Search results for: visual learning

Authors: Aisha Iddrisu

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The proliferation of cyberviolence in the wave of increased social media consumption calls for immediate attention both at the local and global levels. With over 4.70 billion social media users worldwide and 8.8 social media users in Ghana, various forms of violence have become the order of the day in most countries and communities. Cyber violence is defined as producing, retrieving, and sharing of hurtful or dangerous online content to cause emotional, psychological, or physical harm. The urgency and severity of cyber violence have led to the enactment of laws in various countries though lots still need to be done, especially in Ghana. In Ghana, studies on cyber violence have not been extensively dealt with. Existing studies concentrate only on one form or the other form of cyber violence, thus cybercrime and cyber bullying. Also, most studies in Africa have not explored cyber violence forms using empirical theories and the few that existed were qualitatively researched, whereas others examine the effect of cyber violence rather than examining why those who involve in it behave the way they behave. It is against this backdrop that this study aims to examine various cyber violence behaviour among social media users in Ghana by applying the theory of Self-control and Social control theory. This study is important for the following reasons. The outcome of this research will help at both national and international level of policymaking by adding to the knowledge of understanding cyberviolence and why people engage in various forms of cyberviolence. It will also help expose other ways by which such behaviours are enforced thereby serving as a guide in the enactment of the rightful rules and laws to curb such behaviours. It will add to literature on consequences of new media. This study seeks to confirm or reject to the following research hypotheses. H1 Social media usage has direct significant effect of cyberviolence behaviours. H2 Ineffective parental management has direct significant positive relation to Low self-control. H3 Low self-control has direct significant positive effect on cyber violence behaviours among social, H4 Differential association has significant positive effect on cyberviolence behaviour among social media users in Ghana. H5 Definitions have a significant positive effect on cyberviolence behaviour among social media users in Ghana. H6 Imitation has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H7 Differential reinforcement has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H8 Differential association has a significant positive effect on definitions. H9 Differential association has a significant positive effect on imitation. H10 Differential association has a significant positive effect on differential reinforcement. H11 Differential association has significant indirect positive effects on cyberviolence through the learning process.

Keywords: cyberviolence, social media users, self-control theory, social learning theory

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Authors: Jaana Sepp, Ulvi Kõrgemaa, Kristi Puusepp, Õie Tähtla

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COVID-19 was officially recognized as a pandemic in late 2019 by the WHO, and it has led to changes in the education sector. Educational institutions were closed, and most schools adopted distance learning. Estonia is known as a digitally well-developed country. Based on that, in the pandemic time, nursing education continued, and new technological solutions were implemented. To provide nursing education, special focus was paid on quality and flexibility. The aim of this paper is to present administrative, digital, and technological solutions which support Estonian nursing educators to continue the study process in the pandemic time and to develop a sustainable solution for nursing education for the future. This paper includes the authors’ analysis of the documents and decisions implemented in the institutions through the pandemic time. It is a case study of Estonian nursing educators. Results of the analysis show that the implementation of distance learning principles challenges the development of innovative strategies and technics for the assessment of student performance and educational outcomes and implement new strategies to encourage student engagement in the virtual classroom. Additionally, hospital internships were canceled, and the simulation approach was deeply implemented as a new opportunity to develop and assess students’ practical skills. There are many other technical and administrative changes that have also been carried out, such as students’ support and assessment systems, the designing and conducting of hybrid and blended studies, etc. All services were redesigned and made more available, individual, and flexible. Hence, the feedback system was changed, the information was collected in parallel with educational activities. Experiences of nursing education during the pandemic time are widely presented in scientific literature. However, to conclude our study, authors have found evidence that solutions implemented in Estonian nursing education allowed the students to graduate within the nominal study period without any decline in education quality. Operative information system and flexibility provided the minimum distance between the students, support, and academic staff, and likewise, the changes were implemented quickly and efficiently. Institution memberships were updated with the appropriate information, and it positively affected their satisfaction, motivation, and commitment. We recommend that the feedback process and the system should be permanently changed in the future to place all members in the same information area, redefine the hospital internship process, implement hybrid learning, as well as to improve the communication system between stakeholders inside and outside the organization. The main limitation of this study relates to the size of Estonia. Nursing education is provided by two institutions only, and similarly, the number of students is low. The result could be generated to the institutions with a similar size and administrative system. In the future, the relationship between nurses’ performance and organizational outcomes should be deeply investigated and influences of the pandemic time education analyzed at workplaces.

