Search results for: L2 language learning

Authors: Nurten Çelik

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Under the new developments in science, medicine, sociology, psychology and literary theories, body studies has gained huge importance and the body has become a debatable issue. There has emerged, among sociologists and literary theorists, an overwhelming consensus that body is socially, politically and culturally perceived and constructed and thus, the position of an individual in the society is determined in accordance with his/her body image. In this regard, the most complicated point is the theoretical views propounded upon disability studies, where the disabled body is considered to be a site upon which social and political restrictions as well as repressions are inscribed. There has been the widely-accepted view that no matter what kind of disability it is, those with physical, mental or learning impairments face varied social, political and environmental obstacles that prevent them from being an active citizen, worker, lover and even a family member. In parallel with these approaches, the matter of the sufferings of disabled individuals attains its place in cinema and literature as well as in theatre studies under the category of disability theatre. One of the prominent plays that deal with physical disability came from the contemporary British playwright Nina Raine. In her awarded play Tribes, which premiered at the Royal Court Theatre in 2010, Raine develops the social strata where her deaf protagonist, Billy, caught up between two tribes – namely his family and his lover Slyvia, a member of the deaf community– experiences personal and social hardships due to his hearing impairment. In the play, intransigent and self-opinionated family members foster no sense of empathy towards Billy, there are noisy talking and shouting, but no communication, love, compassion or mutual understanding, and language becomes just a tool for the expression of rage and oppression. In the disordered atmosphere of the family life, Billy experiences isolation and loneliness. Billy’s hopes for success and love are destroyed when Slyvia, troubled between hearing and deafness, rejects him because she does not utterly grasp what Billy is experiencing. Drawing upon the hardships, Billy undergoes in his relationships with his family and his girlfriend, Tribes problematizes the concept of deafness and explores to what extent a deaf person can find a place in the hearing world. Setting ‘the disabled’ bodies against ‘the abled’ bodies in a family, a microcosm of the society where bodies are socially shaped and constructed, Tribes dramatizes how the disabled bodies are disenfranchised, stigmatised, marginalized and othered on the grounds that they are socially misfit. Tribes, with a specific focus on the dysfunctional family, shows that the lack of communication and empathy numbs the characters to the feelings of each other and thereby, they become more disabled than Billy. In conclusion, this paper, with the reference to the embodiment of disability and social theories, aims to explore how disabled bodies are socially marked and segregated from family and society.

Keywords: body, deafness, disability, disability theatre, Nina Raine, tribes

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Authors: Mohamed M. El-Awad

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This paper describes an educational platform for design analyses of pump-pipe systems by using Microsoft Excel, its Solver add-in, and the associated VBA programming language. The paper demonstrates the capabilities of the Excel-based platform that suits the iterative nature of the design process better than the use of design charts and data tables. While VBA is used for the development of a user-defined function for determining the standard pipe diameter, Solver is used for optimising the pipe diameter of the pipeline and for determining the operating point of the selected pump.

Keywords: design analyses, pump-pipe systems, Excel, solver, VBA

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Authors: Pardeep Singh, N. S. Johal

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In this research paper the level of subjectivity and objectivity adopted by journalists of different newspapers of the two provinces of the Jammu and Kashmir state has been analysed. This research paper emphasized upon the professionalism of the journalists of two provinces in catering to readers of particular province. In this study it was found that Kashmir based reporters are subjective in their reporting while covering Kashmir sentiments and use hard language against New Delhi, whereas Jammu based reporters are subjective only when it comes to defend security forces and are also bitterly critical of Pakistan, accusing it of being a sponsor of violence in Kashmir.

