Search results for: extracurricular English learning

Authors: Joanna Peksa, Faith Dillon-Lee

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Current developments in the Western economies have turned some universities into corporate institutions driven by practices of production and commodity. Academia is increasingly becoming integrated into national economies as a result of students paying fees and is consequently using business practices in student retention and engagement. With these changes, pedagogy status as a priority within the institution has been changing in light of these new demands. New strategies have blurred the boundaries that separate a student from a client. This led to a change of the dynamic, disrupting the traditional idea of the knowledge market, and emphasizing the corporate aspect of universities. In some cases, where students are seen primarily as a customer, the purpose of academia is no longer to educate but sell a commodity and retain fee-paying students. This paper considers opposing viewpoints on the commodification of higher education, reflecting on the reality of maintaining a pedagogic grounding in an increasingly commercialized sector. By analysing a case study of the Student Success Festival, an event that involved academic and marketing teams, the differences are considered between the respective visions of the pedagogic arm of the university and the corporate. This study argues that the initial concept of the event, based on the principles of gamification, independent learning, and cognitive criticality, was more clearly linked to a grounded pedagogic approach. However, when liaising with the marketing team in a crucial step in the creative process, it became apparent that these principles were not considered a priority in terms of their remit. While the study acknowledges in the power of pedagogy, the findings show that a pact of concord is necessary between different stakeholders in order for students to benefit fully from their learning experience. Nevertheless, while issues of power prevail and whenever power is unevenly distributed, reaching a consensus becomes increasingly challenging and further research should closely monitor the developments in pedagogy in the UK higher education.

Keywords: economic pressure, commodification, pedagogy, gamification, public service, marketization

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Authors: Mohammad Reza Ghaani, Niall English

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Hydrogen is looked upon as the next-generation clean-energy carrier; the search for an efficient material and method for storing hydrogen has been, and is, pursued relentlessly. Clathrate hydrates are inclusion compounds wherein guest gas molecules like hydrogen are trapped in a host water-lattice framework. These types of materials can be categorised as potentially attractive hosting environments for physical hydrogen storage (i.e., no chemical reaction upon storage). Non-equilibrium molecular dynamics (NEMD) simulations have been performed to investigate thermal-driven break-up of propane-hydrate interfaces with liquid water at 270-300 K, with the propane hydrate containing either one or no hydrogen molecule in each of its small cavities. In addition, two types of hydrate-surface water-lattice molecular termination were adopted, at the hydrate edge with water: a 001-direct surface cleavage and one with completed cages. The geometric hydrate-ice-liquid distinction criteria of Báez and Clancy were employed to distinguish between the hydrate, ice lattices, and liquid-phase. Consequently, the melting temperatures of interface were estimated, and dissociation rates were observed to be strongly dependent on temperature, with higher dissociation rates at larger over-temperatures vis-à-vis melting. The different hydrate-edge terminations for the hydrate-water interface led to statistically-significant differences in the observed melting point and dissociation profile: it was found that the clathrate with the planar interface melts at around 280 K, whilst the melting temperature of the cage-completed interface was determined to be circa 270 K.

Keywords: hydrogen storage, clathrate hydrate, molecular dynamics, thermal dissociation