Keywords: hybrid learning, nursing education, nursing, COVID-19

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Authors: Annisa Dewanti Putri, Wang Juan, Y. Qing Shan

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The structural assessment is one of a crucial part for ancient timber structure, in which this phase will be the reference for the maintenance and preservation phase. The mechanical properties of a structure are one of an important component of the structural assessment of building. Feiyun as one of the particular preserved building in China will become one of the Pioneer of Timber Structure Building Assessment. The 3-storey building which is located in Shanxi Province consists of complex ancient timber structure. Due to condition and preservation purpose, assessments (visual inspections, Non-Destructive Test and a Semi Non-Destructive test) were conducted. The stress wave measurement, moisture content analyzer, and the micro-drilling resistance meter data will overview the prediction of Mechanical Properties. As a result, the mechanical properties can be used for the next phase as reference for structural damage solutions.

Keywords: ancient structure, mechanical properties, non destructive test, stress wave, structural assessment, timber structure

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Mahmood Dehqan, Peyman Peyvasteh

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In recent years there has been a growing interest in issues concerning the impact of sociocultural theory (SCT) of learning on different aspects of second/foreign language learning. This study aimed to find the possible effects of sociocultural teaching techniques on reading strategy of EFL learners. Indeed, the present research compared the impact of peer and teacher scaffolding on EFL learners’ reading strategy use across two proficiency levels. To this end, a pre-test post-test quasi-experimental research design was used and two instruments were utilized to collect the data: Nelson English language test and reading strategy questionnaire. Ninety five university students participated in this study were divided into two groups of teacher and peer scaffolding. Teacher scaffolding group received scaffolded help from the teacher based on three mechanisms of effective help within ZPD: graduated, contingent, dialogic. In contrast, learners of peer scaffolding group were unleashed from the teacher-fronted classroom as they were asked to carry out the reading comprehension tasks with the feedback they provided for each other. Results obtained from ANOVA revealed that teacher scaffolding group outperformed the peer scaffolding group in terms of reading strategy use. It means teacher’s scaffolded help provided within the learners’ ZPD led to better reading strategy improvement compared with the peer scaffolded help. However, the interaction effect between proficiency factor and teaching technique was non-significant, leading to the conclusion that strategy use of the learners was not affected by their proficiency level in either teacher or peer scaffolding groups.

Keywords: peer scaffolding, proficiency level, reading strategy, sociocultural theory, teacher scaffolding

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Authors: Shimaa Nagro, Russell Campion

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Mobile devices are becoming ever more widely available, with growing functionality, and they are increasingly used as enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material's user interfaces for mobile devices is beset by many unresolved research problems such as those arising from constraints associated with mobile devices or from issues linked to effective learning. The proposed research aims to produce: (i) a method framework for the design and evaluation of educational material’s interfaces to be delivered on mobile devices, in multimedia form based on Human Computer Interaction strategies; and (ii) a software tool implemented as a fast-track alternative to use the method framework in full. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the method framework. The method framework is a framework to enable an educational designer to effectively and efficiently create educational multimedia interfaces to be used on mobile devices by following a particular methodology that contains practical and usable tools and techniques. It is a method framework that accepts any educational material in its final lesson plan and deals with this plan as a static element, it will not suggest any changes in any information given in the lesson plan but it will help the instructor to design his final lesson plan in a multimedia format to be presented in mobile devices.