Keywords: conflict, Jammu and Kashmir, print media, reporter, critical, violence

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Authors: R. Rahmoun-Mrabet

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It is acknowledged that our style of speaking changes according to a wide range of variables such as gender, setting, the age of both the addresser and the addressee, the conversation topic, and the aim of the interaction. These differences in style are noticeable in monolingual and multilingual speech communities. Yet, they are more observable in speech communities where two or more codes coexist. The linguistic situation in Algeria reflects a state of bilingualism because of the coexistence of Arabic and French. Nevertheless, like all Arab countries, it is characterized by diglossia i.e. the concomitance of Modern Standard Arabic (MSA) and Algerian Arabic (AA), the former standing for the ‘high variety’ and the latter for the ‘low variety’. The two varieties are derived from the same source but are used to fulfil distinct functions that is, MSA is used in the domains of religion, literature, education and formal settings. AA, on the other hand, is used in informal settings, in everyday speech. French has strongly affected the Algerian language and culture because of the historical background of Algeria, thus, what can easily be noticed in Algeria is that everyday speech is characterized by code-switching from dialectal Arabic and French or by the use of borrowings. Tamazight is also very present in many regions of Algeria and is the mother tongue of many Algerians. Yet, it is not used in the west of Algeria, where the study has been conducted. The present work, which was directed in the speech community of Tlemcen-Algeria, aims at depicting some of the outcomes of the contact of Arabic with French such as code-switching, borrowing and interference. The question that has been asked is whether Algerians are aware of their use of borrowings or not. Three steps are followed in this research; the first one is to depict the sociolinguistic situation in Algeria and to describe the linguistic characteristics of the dialect of Tlemcen, which are specific to this city. The second one is concerned with data collection. Data have been collected from 57 informants who were given questionnaires and who have then been classified according to their age, gender and level of education. Information has also been collected through observation, and note taking. The third step is devoted to analysis. The results obtained reveal that most Algerians are aware of their use of borrowings. The present work clarifies how words are borrowed from French, and then adapted to Arabic. It also illustrates the way in which singular words inflect into plural. The results expose the main characteristics of borrowing as opposed to code-switching. The study also clarifies how interference occurs at the level of nouns, verbs and adjectives.

Keywords: bilingualism, borrowing, code-switching, interference, language contact

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Authors: Masanori Kimura

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Due to the decline of the 18-year-old population, Japanese universities have a tendency to convert their form of employment from tenured positions to fixed-term positions for newly hired teachers. The advantage of this is that universities can be more flexible in their employment plans in case they fail to fill the enrollment of quotas of prospective students or they need to supplement teachers who can engage in other academic fields or research areas where new demand is expected. The most serious disadvantage of this, however, is that if secure positions cannot be provided to faculty members, there is the possibility that coherence of education and continuity of research supported by the university cannot be achieved. Therefore, the question of this presentation is as follows: Are universities aiming to give first priority to management, or are they trying to prioritize educational and research rather than management? To answer this question, the author examined the number of job offerings for college foreign language teachers posted on the JREC-IN (Japan Research Career Information Network, which is run by Japan Science and Technology Agency) website from April 2012 to October 2015. The results show that there were 1,002 and 1,056 job offerings for tenured positions and fixed-term contracts respectively, suggesting that, overall, today’s Japanese universities show a tendency to give first priority to management. More detailed examinations of the data, however, show that the tendency slightly varies depending on the types of universities. National universities which are supported by the central government and state universities which are supported by local governments posted more job offerings for tenured positions than for fixed-term contracts: national universities posted 285 and 257 job offerings for tenured positions and fixed-term contracts respectively, and state universities posted 106 and 86 job offerings for tenured positions and fixed-term contracts respectively. Yet the difference in number between the two types of employment status at national and state universities is marginal. As for private universities, they posted 713 job offerings for fixed-term contracts and 616 offerings for tenured positions. Moreover, 73% of the fixed-term contracts were offered for low rank positions including associate professors, lectures, and so forth. Generally speaking, those positions are offered to younger teachers. Therefore, this result indicates that private universities attempt to cut their budgets yet expect the same educational effect by hiring younger teachers. Although the results have shown that there are some differences in personal strategies among the three types of universities, the author argues that all three types of universities may lose important human resources that will take a pivotal role at their universities in the future unless they urgently review their employment strategies.