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Authors: Dewi Indah Irianti

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Introduction: Street children include one of the populations at risk of HIV infection. Their vulnerability to these situations is increased by their lack of understanding of the changes associated with adolescence, the lack of knowledge and skills which could help them to make healthy choices. Social integration increased AIDS knowledge among migrant workers in Thailand. Although social integration has been incorporated into health research in other areas, it has received less attention in AIDS prevention research. This factor has not been integrated into models for HIV prevention. Objectives: The goal of this review is to summarize available knowledge about factors related to HIV/AIDS knowledge and to examine whether social integration was reviewed among street children. Methodology: This study performed a systematic search for English language articles published between January 2006 and March 2016 using the following keywords in various combination: street children, HIV/AIDS knowledge and social integration from the following bibliographic databases: Scopus, ProQuest, JSTOR, ScienceDirect, SpringerLink, EBSCOhost, Sage Publication, Clinical Key, Google Web, and Google Scholar . Results: A total of 10 articles met the inclusion criteria were systematically reviewed. This study reviews the existing quantitative and qualitative literature regarding the HIV/AIDS knowledge of street children in many countries. The study locations were Asia, the Americas, Europe, and Africa. The most determinants associated with HIV/AIDS knowledge among street children are age and sex. In this review, social integration that may be associated with HIV/AIDS knowledge among street children has not been investigated. Conclusion: To the best of the author’s knowledge, this study found that there is no research examining the relationship of social integration with the HIV knowledge among street children. This information may assist in the development of relevant strategies and HIV prevention programs to improve HIV knowledge and decrease risk behaviors among street children.

Keywords: HIV/AIDS knowledge, review, social integration, street children

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Authors: Suleiman Garba, Haruna Ishaku

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Information and communication technology (ICT) includes any communication device encompassing: radio, television, cellular phones, computer, satellite systems and so on, as well as the various services and applications associated with them. The significance of ICT cannot be over-emphasized in education. The teaching and learning processes have integrated with the application of ICTs for effectiveness and enhancement of academic performance among the students. Today, as the educational sector is faced with series of changes and reforms, it was noted that the problem of information technology illiteracy was a serious one among the schools’ teachers in the country as it cuts across primary, secondary schools and tertiary institutions. This study investigated the impact of ICT on the academic performance of senior secondary schools students in Gwagwalada Area Council of Federal Capital Territory (FCT), Abuja. A sample of 120 SSS III students was involved in the study. They were selected by using simple random sampling technique. A questionnaire was developed and validated through expert judgement and reliability co-efficient of 0.81 was obtained. It was used to gather relevant data from the respondents. Findings revealed that there was positive impact of ICT on academic performance of senior secondary schools students. The findings indicated the causes of poor academic performance among the students as lack of qualified teachers to teach in schools, peer group influence, and bullying. Significantly, the findings revealed that ICT had a positive impact on students’ academic performance. The null hypotheses were tested using t-test at 0.05 level of significance. It was discovered that there was significant difference between male and female secondary schools’ students' impact of ICT on academic performance in Gwagawalada Area Council of FCT-Abuja. Based on these findings, some recommendations were made which include: adequate funds should be provided towards procurement of ICT resources, relevant textbooks to enhance students’ active participation in learning processes and students should be provided with internet accessibility at inexpensive rate so as to create a platform for accessing useful information in the pursuit of academic excellence.

Keywords: academic performance, impact, information communication technology, schools, students

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Authors: T. Frawley, G. O'Kelly

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The UCD School of Nursing, Midwifery and Health Systems Higher Diploma in Mental Health (HDMH) nursing programme commenced in January 2017. Forty students successfully completed the programme. Programme evaluation was conducted from the outset. Research ethics approval was granted by the UCD Human Research Ethics Committee – Sciences in November 2016 (LS-E-16-163). Plan for Sustainability: Each iteration of the programme continues to be evaluated and adjusted accordingly. Aims: The ultimate purpose of the HDMH programme is to prepare registered nurses (registered children’s nurse (RCN), registered nurse in intellectual disability (RNID) and registered general nurse (RGN)) to function as effective registered psychiatric nurses in all settings which provide care and treatment for people experiencing mental health difficulties. Curriculum evaluation is essential to ensure that the programme achieves its purpose, that aims and expected outcomes are met and that required changes are highlighted for the programme’s continuing positive development. Methods: Both quantitative and qualitative methods were used in the evaluation. A series of questionnaires were used (the majority pre and post programme) to determine student perceptions of the programme, behaviour and attitudinal change from commencement to completion. These included the student assessment of learning gains (SALG); mental health knowledge schedule (MAKS); mental health clinician attitudes scale (MICA); reported and intended behaviour scale (RIBS); and community attitudes towards the mentally ill (CAMI). In addition, student and staff focus groups were conducted. Evaluation methods also incorporated module feedback. Outcome/Results: The evaluation highlighted a very positive response in relation to the achievement of programme outcomes and preparation for future work as registered psychiatric nursing. Some areas were highlighted for further development, which have been taken cognisance of in the 2019 iteration of the programme.