Keywords: mobile learning, M-Learn, HCI, educational multimedia, interface design

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Authors: Behailu Bezabih Ayele

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Illustrative expressions in art education and in overall learning are being given increasing attention in the transmission of knowledge. The objective of this paper, therefore, is to present an analysis of graffiti on school desks-a way of smuggling knowledge on the edge of classroom education and learning. The methodological approach focuses on the systematic collection and selection of desk graffiti. Four schools are chosen to reflect socioeconomic status and gender composition. The analysis focused on the categorization of graffiti by genre. This was followed by an analysis of the style, intensity as well as content of the messages in terms of overall social impacts. The paper grounds the analysis by reviewing the literature on modern education and art education in the Ethiopian context, as well as the place of desk graffiti. The findings generally show that the school desks and the school environment, by and large, have managed to serve as vessels through which formal and informal knowledge is acquired, transmitted, engrained into the students and transformed into messages by the students. The desks have also apparently served as a springboard to maximize the interfaces between several ideas and disciplines and communications. However, the very fact that the desks serve as massive channels of expression and knowledge transmission also points to a lack of breadth availability of channels of expression, perhaps confounding the ability of classrooms as means of outlet of expression and documentation for the students. This points to the need for efforts in education policy and funding of artistic endeavors for young students.

Keywords: artistic expression, desk graffiti, education, school children, Ethiopia

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: O. Dvorak, M. Panek, E. Oberhofnerova, I. Sterbova

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Extractives contained in larch wood (Larix decidua, Mill.) reduce the service-life of exterior coating systems, especially transparent and semi-transparent. The aim of this work was to find out whether the initial several-week leaching of extractives from untreated wood in the exterior will positively affect the selected characteristics and the overall life of the semi-transparent oil-based coating. Samples exposed to exterior leaching for 10 or 20 weeks, and the reference samples without leaching were then treated with a coating system. Testing was performed by the method of artificial accelerated weathering in the UV chamber combined with thermal cycling during 6 weeks. The changes of colour, gloss, surface wetting, microscopic analyses of surfaces, and visual damage of paint were evaluated. Only 20-week initial leaching had a positive effect. Both to increase the color stability during aging, but also to slightly increase the overall life of the tested semi-transparent coating system on larch wood.

Keywords: larch wood, coating, durability. extractives

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Authors: Tarek Saadawi, Rosario Gennaro, Jonathan Akeley

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There is rapidly growing demand for professionals to fill positions in Cybersecurity. This is recognized as a national priority both by government agencies and the private sector. Cybersecurity is a very wide technical area which encompasses all measures that can be taken in an electronic system to prevent criminal or unauthorized use of data and resources. This requires defending computers, servers, networks, and their users from any kind of malicious attacks. The need to address this challenge has been recognized globally but is particularly acute in the New York metropolitan area, home to some of the largest financial institutions in the world, which are prime targets of cyberattacks. In New York State alone, there are currently around 57,000 jobs in the Cybersecurity industry, with more than 23,000 unfilled positions. The Cybersecurity Program at City College is a collaboration between the Departments of Computer Science and Electrical Engineering. In Fall 2020, The City College of New York matriculated its first students in theCybersecurity Master of Science program. The program was designed to fill gaps in the previous offerings and evolved out ofan established partnership with Facebook on Cybersecurity Education. City College has designed a program where courses, curricula, syllabi, materials, labs, etc., are developed in cooperation and coordination with industry whenever possible, ensuring that students graduating from the program will have the necessary background to seamlessly segue into industry jobs. The Cybersecurity Program has created multiple pathways for prospective students to obtain the necessary prerequisites to apply in order to build a more diverse student population. The program can also be pursued on a part-time basis which makes it available to working professionals. Since City College’s Cybersecurity M.S. program was established to equip students with the advanced technical skills needed to thrive in a high-demand, rapidly-evolving field, it incorporates a range of pedagogical formats. From its outset, the Cybersecurity program has sought to provide both the theoretical foundations necessary for meaningful work in the field along with labs and applied learning projects aligned with skillsets required by industry. The efforts have involved collaboration with outside organizations and with visiting professors designing new courses on topics such as Adversarial AI, Data Privacy, Secure Cloud Computing, and blockchain. Although the program was initially designed with a single asynchronous course in the curriculum with the rest of the classes designed to be offered in-person, the advent of the COVID-19 pandemic necessitated a move to fullyonline learning. The shift to online learning has provided lessons for future development by providing examples of some inherent advantages to the medium in addition to its drawbacks. This talk will address the structure of the newly-implemented Cybersecurity Master’s Program and discuss the innovations, challenges, and possible future directions.