Keywords: higher education, management, employment status, foreign language education

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a formalized modeling language that was introduced back around 50-60 years, have been widely used for modeling discrete event dynamic systems and simulating their behavior. Reachability analysis of Petri nets gives many insights into a modeled system. This idea leads us to study the reachability technique and use it in the reachability problem in the state space of reachable markings. With the same concept, Crisp Boolean Petri nets were defined in which the marking vectors that are boolean are distinct in the reachability analysis of the nets. We generalize the concept and define ‘Crisp’ Petri nets that generate the marking vectors exactly once in their reachability-based analysis, not necessarily Boolean.

Keywords: marking vector, n-vector, Petri nets, reachability

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Lik Hang Gary Wong

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Background: Practice learning is crucial for preparing the healthcare profession to meet the real challenge upon graduation. Students are required to demonstrate their competence in managing interpersonal challenges, such as teamwork with other professionals and communicating well with the service users, during the placement. Such competence precedes clinical practice, and it may eventually affect students' actual performance in a clinical context. Unfortunately, there were limited studies investigating how such competence affects students' performance in practice learning. Objectives: The aim of this study is to investigate how self-rated interpersonal competence affects students' actual performance during clinical placement. Methods: 40 occupational therapy students from Hong Kong were recruited in this study. Prior to the clinical placement (level two or above), they completed an online survey that included the Interpersonal Communication Competence Scale (ICCS) measuring self-perceived competence in interpersonal communication. Near the end of their placement, the clinical educator rated students’ performance with the Student Practice Evaluation Form - Revised edition (SPEF-R). The SPEF-R measures the eight core competency domains required for an entry-level occupational therapist. This study adopted the cross-sectional observational design. Pearson correlation and multiple regression are conducted to examine the relationship between students' interpersonal communication competence and their actual performance in clinical placement. Results: The ICCS total scores were significantly correlated with all the SPEF-R domains, with correlation coefficient r ranging from 0.39 to 0.51. The strongest association was found with the co-worker communication domain (r = 0.51, p < 0.01), followed by the information gathering domain (r = 0.50, p < 0.01). Regarding the ICCS total scores as the independent variable and the rating in various SPEF-R domains as the dependent variables in the multiple regression analyses, the interpersonal competence measures were identified as a significant predictor of the co-worker communication (R² = 0.33, β = 0.014, SE = 0.006, p = 0.026), information gathering (R² = 0.27, β = 0.018, SE = 0.007, p = 0.011), and service provision (R² = 0.17, β = 0.017, SE = 0.007, p = 0.020). Moreover, some specific communication skills appeared to be especially important to clinical practice. For example, immediacy, which means whether the students were readily approachable on all social occasions, correlated with all the SPEF-R domains, with r-values ranging from 0.45 to 0.33. Other sub-skills, such as empathy, interaction management, and supportiveness, were also found to be significantly correlated to most of the SPEF-R domains. Meanwhile, the ICCS scores correlated differently with the co-worker communication domain (r = 0.51, p < 0.01) and the communication with the service user domain (r = 0.39, p < 0.05). It suggested that different communication skill sets would be required for different interpersonal contexts within the workplace. Conclusion: Students' self-perceived interpersonal communication competence could predict their actual performance during clinical placement. Moreover, some specific communication skills were more important to the co-worker communication but not to the daily interaction with the service users. There were implications on how to better prepare the students to meet the future challenge upon graduation.

Keywords: interpersonal competence, clinical education, healthcare professional education, occupational therapy, occupational therapy students

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Authors: A. Ham, A. Kuckert-Wostheinrich