Keywords: learning gains, mental health, nursing, stigma

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Faizan Tariq, Moayid Ali Zaidi

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Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: Ramune Kasperaviciene, Jurgita Motiejuniene, Dalia Venckiene

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Familiarising students with strategies for transferring cultural meanings (intertextual units, culture-specific idioms, culture-specific items, etc.) should be part of a comprehensive translator training programme. The present paper focuses on strategies for transferring such meanings into other languages and explores possibilities for introducing these methods and practice to translation students. The authors (university translation teachers) analyse the means of transferring cultural meanings from English into Lithuanian in a specific travel book, attribute these means to theoretically grounded strategies, and make calculations related to the frequency of adoption of specific strategies; translation students are familiarised with concepts and methods related to transferring cultural meanings and asked to put their theoretical knowledge into practice, i.e. interpret and translate certain culture-specific items from the same source text, and ground their decisions on theory; the comparison of the strategies employed by the professional translator of the source text (as identified by the authors of this study) and by the students is made. As a result, both students and teachers gain valuable experience, and new practices of conducting translation classes for a specific purpose evolve. Conclusions highlight the differences and similarities of non-professional and professional choices, summarise the possibilities for introducing methods of transferring cultural meanings to students, and round up with specific considerations of the impact of theoretical knowledge and the degree of experience on decisions made in the translation process.

Keywords: cultural meanings, culture-specific items, strategies for transferring cultural meanings, translator training

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Authors: Osakwe Jude Odiakaosa

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Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

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Authors: Cissy Li

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Mentorship is a commonly used strategy for career development that has obvious benefits for students in undergraduate pre-service teacher training programs. In contrast to teaching practicum, which generally involves pedagogical supervision and performance evaluation by teachers, mentorship is more focused on sharing experiences, supporting challenges, and nurturing skills in order to promote personal and professional growth. To empower pre-service teachers and prepare them for potential challenges in the context of local English language teaching (ELT), an alumni mentoring program was established in the framework of communities of practice (CoP), with the mentors being in-service graduates working in local schools and mentees being students on the teacher-training programme in a Hong Kong university. By triangulating audio transcripts of mentoring sessions delivered by three top mentors with data from questionnaire responses and mentor logs, this paper examines the mentoring styles of the three best mentors from the metadiscursive perspective. It was found that, in a community of practice, mentors who may seem to enjoy a relative more dominant position, in fact, had to strategically and pragmatically employ metadiscursive resources to manage relationships with the mentees and organize talks in the mentoring process. Other attributing factors for a successful mentoring session include mentor personality and prior mentorship experiences, nature of the activities in the session, and group dynamics. This paper concludes that it is the combination of all the factors that constitute a particular mentoring style. The findings have implications for mentoring programs in teacher preparation.

Keywords: mentoring, teacher education, mentoring style, metadiscourse

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Authors: Neeraj Malhotra, Ramya Shenoy

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Objective: To assess the effect of clinical parameters (bonding agent, preparation design & storage media) on the strength of reattached anterior tooth fragment. Methodology: This is a systematic review and meta-analysis for articles referred from MEDLINE, PUBMED, and GOOGLE SCHOLAR. The articles on tooth reattachment and clinical factors affecting fracture strength/bond strength/fracture resistance of the reattached tooth fragment in anterior teeth and published in English from 1999 to 2016 were included for final review. Results: Out of 120 shortlisted articles, 28 articles were included for the systematic review and meta-analysis based on 3 clinical parameters i.e. bonding agent, tooth preparation design & storage media. Forest plot & funnel plots were generated based on individual clinical parameter and their effect on strength of reattached anterior tooth fragment. Results based on analysis suggest combination of both conclusive evidence favoring the experimental group as well as in-conclusive evidence for individual parameter. Conclusion: There is limited evidence as there are fewer articles supporting each parameter in human teeth. Bonding agent had showed better outcome in selected studies.

