Search results for: mobile game based learning

Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: Mehmet Yanardag, Ilker Yilmaz

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Children with autism spectrum disorders (ASD) enjoy and success the aquatic-based exercise and play skills in a pool instead of land-based exercise in a gym. Some authors also observed that many children with ASD experience more success in attaining movement skills in aquatic environment. Properties of the water and hydrodynamic principles cause buoyancy of the water and decrease effects of gravity and it leads to allow a child to practice important aquatic skills with limited motor skills. Also, some authors experience that parents liked the effects of the aquatic intervention program on children with ASD such as improving motor performance, movement capacity and learning basic swimming skills. The purpose of this study was to investigate the effects of aquatic exercise training on water orientation and underwater working capacity were measured in the pool. This study included in four male children between 5 and 7 years old with ASD and 6.25±0.5 years old. Aquatic exercise skills were applied by using one of the error less teaching which is called the 'most to least prompt' procedure during 12-week, three times a week and 60 minutes a day. The findings of this study indicated that there were improvements test results both water orientation skill and underwater working capacity of children with ASD after 12-weeks exercise training. It was seen that the aquatic exercise intervention would be affected to improve working capacity and orientation skills with the special education approaches applying children with ASD in multidisciplinary team-works.

Keywords: aquatic, autism, orientation, ASD, children

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Authors: Mohammad Iqbal Maiik

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Islamic marketing ethics combines the principle of value maximization with the principles of equity and justice for the welfare of the society. Adherence to the Islamic ethics in the Islamic banking industry can help elevate the standards of both behavior and living of bankers and customers alike. In a rapidly changing marketing environment, the need to be customer-focused has never been as important as it is today. At present where customers are becoming more demanding and increasingly mobile between competing financial providers, being customer-focused is not enough. Islamic banks and more specifically their customer-contact employees (customer relation advisers or officers) need to be perceived by their customers as being Islamic. This study represents an initial step in analyzing the role of Islamic ethical sales behavior as it may be perceived by the customers of Islamic Banks.

Keywords: Islam, ethics, marketing, Islamic banks

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: Preeti Panthari, Harsha Kharkwal

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Myrica nagi belongs to Myricaceae family. It is known for its therapeutic use since ancient times. The leaves were extracted with methanol and further fractioned with different solvents with increasing polarity. The n-butanol fraction of methanol extract was passed through celite, on separation through silica gel column chromatography yielded ten fractions. For the first time we report isolation of Caffeic acid from n-butanol fraction of Myrica nagi leaves in Chloroform: methanol (70:30) fraction. The mobile phase used for analysis in HPLC was Methanol: water (60:40) at the flow rate of 1 ml/min at wavelength of 280 nm. The retention time was 2.66 mins.

Keywords: Myrica nagi, column chromatography, retention time, caffeic acid

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: S. Chee Choy, Pauline Swee Choo Goh, Yow Lin Liew

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The purpose of this study is to evaluate the English version and a Malay translation of the 21-item Learner Awareness Questionnaire for its application to assess student learning in higher education. The Learner Awareness Questionnaire, originally written in English, is a quantitative measure of how and why students learn. The questionnaire gives an indication of the process and motives to learn using four scales: survival, establishing stability, approval, and loving to learn. Data in the present study came from 680 university students enrolled in various programs in Malaysia. The Malay version of the questionnaire supported a similar four-factor structure and internal consistency to the English version. The four factors of the Malay version also showed moderate to strong correlations with those of the English versions. The results suggest that the Malay version of the questionnaire is similar to the English version. However, further refinement for the questions is needed to strengthen the correlations between the two questionnaires.