Keywords: cybersecurity, new york, city college, graduate degree, master of science

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Authors: Salihu Abdullahi Galle

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Students' performance in Economics in schools and on standardized exams in Nigeria has been worrying throughout the years, owing to some teachers' use of conventional and lecture teaching methods. Other obstacles include a lack of training, standardized testing pressure, and aversion to change, all of which can have an impact on students' cognitive ability in Economics and future careers. The researchers employed formative evaluation with feedback (FEFB) to support the teaching and learning process by providing constant feedback to both teachers and students. The researchers employed a quasi-experimental research design to examine two teaching methods (FEFB and traditional). The pre-test and post-test interaction effects were evaluated between students in the experimental group (FEFB) and those in the conventional group. The interaction effects of pre-test and post-test on male and female in the two groups were also examined, with 90 participants. The findings show that students exposed to a FEFB-based teaching approach outperform pupils taught in a traditional classroom setting, and there is no gender interaction effect between the two groups. In light of these findings, the researchers urge that Economics teachers employ FEFB during teaching and learning to ensure timely feedback, and that policymakers ensure that Economics teachers receive training and re-training on FEFB approaches.

Keywords: formative evaluation with feedback (FEFB), students, economics achievement, secondary education

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Authors: Catarina Maria Neto Da Cruz, Ana Maria Reis D’Azevedo Breda

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The world is changing and, consequently, the young people need more sophisticated tools and skills to lead with the world’s complexity. The Organisation for Economic Co-operation and Development Learning Framework 2030 suggests an interdisciplinary knowledge as a principle for the future of education systems. In the curricular document Portuguese about the profile of students leaving compulsory education, the critical thinking and creative thinking are pointed out as skills to be developed, which imply the interconnection of different knowledge, applying it in different contexts and learning areas. Unlike primary school teachers, teachers specialized in a specific area lead to more difficulties in the implementation of interdisciplinary approaches in the classrooms and, despite the effort, the interdisciplinarity is not a common practice in schools. Statement like "Mathematics is everywhere" is unquestionable, however, many math teachers show difficulties in presenting such evidence in their classes. Mathematical modelling and problems in real contexts are promising in the development of interdisciplinary pedagogical practices and in Portugal there is a continuous training offer to contribute to the development of teachers in terms of their pedagogical approaches. But when teachers find themselves in the classroom, without a support, do they feel able to implement interdisciplinary practices? In this communication we will try to approach this issue through a case study involving a group of Mathematics teachers, who attended a training aimed at stimulating interdisciplinary practices in real contexts, namely related to the COVID-19 pandemic.

Keywords: education, mathematics, teacher training, interdisciplinarity

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Authors: Patricia P. M. C. Lourenco, Javier Bringué Sala, Anaisa D. A. de Sena

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Almost everyone in Dramaland knows the names of big Korean stars that grace their computer screens on a roll through social media and video streaming platforms that enable awareness of Korean dramas and lifestyle at a click. A surface culture instilled with notions of belonging has redefined the meaning of friendship and challenged deep inner values. Not everyone, however, knows Chinese Dramas or their stars, which is a consequence of Dramaland's focus on Korean dramas and promoting the Korean experience. Despite a parity in terms of production quality, star power, scripts and compelling visual settings, Chinese Dramas have been playing catch up to their famous counterparts. While they might have a strong competitive soft power for international drama fans, the soft power of Korean dramas is imbued with substantial societal values that they want to share with others. Those values are portrayed in an artistic way that connects with audiences who experience loneliness in the non-virtual world contrary to the way Chinese Dramas are perceived.