Keywords: bonding agent, bond strength, fracture strength, preparation design, reattachment, storage media

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Authors: Raheel Shakoor Siddiqui, Sanjay Narayana Murthy, Manikandar Srinivas Cheruvu, Kash Akhtar

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Major trauma is a dynamic public health epidemic that is continuously evolving. Major trauma care services rely on multi-disciplinary team input involving highly trained pre and in-hospital critical care teams. Pre-hospital critical care teams (PHCCTs), major trauma centres (MTCs), trauma units, and rehabilitation facilities all form an efficient and organised trauma system. England comprises 27 MTCs funded by the National Health Service (NHS). Major trauma care entails enhanced resuscitation protocols coupled with the expertise of dedicated trauma teams and rapid radiological imaging to improve trauma outcomes. Literature reports a change in the demographic of major trauma as elderly patients (silver trauma) with injuries sustained from a fall of 2 metres or less commonly present to services. Evidence of an increasing population age with multiple comorbidities necessitates treatment within the first hour of injury (golden hour) to improve trauma survival outcomes. Staffing and funding pressures within the NHS have subsequently led to a shortfall of available physician-led PHCCTs. Thus, there is a strong emphasis on targeted research and funding to appropriately deploy resources to deprived areas. This review article will discuss the current English trauma system whilst critically appraising present challenges, identifying insufficiencies, and recommending aims for an improved future trauma system in England.

Keywords: trauma, orthopaedics, major trauma, trauma system, trauma network

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Volker Koch

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This paper deals with the education of purchasing professionals in Austria. In this education, equivalent and measurable criteria are collected in order to create a comparison. The comparison shows the problem. To make the aforementioned comparison possible, methodologies such as KODE-Competence Atlas or presentations in a matrix form are used. The result shows the content taught and whether there are any similarities or interesting differences in the current Austrian purchasers’ formations. Purchasing professionals learning competencies are also illustrated in the study result.

Keywords: competencies, education, purchasing professional, technological-oriented

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Authors: Sereen Itani

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As the world aspires for technological innovation, Innovative Robotics Technology-Supported Pedagogic Models in STEAM Education (Science, Technology, Engineering, Arts, and Mathematics) are critical in our global education system to build and enhance the next generation 21st century skills. Thus, diverse international schools endeavor in attempts to construct an integrated robotics and technology enhanced curriculum based on interdisciplinary subjects. Accordingly, it is vital that the globe remains resilient in STEAM fields by equipping the future learners and educators with Innovative Technology Experiences through robotics to support such fields. A variety of advanced teaching methods is employed to learn about Robotics Technology-integrated pedagogic models. Therefore, it is only when STEAM and innovations in Robotic Technology becomes integrated with real-world applications that transformational learning can occur. Robotics STEAM education implementation faces major challenges globally. Moreover, STEAM skills and concepts are communicated in separation from the real world. Instilling the passion for robotics and STEAM subjects and educators’ preparation could lead to the students’ majoring in such fields by acquiring enough knowledge to make vital contributions to the global STEAM industries. Thus, this necessitates the establishment of Pedagogic models such as Innovative Robotics Technologies to enhance STEAM education and develop students’ 21st-century skills. Moreover, an ICT innovative supported robotics classroom will help educators empower and assess students academically. Globally, the Robotics Design System and platforms are developing in schools and university labs creating a suitable environment for the robotics cross-discipline STEAM learning. Accordingly, the research aims at raising awareness about the importance of robotics design systems and methodologies of effective employment of robotics innovative technology-supported pedagogic models to enhance and develop (STEAM) education globally and enhance the next generation 21st century skills.