Keywords: student learning, learner awareness, questionnaire development, instrument validation

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Authors: Taksina Bunbut

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Personality and grooming are vital for creating professionalism and safety image for all staffs in the airline industry. Airline Business Program also has an aim to educate students through the subject Personality Development and Grooming in order to elevate the quality of students to meet standard requirements of the airline industry. However, students agree that there are many difficulties that cause unsuccessful learning experience in this subject. The research is to study problems that can afflict students from getting good results in the classroom. Furthermore, exploring possible solutions to overcome challenges are also included in this study. The research sample consists of 140 students who attended the class of Personality Development and Grooming. The employed research instrument is a questionnaire. Statistic for data analysis is t-test and Multiple Regression Analysis. The result found that although students are satisfied with teaching and learning of this subject, they considered that teaching in English and teaching topics in social etiquette in different cultures are difficult for them to understand.

Keywords: personality development, grooming, Airline Business Program, soft skill

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Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

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Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Justin D. Olmanson, Fitsum Abebe, Valerie Jones, Eric Kyle, Xianquan Liu, Katherine Robbins, Guieswende Rouamba

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The history of education technology--and designing, adapting, and adopting technologies for use in educational spaces--is nuanced, complex, and dynamic. Yet, despite a range of continually emerging technologies, the design and development process often yields results that appear quite similar in terms of affordances and interactions. Through this study we (1) verify the extent to which designs have been constrained, (2) consider what might account for it, and (3) offer a way forward in terms of how we might identify and strategically sidestep these influences--thereby increasing the diversity of our designs with a given technology or within a particular learning domain. We begin our inquiry from the perspective that a host of co-influencing elements, fields, and meta narratives converge on the education technology design process to exert a tangible, often homogenizing effect on the resultant designs. We identify several elements that influence design in often implicit or unquestioned ways (e.g. curriculum, learning theory, economics, learning context, pedagogy), we describe our methodology for identifying the elemental positionality embedded in a design, we direct our analysis to a particular subset of technologies in the field of literacy, and unpack our findings. Our early analysis suggests that the majority of education technologies designed for use/used in US public schools are heavily influenced by a handful of mainstream theories and meta narratives. These findings have implications for how we approach the education technology design process--which we use to suggest alternative methods for designing/ developing with emerging technologies. Our analytical process and re conceptualized design process hold the potential to diversify the ways emerging and established technologies get incorporated into our designs.

Keywords: curriculum, design, innovation, meta narratives

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

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Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

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Authors: Michael Brazley

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Virtual Reality (VR) and 3D videos are the most current generation of learning technology today. Virtual Reality and 3D videos are being used in professional offices and Schools now for marketing and education. Technology in the field of design has progress from two dimensional drawings to 3D models, using computers and sophisticated software. Virtual Reality is being used as collaborative means to allow designers and others to meet and communicate inside models or VR platforms using avatars. This research proposes to teach students from different backgrounds how to take a digital model into a 3D video, then into VR, and finally VR with multiple avatars communicating with each other in real time. The next step would be to develop the model where people from three or more different locations can meet as avatars in real time, in the same model and talk to each other. This research is longitudinal, studying the use of 3D videos in graduate design and Virtual Reality in XR (Extended Reality) courses. The research methodology is a combination of quantitative and qualitative methods. The qualitative methods begin with the literature review and case studies. The quantitative methods come by way of student’s 3D videos, survey, and Extended Reality (XR) course work. The end product is to develop a VR platform with multiple avatars being able to communicate in real time. This research is important because it will allow multiple users to remotely enter your model or VR platform from any location in the world and effectively communicate in real time. This research will lead to improved learning and training using Virtual Reality and Avatars; and is generalizable because most Colleges, Universities, and many citizens own VR equipment and computer labs. This research did produce a VR platform with multiple avatars having the ability to move and speak to each other in real time. Major implications of the research include but not limited to improved: learning, teaching, communication, marketing, designing, planning, etc. Both hardware and software played a major role in project success.

