included program size, diversity, urban setting, student organizations, community-engagement, crisis framing, learning for exams, inefficient bureaucracy, and professionalism. Moreover, they identified system structures that do not always leverage cultural strengths or reduce cultural problematics. Based on the results, opportunities for productive change are identified. These include leadership visibly supporting and enacting overall organizational narratives, making greater efforts in consistently ‘closing the loop’, regularly sharing how student input effects change, employing strategies of crisis communication more often, strengthening communication infrastructure, ensuring structures facilitate effective operations and change efforts, and highlighting change efforts in informational communication. Organizational communication and communications are not soft-skills, or of secondary concern within organizations, rather they are foundational in nature and serve to educate/inform all stakeholders. As primary stakeholders, students and their success directly affect the accomplishment of organizational goals. This study demonstrates how inquiries about how students navigate their educational experience extends research-based knowledge and provides actionable knowledge for the improvement of organizational operations in UME.

Keywords: medical education programs, organizational communication, participatory research, qualitative mixed methods

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991 School Partners in Initial Teacher Education: An Including or Excluding Approach When Engaging Schools

Authors: Laila Niklasson

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The aim of the study is to critically discuss how partner schools are engaged during Initial teacher education, ITE. The background is an experiment in Sweden where the practicum organization is reorganized due to a need to enhance quality during practicum. It is a national initiative from the government, supported by the National Agency of Education and lasts 2014-2019. The main features are concentration of students to school with a certain amount of mentors, mentors who have a mentor education and teachers with relevant subject areas and where there could be a mentor team with a leader at the school. An expected outcome is for example that the student teachers should be engaged in peer-learning. The schools should be supported by extra lectures from university teachers during practicum and also extra research projects where the schools should be engaged. A case study of one university based ITE was carried out to explore the consequences for the schools not selected. The result showed that from engaging x schools in a region, x was engaged. The schools are both in urban and rural areas, mainly in the latter. There is also a tendency that private schools are not engaged. On a unit level recruitment is perceived as harder for schools not engaged. In addition they cannot market themselves as ´selected school´ which can affect parent´s selection of school for their children. Also, on unit level, but with consequences for professional development, they are not selected for research project and thereby are not fully supported during school development. The conclusion is that from an earlier inclusive approach concerning professions where all teachers were perceived as possible mentors, there is a change to an exclusive approach where selected schools and selected teachers should be engaged. The change could be perceived as a change in governance mentality, but also in how professions are perceived, and development work is pursued.

Keywords: initial teacher education, practicum schools, profession, quality development

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990 Measuring Principal and Teacher Cultural Competency: A Need Assessment of Three Proximate PreK-5 Schools

Authors: Teresa Caswell

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Throughout the United States and within a myriad of demographic contexts, students of color experience the results of systemic inequities as an academic outcome. These disparities continue despite the increased resources provided to students and ongoing instruction-focused professional learning received by teachers. The researcher postulated that lower levels of educator cultural competency are an underlying factor of why resource and instructional interventions are less effective than desired. Before implementing any type of intervention, however, cultural competency needed to be confirmed as a factor in schools demonstrating academic disparities between racial subgroups. A needs assessment was designed to measure levels of individual beliefs, including cultural competency, in both principals and teachers at three neighboring schools verified to have academic disparities. The resulting mixed method study utilized the Optimal Theory Applied to Identity Development (OTAID) model to measure cultural competency quantitatively, through self-identity inventory survey items, with teachers and qualitatively, through one-on-one interviews, with each school’s principal. A joint display was utilized to see combined data within and across school contexts. Each school was confirmed to have misalignments between principal and teacher levels of cultural competency beliefs while also indicating that a number of participants in the self-identity inventory survey may have intentionally skipped items referencing the term oppression. Additional use of the OTAID model and self-identity inventory in future research and across contexts is needed to determine transferability and dependability as cultural competency measures.

Keywords: cultural competency, identity development, mixed-method analysis, needs assessment

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989 Automated Fact-Checking by Incorporating Contextual Knowledge and Multi-Faceted Search

Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

Procedia PDF Downloads 62