Keywords: education, robotics, STEAM (Science, Technology, Engineering, Arts and Mathematics Education), challenges

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Carly Nesvat, Dominic Jarrett, Colin Thomson, Wilma Coltart, Thelma Bowers, Jan Thomson

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Introduction: Within Scotland, the Same As You strategy committed to moving people with learning disabilities out of long-stay hospital accommodation into homes in the community. Much of the focus of this movement was on the placement of people within individual homes. In order to achieve this, potentially excessive supports were put in place which created dependence, and carried significant ongoing cost primarily for local authorities. The greater focus on empowerment and community participation which has been evident in more recent learning disability strategy, along with the financial pressures being experienced across the public sector, created an imperative to re-examine that provision, particularly in relation to the use of expensive sleepover supports to individuals, and the potential for this to be appropriately scaled back through the use of telecare. Method: As part of a broader programme of redesigning overnight supports within North Ayrshire, a cluster of individuals living in close proximity were identified, who were in receipt of overnight supports, but who were identified as having the capacity to potentially benefit from their removal. In their place, a responder service was established (an individual staying overnight in a nearby service user’s home), and a variety of telecare solutions were placed within individual’s homes. Active and passive technology was connected to an Alarm Receiving Centre, which would alert the local responder service when necessary. Individuals and their families were prepared for the change, and continued to be informed about progress with the pilot. Results: 4 individuals, 2 of whom shared a tenancy, had their sleepover supports removed as part of the pilot. Extensive data collection in relation to alarm activation was combined with feedback from the 4 individuals, their families, and staff involved in their support. Varying perspectives emerged within the feedback. 3 of the individuals were clearly described as benefitting from the change, and the greater sense of independence it brought, while more concerns were evident in relation to the fourth. Some family members expressed a need for greater preparation in relation to the change and ongoing information provision. Some support staff also expressed a need for more information, to help them understand the new support arrangements for an individual, as well as noting concerns in relation to the outcomes for one participant. Conclusion: Developing a telecare response in relation to a cluster of individuals was facilitated by them all being supported by the same care provider. The number of similar clusters of individuals being identified within North Ayrshire is limited. Developing other solutions such as a response service for redesign will potentially require greater collaboration between different providers of home support, as well as continuing to explore the full range of telecare, including digital options. The pilot has highlighted the need for effective preparatory and ongoing engagement with staff and families, as well as the challenges which can accompany making changes to long-standing packages of support.

Keywords: challenges, change, engagement, telecare

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Wan-Ling Chang, Hsiu-Ju Huang, Jui-Hsiu Chang

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In 2004, the Ministry of Foreign Affairs Taiwan launched ‘An Arrangement on Working Holiday Scheme’ with 15 countries including New Zealand, Japan, Canada, Germany, South Korea, Britain, Australia and others. The aim of the scheme is to allow young people to work and study English or other foreign languages. Each year, there are 30,000 Taiwanese youths applied for participating in the working holiday schemes. However, frequent accidents could cause huge medical expenses and post-delivery fee, which are usually unaffordable for most families. Therefore, this study explored the relationship among perceived risk toward working holiday, insurance product knowledge, brand image and insurance purchase intention for Taiwanese youths who plan to apply for working holiday. A survey questionnaire was distributed for data collection. A total of 316 questionnaires were collected for data analyzed. Data were analyzed using descriptive statistics, independent samples T-test, one-way ANOVA, correlation analysis, regression analysis and hierarchical regression methods of analysis and hypothesis testing. The results of this research indicate that perceived risk has a negative influence on insurance purchase intention. On the opposite, product knowledge has brand image has a positive influence on the insurance purchase intention. According to the mentioned results, practical implications were further addressed for insurance companies when developing a future marketing plan.