Keywords: virtual reality, avatars, education, XR

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Authors: Thelma Mort

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This empirical, qualitative research uses interviews of four intermediate phase English language student teachers at one university in South Africa and is an exploration of student teacher learning on their teaching practicum in their penultimate year of the initial teacher education course. The country’s post-apartheid language in education policy provides a context to this study in that children move from mother tongue language of instruction in foundation phase to English as a language of instruction in Intermediate phase. There is another layer of context informing this study which is the school context; the student teachers’ reflections are from their teaching practicum in resource constrained schools, which make up more than 75% of schools in South Africa. The findings were that in these schools, deep biases existed to local languages, that language was being used as a proxy for social class, and that conditions necessary for language acquisition were absent. The student teachers’ attitudes were in contrast to those found in the schools, namely that they had various pragmatic approaches to overcoming obstacles and that they saw language as enabling interdisciplinary work. This study describes language issues, tensions created by policy in South African schools and also supplies a regional account of learning to teach in resource constrained schools in Cape Town, where such language tensions are more inflated. The central findings in this research illuminate attitudes to language and language education in these teaching practicum schools and the complexity of learning to be a language teacher in these contexts. This study is one of the few local empirical studies regarding language teaching in the classroom and language teacher education; as such it offers some background to the country’s poor performance in both international and national literacy assessments.

Keywords: language teaching, narrative, post apartheid, South Africa, student teacher

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Authors: Kate Barnett-Richards, Marie Sams

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As the need for integration between students and industry grows, classroom practitioners must find ways of engaging students whilst also involving industry professionals to help shape the changing nature of university level education. As part of a project funded by the Disruptive Media Learning Lab at Coventry University, traditional case study based seminars on two modules were replaced by interactive live cases. Utilising Google+ as a social media platform allowed students and industry professional to come together and share ideas on a range of current issues. As technology becomes an ever increasingly important part of the higher education landscape, classroom practitioners need to adapt and find ways of utilising technological tools which can enhance the overall classroom experience. Given that many of these innovations come from the individuals involved in delivering classroom based sessions it is vital to share ideas, experiences and best practices so as to allow and encourage others to use the numerous free tools and platforms available. This poster presents the reflections, challenges, and problems faced by education practitioners when engaging students with industry partners in live case study discussions via Google+ within a classroom setting. It is expected that this poster will be of interest to a number of academics and teaching fellows who may be considering utilising social media tools to connect their students with industry.

Keywords: case study, Google+, practitioner, reflections.

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Authors: Canan Duzan

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For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

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Authors: Narendra Babu Bommenahalli Veerabhadrappa

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Teaching sustainability concepts along with profit maximizing philosophy of business in management education is a challenge. This paper explores and evaluates various learning models to inculcate sustainability concepts in management education. The paper explains about a new pedagogy that was tested in a business management school (Indus Business Academy, Bangalore, India) to teach sustainability. The pedagogy was designed by intertwining concepts related to sustainability with digital marketing concepts. As part of this experimental method, students (in groups) were assigned with various topics of sustainability and were asked to work with concepts of digital marketing and thus market the concepts of sustainability. The paper explains as a case study as to how sustainability was integrated with digital marketing tools and how learning towards sustainability was facilitated. It also explains the outcomes of this pedagogical method, in terms of inculcating sustainability concepts amongst management students as well as marketing and proliferation of sustainability concepts to bring about the behavioral changes amongst target audience towards sustainability.

Keywords: management-education, pedagogy, sustainability, behavior

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Tayyab Ahmad, Gerard Healey

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Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

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Authors: Nouzha Yasmina Soulimane-Benhabib