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Demographic changes, like the ageing population in European countries and shortage of nursing staff, the increasing number of people with severe cognitive impairment, and elderly socially isolated people raise important questions about who will provide long-term care for ageing citizens. Due to the so-called refugee crisis in 2015, some health care institutions for ageing citizens in Europe invited first generation immigrants to start a nursing career and providing them language skills, nursing training, and internships. The aim of this ethnographic research was to explore the social processes affecting workforce integration and how newcomers enact good care in ageing citizens in a German nursing home. By ethnographic fieldwork, 200 hours of participant observations, 25 in-depth interviews with immigrants and established staff, 2 focus groups with 6 immigrants, and 6 established staff members, data were analysed. The health care institution provided the newcomers a nursing program on psychogeriatric theory and nursing skills in the psychogeriatric field and professional oriented language skills. Courses of health prevention and theater plays accompanied the training. The knowledge learned in education could be applied in internships on the wards. Additionally, diversity and inclusivity courses were given to established personal for cultural awareness and sensitivity. They learned to develop a collegial attitude of respect and appreciation, regardless of gender, nationality, ethnicity, religion or belief, age sexual orientation, or disability and identity. The qualitative data has shown that social processes affected workforce integration, like organizational constraints, staff shortages, and a demanding workload. However, zooming in on the interactions between newcomers and residents, we noticed how they tinkered to enact good care by embodied caring, playing games, singing and dancing. By situational acting and practical wisdom in nursing care, the newcomers could meet the needs of ageing residents. Thus, when health care institutions open up nursing programs for newcomers with refugees’ backgrounds and focus on talent instead of shortcomings, we might as well stimulate the unknown competencies, attitudes, skills, and expertise of newcomers and create excellent nurses for excellent care.

Keywords: established staff, Germany, nursing, refugees

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Authors: Folasade R. Sulaiman

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Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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Authors: Joyce Joas Kahembe

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The implementation of education assessment reforms in developing countries has been claimed to be problematic and difficult. The socio-economic teaching and learning environment has pointed to constraints in the education reform process. Nevertheless, there are existing assessment practices that if enhanced, can have potential to foster formative assessment practices in those contexts. The present study used the sociocultural perspective to explore teachers’ assessment practices and factors influencing them in Tanzania. Specifically, the sociocultural perspective helped to trace social, economic and political histories imparted to teachers’ assessment practices. The ethnographic oriented methods like interviews, observations and document reviews was used in this exploration. Teachers used assessment practices, such as questioning and answering, tests, assignments and examinations, for evaluating, monitoring and diagnosing students’ understanding, achievement and performance and standards and quality of instruction practices. The obtained assessment information functioned as feedback for improving students’ understanding, performance, and the standard and quality of teaching instruction and materials. For example, teachers acknowledged, praised, approved, disapproved, denied, graded, or marked students’ responses to give students feedback and aid learning. Moreover, teachers clarified and corrected or repeated students’ responses with worded/added words to improve students’ mastery of the subject content. Teachers’ assessment practices were influenced by the high demands of passing marks in the high stakes examinations and the contexts of the social economic teaching environment. There is a need to ally education assessment reforms with existing socio-economic teaching environments and society and institutional demands of assessment to make assessment reforms meaningful and sustainable. This presentation ought to contribute on ongoing strategies for contextualizing assessment practices for formative uses.

Keywords: assessment, feedback, practices, formative assessment

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Łukasz Bis

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The author is going to discuss virtual reality and its importance for new didactic methods. It has been known for years that experience-based education gives much better results in terms of long-term memory than theoretical study. However, practice is expensive - virtual reality allows the use of an empirical approach to learning, with minimized production costs. The author defines what makes a given VR experience appropriate (adequate) for the didactic and cognitive process. The article is a kind of a list of guidelines and their importance for the VR experience under development.

Keywords: virtual reality, education, universal design, guideline

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Authors: Aamna Zafar

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Through linguistic and cultural analysis, this study seeks to trace the development of the English and Urdu languages. Along with examining how the vocabulary and syntax of English and Urdu have evolved over time and the linguistic trends that may be seen in these changes, this study will also look at the historical and cultural influences that have shaped the languages throughout time. The study will also look at how English and Urdu have changed over time, both in terms of language use and communication inside each other's cultures and globally. We'll research how these changes affect social relations and cultural identity, as well as how they might affect the future of these languages.