Keywords: insurance product knowledges, insurance purchase intention, perceived risk, working holiday

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Veronika Solopova, Oana-Iuliana Popescu, Tim Landgraf, Christoph Benzmüller

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Beginning in 2014, slowly building geopolitical tensions in Eastern Europe led to a full-blown conflict between the Russian Federation and Ukraine that generated an unprecedented amount of news articles and data from social media data, reflecting the opposing ideologies and narratives as a background and the essence of the ongoing war. These polarized informational campaigns have led to countless mutual accusations of misinformation and fake news, shaping an atmosphere of confusion and mistrust for many readers all over the world. In this study, we analyzed scraped news articles from Ukrainian, Russian, Romanian and English-speaking news outlets, on the eve of 24th of February 2022, compared to day five of the conflict (28th of February), to see how the media influenced and mirrored the changes in public opinion. We also contrast the sources opposing and supporting the stands of the Russian government in Ukrainian, Russian and Romanian media spaces. In a data-driven way, we describe how the narratives are spread throughout Eastern and Central Europe. We present predictive linguistic features surrounding war propaganda. Our results indicate that there are strong similarities in terms of rhetoric strategies in the pro-Kremlin media in both Ukraine and Russia, which, while being relatively neutral according to surface structure, use aggressive vocabulary. This suggests that automatic propaganda identification systems have to be tailored for each new case, as they have to rely on situationally specific words. Both Ukrainian and Russian outlets lean towards strongly opinionated news, pointing towards the use of war propaganda in order to achieve strategic goals.

Keywords: linguistic, news, propaganda, Russia, ukraine

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Authors: Lauren B. Birney

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The envisioned long-term outcome of this three-year research, and implementation plan is for 1) teachers and students to design and build their own computational models of real-world environmental-human health phenomena occurring within the context of the “Human Harbor” and 2) project researchers to evaluate the degree to which these integrated Computer Science (CS) education experiences in New York City (NYC) public school classrooms (PreK-12) impact students’ computational-technical skill development, job readiness, career motivations, and measurable abilities to understand, articulate, and solve the underlying phenomena at the center of their models. This effort builds on the partnership’s successes over the past eight years in developing a benchmark Model of restoration-based Science, Technology, Engineering, and Math (STEM) education for urban public schools and achieving relatively broad-based implementation in the nation’s largest public school system. The Billion Oyster Project Curriculum and Community Enterprise for Restoration Science (BOP-CCERS STEM + Computing) curriculum, teacher professional developments, and community engagement programs have reached more than 200 educators and 11,000 students at 124 schools, with 84 waterfront locations and Out of School of Time (OST) programs. The BOP-CCERS Partnership is poised to develop a more refined focus on integrating computer science across the STEM domains; teaching industry-aligned computational methods and tools; and explicitly preparing students from the city’s most under-resourced and underrepresented communities for upwardly mobile careers in NYC’s ever-expanding “digital economy,” in which jobs require computational thinking and an increasing percentage require discreet computer science technical skills. Project Objectives include the following: 1. Computational Thinking (CT) Integration: Integrate computational thinking core practices across existing middle/high school BOP-CCERS STEM curriculum as a means of scaffolding toward long term computer science and computational modeling outcomes. 2. Data Science and Data Analytics: Enabling Researchers to perform interviews with Teachers, students, community members, partners, stakeholders, and Science, Technology, Engineering, and Mathematics (STEM) industry Professionals. Collaborative analysis and data collection were also performed. As a centerpiece, the BOP-CCERS partnership will expand to include a dedicated computer science education partner. New York City Department of Education (NYCDOE), Computer Science for All (CS4ALL) NYC will serve as the dedicated Computer Science (CS) lead, advising the consortium on integration and curriculum development, working in tandem. The BOP-CCERS Model™ also validates that with appropriate application of technical infrastructure, intensive teacher professional developments, and curricular scaffolding, socially connected science learning can be mainstreamed in the nation’s largest urban public school system. This is evidenced and substantiated in the initial phases of BOP-CCERS™. The BOP-CCERS™ student curriculum and teacher professional development have been implemented in approximately 24% of NYC public middle schools, reaching more than 250 educators and 11,000 students directly. BOP-CCERS™ is a fully scalable and transferable educational model, adaptable to all American school districts. In all settings of the proposed Phase IV initiative, the primary beneficiary group will be underrepresented NYC public school students who live in high-poverty neighborhoods and are traditionally underrepresented in the STEM fields, including African Americans, Latinos, English language learners, and children from economically disadvantaged households. In particular, BOP-CCERS Phase IV will explicitly prepare underrepresented students for skilled positions within New York City’s expanding digital economy, computer science, computational information systems, and innovative technology sectors.