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Language is a medium of communication and a means of expression that is why today the learning of foreign languages especially the English language has become a basic necessity for every student who is ambitious. It is known that culture and language are inseparable and complementary, however, in the process of teaching a foreign language, teachers used to focus mainly on preparing adequate syllabi for ESP students, yet, some parameters should be considered. For instance; the culture of the target language may play an important role since students attitudes towards a foreign language enhance their learning or vice versa. The aim of this study is to analyse how culture could influence the teaching of a foreign language, we have taken the example of the English language as it is considered as the second foreign language in Algeria after French. The study is conducted at the Preparatory School of Sciences and Techniques, Tlemcen where twenty-five students participated in this research. The reasons behind learning the English language are various, and since English is the most widely-spoken language in the world, it is the language of research and education and it is used in many other fields, we have to take into consideration one important factor which is the social distance between the culture of the Algerian learner and the culture of the target language, this gap may lead to a culture shock. Two steps are followed in this research: The first one is to collect data from those students who are studying at the Preparatory School under the form of questionnaire and an interview is submitted to six of them in order to reinforce our research and get effective and precise results, and the second step is to analyse these data taking into consideration the diversity of the learners within this institution. The results obtained show that learners’ attitudes towards the English community and culture are mixed and it may influence their curiosity and attention to learn. Despite of big variance between Algerian and European cultures, some of the students focused mainly on the benefits of the English language since they need it in their studies, research and a future carrier, however, the others manifest their reluctance towards this language and this is mainly due to the profound impact of the English culture which is different from the Algerian one.

Keywords: Algeria, culture, English, impact

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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Authors: Abraham Motlhabane

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In most practical-related science lessons, the focus is on completing the experimental procedure as directed by the teacher. However, the scientific discourse among learners themselves and teacher–learner discourse about scientific processes, scientific inquiry and the nature of science should play an important role in the teaching and learning of science. This means the incorporation of inquiry-based activities aimed at sparking debates about scientific concepts. This article analyses a science lesson presented by a teacher to his colleagues acting as learners. Six lessons were presented and transcribed. One of the lessons has been used for this study as the basis for the events as they unfolded during the lesson. Data was obtained through direct observations and the use of a predetermined observation schedule. Field notes were compiled during teacher preparations and the presentation of the lessons.

Keywords: discourse, inquiry, practical work, science, scientific

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Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias

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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.

Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution

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Authors: Amani Hamdan

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A post-workshop of higher-order thinking skills (HOTS), for faculty from diverse academic disciplines, was conducted and the researcher surveyed the participants’ intentions and plans to include HOTS as a goal, as learning and teaching task in their practices. Follow-up interviews with a random sample of participants were used to determine if they fulfilled their intentions three 3 months after the workshop. The degree of planned and enacted HOTS then was analyzed against the post-workshop HOT ability and knowledge. This is one topic that has not been adequately explored in faculty professional development literature where measuring the effect of learning on their ability to use what they learned. This qualitative method study explored a group of male and female faculty members (n=85) enrolled in HOTS 2 day workshop. The results showed that 89% of faculty members although were mostly enthused to apply what they learned after a 3 months period they were caught up with routine presentations and lecturing.

Keywords: higher education, faculty development, Saudi Arabia, higher order thinking skills

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Hubert Pun

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When a manufacturer outsources the production of a product, it distributes its intellectual property (IP) into a supply chain that it may not be able to fully control. An IP agreement between a manufacturer and its suppliers is a popular solution to address the challenge of supplier-copycatting. The goal of this paper is to examine the impact of copycatting, from both the supplier and third-party firms, and the effectiveness of an IP agreement. Specifically, we use a game-theoretic approach to examine a system where a manufacturer outsources to a supplier. The supplier and a third-party firm decide whether or not to enter the market with copycat products while the manufacturer selects the level of marketing investment. The manufacturer can reduce the threat of supplier-copycatting by signing an IP agreement. We find that the manufacturer can be worse off from signing an IP agreement with its supplier, even if the IP agreement is costless and perfectly enforceable. We show that a manufacturer can deter copycat products through vertical integration and IP agreements and we outline the instances where each method is preferred. Furthermore, we find that the manufacturer may choose not to invest in quality improvements as a copycat deterrence strategy. We show that the supplier can benefit from the manufacturer’s decision to sign an IP agreement and that the supplier and the consumers can benefit from government regulations against copycat products. Our paper demonstrates the strengths and limitations of various copycat deterrence strategies when a supplier and third-party may produce copycat products.

Keywords: coopetitive supply chain, copycat, government regulation, intellectual property

Procedia PDF Downloads 164