Keywords: linguistic and cultural analysis, historical factors, cultural factors, vocabulary, syntax, significance

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Authors: Meng-Ying Chiu, Yu-Fang Huang, Pei-Wei Wang, Yi-Ru Wang, Yi-Shuan Shao, Mei-Lien Chen

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Background: Organophosphate pesticides (OPs) are the most heavily used pesticides in agriculture in Taiwan. Therefore, they are commonly detected in general public including pregnant women and children. These compounds are proven endocrine disrupters that may affect the neural development in humans. The aim of this study is to assess the OPs exposure of children in 2 years of age and to examine the association between the exposure concentrations and neurodevelopmental effects in children. Methods: In a prospective cohort of 280 mother-child pairs, urine samples of prenatal and postnatal were collected from each participant and analyzed for metabolites of OPs by using gas chromatography-mass spectrometry. Six analytes were measured including dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphate (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP). This study created a combined concentration measure for dimethyl compounds (DMs) consisting of the three dimethyl metabolites (DMP, DMTP, and DMDTP), for diethyl compounds (DEs) consisting of the three diethyl metabolites (DEP, DETP, and DEDTP) and six dialkyl phosphate (DAPs). The Bayley Scales of Infant and Toddler Development (Bayley-III) was used to assess children's cognitive behavior at 2 years old. The association between OPs exposure and Bayley-III scale score was determined by using the Mann-Whitney U test. Results: The measurements of urine samples are still on-going. This preliminary data are the report of 56 children aged 2 from the cohort. The detection rates for DMP, DMTP, DMDTP, DEP, DETP, and DEDTP are 80.4%, 69.6%, 64.3%, 64.3%, 62.5%, and 75%, respectively. After adjusting the creatinine concentrations of urine, the median (nmol/g creatinine) of urinary DMP, DMTP, DMDTP, DEP, DETP, DEDTP, DMs, DEs, and DAPs are 153.14, 53.32, 52.13, 19.24, 141.65, 192.17, 308.8, 311.6, and 702.11, respectively. The concentrations of urine are considerably higher than that in other countries. Children’s cognitive behavior was used three scales for Bayley-III, including cognitive, language and motor. In Mann-Whitney U test, the higher levels of DEs had significantly lower motor score (p=0.037), but no significant association was found between the OPs exposure levels and the score of either cognitive or language. Conclusion: The limited sample size suggests that Taipei children are commonly exposed to OPs and OPs exposure might affect the cognitive behavior of young children. This report will present more data to verify the results. The predictors of OPs concentrations, such as dietary pattern will also be included.

Keywords: biomonitoring, children, neurodevelopment, organophosphate pesticides exposure

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Authors: Madina Tynybayeva, Sanya Zhumazhanova, Saltanat Kozhakhmetova, Merey Mussabayeva

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One of the leading indicators of the education quality is the level of students’ educational achievements. The processes of modernization of Kazakhstani education system have predetermined the need to improve the national system by assessing the quality of education. The results of assessment greatly contribute to addressing questions about the current state of the educational system in the country. The monitoring of students’ educational achievements (MEAS) is the systematic measurement of the quality of education for compliance with the state obligatory standard of Kazakhstan. This systematic measurement is independent of educational organizations and approved by the order of the Minister of Education and Scienceof Kazakhstan. The MEAS was conducted in the regions of Kazakhstanfor the first time in 2022 by the National Testing Centre. The measurement does not have legal consequences either for students or for educational organizations. Students’ achievements were measured in three subject areas: reading, mathematics and science literacy. MEAS was held for the first time in April this year, 105 thousand students from 1436 schools of Kazakhstan took part in the testing. The monitoring was accompanied by a survey of students, teachers, and school leaders. The goal is to identify which contextual factors affect learning outcomes. The testing was carried out in a computer format. The test tasks of MEAS are ranked according to the three levels of difficulty: basic, medium, and high. Fourth graders are asked to complete 30 closed-type tasks. The average score of the results is 21 points out of 30, which means 70% of tasks were successfully completed. The total number of test tasks for 9th grade students – 75 questions. The results of ninth graders are comparatively lower, the success rate of completing tasks is 63%. MEAS participants did not reveal a statistically significant gap in results in terms of the language of instruction, territorial status, and type of school. The trend of reducing the gap in these indicators is also noted in the framework of recent international studies conducted across the country, in particular PISA for schools in Kazakhstan. However, there is a regional gap in MOES performance. The difference in the values of the indicators of the highest and lowest scores of the regions was 11% of the success of completing tasks in the 4th grade, 14% in the 9thgrade. The results of the 4th grade students in reading, mathematics, and science literacy are: 71.5%, 70%, and 66.9%, respectively. The results of ninth-graders in reading, mathematics, and science literacy are 69.6%, 54%, and 60.8%, respectively. From the surveys, it was revealed that the educational achievements of students are considerably influenced by such factors as the subject competences of teachers, as well as the school climate and motivation of students. Thus, the results of MEAS indicate the need for an integrated approach to improving the quality of education. In particular, the combination of improving the content of curricula and textbooks, internal and external assessment of the educational achievements of students, educational programs of pedagogical specialties, and advanced training courses is required.