Keywords: computer science, data science, equity, diversity and inclusion, STEM education

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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An important tool for the enhancement of cultural sites is serious games (SG), i.e., games designed for educational purposes; SG is applied in cultural sites through trivia, puzzles, and mini-games for participation in interactive exhibitions, mobile applications, and simulations of past events. The combination of Augmented Reality (AR) and digital cultural content has also produced examples of cultural heritage recovery and revitalization around the world. Through AR, the user perceives the information of the visited place in a more real and interactive way. Another interesting technological development for the revitalization of cultural sites is the combination of AR and Global Positioning System (GPS), which integrated have the ability to enhance the user's perception of reality by providing historical and architectural information linked to specific locations organized on a route. To the author’s best knowledge, there are currently no applications that combine GPS AR and SG for cultural heritage revitalization. The present research focused on the development of an SG based on GPS and AR. The study area is the village of Caldana in Tuscany, Italy. Caldana is a fortified Renaissance village; the most important architectures are the walls, the church of San Biagio, the rectory, and the marquis' palace. The historical information is derived from extensive research by the Department of Architecture at the University of Florence. The storyboard of the SG is based on the history of the three characters who built the village: marquis Marcello Agostini, who was commissioned by Cosimo I de Medici, Grand Duke of Tuscany, to build the village, his son Ippolito and his architect Lorenzo Pomarelli. The three historical characters were modeled in 3D using the freeware MakeHuman and imported into Blender and Mixamo to associate a skeleton and blend shapes to have gestural animations and reproduce lip movement during speech. The Unity Rhubarb Lip Syncer plugin was used for the lip sync animation. The historical costumes were created by Marvelous Designer. The application was developed using the Unity 3D graphics and game engine. The AR+GPS Location plugin was used to position the 3D historical characters based on GPS coordinates. The ARFoundation library was used to display AR content. The SG is available in two versions: for children and adults. the children's version consists of finding a digital treasure consisting of valuable items and historical rarities. Players must find 9 village locations where 3D AR models of historical figures explaining the history of the village provide clues. To stimulate players, there are 3 levels of rewards for every 3 clues discovered. The rewards consist of AR masks for archaeologist, professor, and explorer. At the adult level, the SG consists of finding the 16 historical landmarks in the village, and learning historical and architectural information interactively and engagingly. The application is being tested on a sample of adults and children. Test subjects will be surveyed on a Likert scale to find out their perceptions of using the app and the learning experience between the guided tour and interaction with the app.