Keywords: assessment, secondary school, monitoring, functional literacy, kazakhstan

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Authors: Ray Bryant

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3Strands Global Foundation (3SGF), a non-profit with a mission to mobilize communities to combat human trafficking through prevention education and reintegration programs, launched a groundbreaking study that calls out the usage and benefits of artificial intelligence in the war against human trafficking. Having gathered more than 30,000 stories from counselors and school staff who have gone through its PROTECT Prevention Education program, 3SGF sought to develop a methodology to measure the effectiveness of the training, which helps educators and school staff identify physical signs and behaviors indicating a student is being victimized. The program further illustrates how to recognize and respond to trauma and teaches the steps to take to report human trafficking, as well as how to connect victims with the proper professionals. 3SGF partnered with Levity, a leader in no-code Artificial Intelligence (AI) automation, to create the research study utilizing natural language processing, a branch of artificial intelligence, to measure the effectiveness of their prevention education program. By applying the logic created for the study, the platform analyzed and categorized each story. If the story, directly from the educator, demonstrated one or more of the desired outcomes; Increased Awareness, Increased Knowledge, or Intended Behavior Change, a label was applied. The system then added a confidence level for each identified label. The study results were generated with a 99% confidence level. Preliminary results show that of the 30,000 stories gathered, it became overwhelmingly clear that a significant majority of the participants now have increased awareness of the issue, demonstrated better knowledge of how to help prevent the crime, and expressed an intention to change how they approach what they do daily. In addition, it was observed that approximately 30% of the stories involved comments by educators expressing they wish they’d had this knowledge sooner as they can think of many students they would have been able to help. Objectives Of Research: To solve the problem of needing to analyze and accurately categorize more than 30,000 data points of participant feedback in order to evaluate the success of a human trafficking prevention program by using AI and Natural Language Processing. Methodologies Used: In conjunction with our strategic partner, Levity, we have created our own NLP analysis engine specific to our problem. Contributions To Research: The intersection of AI and human rights and how to utilize technology to combat human trafficking.

Keywords: AI, technology, human trafficking, prevention

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

Procedia PDF Downloads 172

Authors: Vassilis Argyropoulos, Magda Nikolaraizi, Maria Papazafiri

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This study describes a series of learning workshops, which took place within CUIDAR project. The workshops aimed to empower children to share their experiences and views in relation to natural hazards and disasters. The participants in the workshops were ten primary school students who had severe visual impairments or multiple disabilities and visual impairments (MDVI). The main objectives of the workshops were: a) to promote access of the children through the use of appropriate educational material such as texts in braille, enlarged text, tactile maps and the implementation of differentiated instruction, b) to make children aware regarding their rights to have access to information and to participate in planning and decision-making especially in relation to disaster education programs, and c) to encourage children to have an active role during the workshops through child-led and experiential learning activities. The children expressed their views regarding the meaning of hazards and disasters. Following, they discussed their experiences and emotions regarding natural hazards and disasters, and they chose to place the emphasis on a hazard, which was more pertinent to them, their community and their region, namely fires. Therefore, they recalled fires that have caused major disasters, and they discussed about the impact that these fires had on their community or on their country. Furthermore, they were encouraged to become aware regarding their own role and responsibility to prevent a fire or get prepared and know how to behave if a fire occurs. They realized that prevention and preparation are a matter of personal responsibility. They also felt the responsibility to inform their own families. Finally, they met important people involved in fire protection such as rescuers and firefighters and had the opportunity to carry dialogues. In conclusion, through child led workshops, experiential and accessible activities, the students had the opportunity to share their own experiences, to express their views and their questions, to broaden their knowledge and to realize their personal responsibility in disaster risk reduction, specifically in relation to fires.

Keywords: accessibility, children, disasters, visual impairment

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

Procedia PDF Downloads 39

Authors: Nadezhda F. Mikahailova, Margarita E. Fattakhova, Mirgarita A. Mironova, Ekaterina V. Vyacheslavova, Vladimir A. Mikahailov

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Stigma is a significant obstacle to the successful adaptation of deaf students to the conditions of an educational institution, especially for those who study in inclusion. The aim of the study was to identify the spheres of life which are the most significant for developing of the stigma of deaf students; to assess the influence of factors associated with deafness on the degree of their self-stigmatization (time and degree of hearing loss, type of education - inclusion / differentiation) and to find out who is more prone to stigma - which characteristics of personality, identity, mental health and coping are specific for those deaf who demonstrates stigmatizing attitudes. The study involved 154 deaf and hard-of-hearing students (85 male and 69 female) aged from 18 to 45 years - 28 students of the Herzen State Pedagogical University (St. Petersburg), who study in inclusion, 108 students of the National Research Technological University and 18 students of the Aviation Technical College (Kazan) - students in groups with a sign language interpreter. We used the following methods: modified questionnaire 'Self-assessment and coping strategies' (Jambor & Elliot, 2005), Scale of self-esteem (Rosenberg et al, 1995), 'Big-Five' (Costa&McCrae, 1997), TRF (Becker, 1989), WCQ (Lazarus & Folkman, 1988), self-stigma scale (Mikhailov, 2008). The severity of self-stigmatization of deaf and hard of hearing students was determined by the degree of deafness and the time they live with hearing loss, learning conditions, the type of self-identification (acculturation), personality traits, and the specifics of coping behavior. Persons with congenital hearing loss more often noted a benevolent and sympathetic attitude towards them on the part of the hearers and less often, due to deafness, limited themselves to visiting public places than late deaf people, which indicates 'get rid of' the experience of their defect and normalization of the state. Students studying in conditions of inclusion more often noted the dismissive attitude of society towards deaf people. Individuals with mild to moderate hearing loss were more likely to fear marriage and childbearing because of their deafness than students with profound hearing loss. Those who considered themselves disabled (49% of all respondents) were more inclined to cope with seeking social support and less used 'distancing' coping. Those who believed that their quality of life and social opportunities were most influenced by the attitude of society towards the deaf (39%) were distinguished by a less pronounced sense of self-worth, a desire for autonomy, and frequent usage of 'avoidance' coping strategies. 36.4% of the respondents noted that there have been situations in their lives when people learned that they are deaf, began to treat them worse. These respondents had predominantly deaf acculturation, but more often, they used 'bicultural skills,' specific coping for the deaf, and had a lower level of extraversion and emotional stability. 31.2% of the respondents tried to hide from others that they have hearing problems. They considered themselves to be in a culture of hearing, used coping strategies 'bicultural skills,' and had lower levels of extraversion, cooperation, and emotional stability. Acknowledgment: Supported by the RFBR № 19-013-0040

Keywords: acculturation, coping, deafness, stigmatization

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Authors: Stanley Fore, Sharon Chipeperekwa