Keywords: augmented reality, cultural heritage, GPS, serious game

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Authors: Michal Pachocki

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This study investigates the effects of mobility in the context of a different environment and work culture through analysing the learners perception of their international work experience. Since this kind of professional training abroad is becoming more popular in Europe, mainly due to the EU funding opportunities, it is of paramount importance to assess its long-term impact on educational and career paths of former students. Moreover, the tracer study aimed at defining what professional, social and intercultural competencies were gained or developed by the interns and to which extent those competences proved to be useful meeting the labor market requirements. Being a populous EU member state which actively modernizes its vocational education system (also with European funds), Poland can serve as an illustrative case study to investigate the above described research problems. However, the examined processes are most certainly universal, wherever mobility is included in the learning process. The target group of this research was the former mobility participants and the study was conducted using quantitative and qualitative methods, such as the online survey with over 2 600 questionnaires completed by the former mobility participants; -individual in-depth interviews (IDIs) with 20 Polish graduates already present in the labour market; - 5 focus group interviews (FGIs) with 60 current students of the Polish vocational schools, who have recently returned from the training abroad. As the adopted methodology included a data triangulation, the collected findings have also been supplemented with data obtained by the desk research (mainly contextual information and statistical summary of mobility implementation). The results of this research – to be presented in full scope within the conference presentation – include the participants’ perception of their work mobility. The vast majority of graduates agrees that such an experience has had a significant impact on their professional careers and claims that they would recommend training abroad to persons who are about to enter the labor market. Moreover, in their view, such form of practical training going beyond formal education provided them with an opportunity to try their hand in the world of work. This allowed them – as they accounted for them – to get acquainted with a work system and context different from the ones experienced in Poland. Although the work mobility becomes an important element of the learning process in the growing number of Polish schools, this study reveals that many sending institutions suffer from a lack of the coherent strategy for planning domestic and foreign training programmes. Nevertheless, the significant number of graduates claims that such a synergy improves the quality of provided training. Despite that, the research proved that the transnational mobilities exert an impact on their future careers and personal development. However, such impact is, in their opinion, dependant on other factors, such as length of the training period, the nature and extent of work, recruitment criteria and the quality of organizational arrangement and mentoring provided to learners. This may indicate the salience of the sending and receiving institutions organizational capacity to deal with mobility.

Keywords: learning mobility, transnational training, vocational education and training graduates, tracer study

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Authors: E. Oliver, A. Cebolla, A. Dominguez, A. Gonzalez-Segura, E. de la Cruz, S. Albertini, L. Ferrini, K. Kronika, T. Nilsen, R. Baños

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The main objective of MEAL is to develop a pedagogical tool aimed to help teachers and nutritionists (students and professionals) to acquire, train, promote and deliver to children basic nutritional education and healthy eating behaviours competencies. MEAL is focused on eating behaviours and not only in nutritional literacy, and will use new technologies like Information and Communication Technologies (ICTs) and serious games (SG) platforms to consolidate the nutritional competences and habits.

Keywords: nutritional education, pedagogical ICT platform, serious games, training course

Procedia PDF Downloads 513

Authors: Antonio M. Oliveira, Patricia Oliveira-Silva, Jose Matias Alves, Gary McPherson

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The music teaching is oriented towards offering formal music training. Due to its specificities, this vocational program starts at a very young age. Although provided by the State, the offer is limited to 6 schools throughout the country, which means that the vacancies for prospective students are very limited every year. It is therefore crucial that these vacancies be taken by especially motivated children grown within households that offer the ideal setting for success. Some of the instruments used to evaluate musical performance are highly sensitive to specific previous training, what represents a severe validity problem for testing children who have had restricted opportunities for formal training. Moreover, these practices may be unfair because, for instance, they may not reflect the candidates’ music aptitudes. Based on what constitutes a prerequisite for making an excellent music student, researchers in this field have long argued that motivation, task commitment, and parents’ support are as important as ability. Thus, the aim of this study is: (1) to prepare an inventory of admission requirements in Australia, Portugal and Ireland; (2) to examine whether the candidates to music conservatories and parents’ level of motivation, assessed at three evaluation points (i.e., admission, at the end of the first year, and at the end of the second year), correlates positively with the candidates’ progress in learning a musical instrument (i.e., whether motivation at the admission may predict student musicianship); (3) an adaptation of an existing instrument to assess the motivation (i.e., to adapt the items to the music setting, focusing on the motivation for playing a musical instrument). The inclusion criteria are: only children registered in the administrative services to be evaluated for entrance to the conservatory will be accepted for this study. The expected number of participants is fifty (5-6 years old) in all the three frequency schemes: integrated, articulated and supplementary. Revisiting musical admission procedures is of particular importance and relevance to musical education because this debate may bring guidance and assistance about the needed improvement to make the process of admission fairer and more transparent.

Keywords: music learning, music admission requirements, student’s motivation, parent’s motivation

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Authors: Elham Shirvani-Ghadikolaei

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In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.

Keywords: educational neurosciences, embodied cognition, pedagogical neurosciences, phenomenology

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

Procedia PDF Downloads 164