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The start of the 2011 academic year in South Africa saw a number of Institutions of Higher Learning introducing online registration for their students. The efficiency and effectiveness of Information Systems are increasingly becoming a necessity and not an option for many organizations. An information system should be able to allow end users to access information easily and navigate with ease. The selected University of Technology (UoT) in this research is one of the largest public institution of higher learning in the Western Cape Province and boasts of an enrolment of more than 30000 students per academic year. An observation was made that, during registration students’ stand in long queues waiting to register or for assistance to register. The system tends to ‘freeze’ whilst students are registering and students are in most cases unfamiliar with the system interface. They constantly have to enquire what to do next when going through online registration process. A mixed method approach will be adopted which comprises of quantitative and qualitative approaches. The study uses constructs of the updated DeLone and McLean IS success model (2003) to analyse and explain the student’s perceptions of the online registration system. The research was undertaken to establish the student’s perceptions of the online registration system. This research seeks to identify and analyse the challenges and success factors of introducing an online registration system whilst highlighting the extent to which this system has been able to solve the numerous problems associated with the manual era. The study will assist management and those responsible for managing the current system to determine how well the system is working or not working to achieve user satisfaction. It will also assist them going forward on what to consider before, during and after implementation of an information system. Respondents will be informed of the objectives of the research, and their consent to participate will be sought. Ethical considerations that will be applied to this study include; informed consent and protection from harm, right to privacy and involvement of the research.

Keywords: online registration, information systems, University of Technology, end-users

Procedia PDF Downloads 232

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: A. Raj Kumar, A. Okunseinde, P. Raghavan, V. Kapila

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Stroke is the leading cause of adult disability worldwide. With recent advances in immediate post-stroke care, there is an increasing number of young stroke survivors, under the age of 65 years. While most stroke survivors will regain the ability to walk, they often experience long-term arm and hand motor impairments. Long term upper limb rehabilitation is needed to restore movement and function, and prevent deterioration from complications such as learned non-use and learned bad-use. We have developed a novel virtual coach, a wearable instrumented rehabilitation jacket, to motivate individuals to participate in long-term skill re-learning, that can be personalized to their impairment profile. The jacket can estimate the movements of an individual’s arms using embedded off-the-shelf sensors (e.g., 9-DOF IMU for inertial measurements, flex-sensors for measuring angular orientation of fingers) and a Bluetooth Low Energy (BLE) powered microcontroller (e.g., RFduino) to non-intrusively extract data. The 9-DOF IMU sensors contain 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer to compute the quaternions, which are transmitted to a computer to compute the Euler angles and estimate the angular orientation of the arms. The data are used in a gaming environment to provide visual, and/or haptic feedback for goal-based, augmented-reality training to facilitate re-learning in a cost-effective, evidence-based manner. The full paper will elaborate the technical aspects of communication, interactive gaming environment, and physical aspects of electronics necessary to achieve our stated goal. Moreover, the paper will suggest methods to utilize the proposed system as a cheaper, portable, and versatile system vis-à-vis existing instrumentation to facilitate post-stroke personalized arm rehabilitation.

Keywords: feedback, gaming, Euler angles, rehabilitation, augmented reality

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Authors: Ronit German, Alexandra Beytenbrat

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Although English seems to be prevalent in every sphere of Israeli daily life, not many Israeli students have a sufficient level of writing and speaking in English which is necessary for academic studies. The inadequate level of English among Israeli students, almost the sole focus on teaching reading comprehension, and the need to adapt to the trends of the professional worldwide demands triggered a reform that requires to implement Common European Framework of Reference (CEFR) and English as a Medium of Instruction (EMI) courses in the Israeli academic institutions. However, it will be argued that this reform is challenging to implement. The fact that modern Hebrew is a revived language, and that English is L3 for more than 30% of the population, the diverse social and cultural students’ background, and psychological factors stand in the way of the new reform.

Keywords: CEFR, cultural diversity, EMI courses, English in Israel, reform

Procedia PDF Downloads 190