Keywords: Chinese dramas, fandom, Korean dramas, participatory culture, value perception, soft power, surface culture

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Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

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One of the main problems of the design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnel projects in which there is a number of tunnels and different professional teams involved. In this regard, comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels, such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate, and so forth, can be calculated and reported in a standard format.

Keywords: engineering geology, rock mass classification, rock mechanic, tunnel

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Authors: Odenigbo Veronica Ngozi, Lorreta Chika Ukwuaba

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This study focuses on how the strengthening adult literacy program can help accelerate transformative strategies to end female genital mutilation (FGM) in Nigeria, specifically in Nsukka Local Government Area. The research delves into the definition of FGM, adult literacy programs, and how to achieve ending FGM to attain Sustainable Development Goals (SDGs) in 2030. It further discusses the practice of FGM in Nigeria and emphasizes the statement of the problem. The main aim of the study is to investigate how strengthening adult literacy programs can help accelerate transformative strategies to end FGM in Nigeria and achieve SDGs in 2030. The researchers utilized a survey research design to conduct the study in Nsukka L.G.A. The population was composed of 26 facilitators and adult learners in five adult learning centers in the area. The entire population was used as a sample, and structured questionnaires were employed to elicit information. The items on the questionnaire were face-validated by three experts, and the reliability of the instrument was verified using Cronbach Alpha Reliability Technique. The research questions were analyzed using means and standard deviation while the hypothesis was tested at 0.05 level of degree of significance using a t-test. The findings show that through adult literacy program acceleration of transformative strategies, the practices of FGM can be ended. Strengthening adult literacy programs is a good channel to end or stop FGM through the knowledge and skill acquired from the learning centers. The theoretical importance of the study lies in the fact that it highlights the role of adult literacy programs in accelerating transformative strategies to combat harmful cultural practices such as FGM. It further supports the importance of education and knowledge in achieving sustainable development goals by 2030. Structured questionnaires were distributed to an entire population of 26 facilitators and adult learners in five adult learning centers in Nsukka L.G.A. The questionnaire items were face–validated by three experts, and the reliability of the instrument was verified using Cronbach Alpha Reliability Technique. The research questions were analyzed using means and standard deviation, while the hypothesis was tested using a t-test at 0.05 level of degree of significance. The study addressed the question of how strengthening adult literacy programs can help accelerate transformative strategies to end FGM in Nigeria and achieve SDGs by 2030. In conclusion, the study found that adult literacy is a good tool to end FGM in Nigeria. The recommendations were that government, non-governmental organizations (NGOs), Community-based organizations (CBOs), and individuals should support the funding and establishment of adult literacy centers in communities so as to reach every illiterate parent or individual and acquire the knowledge and skill needed to understand the negative effect of FGM in the life of a girl child.

Keywords: adult literacy, female genital mutilation, learning centers, SDGs, strengthening

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Authors: Muna F. Al-Sammaraie

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The aim of this research is to present a multi spectral image enhancement methods used to achieve highly real digital image populates only a small portion of the available range of digital values. Also, a quantitative measure of image enhancement is presented. This measure is related with concepts of the Webers Low of the human visual system. For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. This study involves changing the original values so that more of the available range is used; then increases the contrast between features and their backgrounds. It consists of reading the binary image on the basis of pixels taking them byte-wise and displaying it, calculating the statistics of an image, automatically enhancing the color of the image based on statistics calculation using algorithms and working with RGB color bands. Finally, the enhanced image is displayed along with image histogram. A number of experimental results illustrated the performance of these algorithms. Particularly the quantitative measure has helped to select optimal processing parameters: the best parameters and transform.

Keywords: image enhancement, multi-spectral, RGB, histogram

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Authors: Avi Shrivastava

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Our world continues to grapple with a lot of social issues. Economic growth and scientific advancements have not completely eradicated poverty, homelessness, discrimination and bias, gender inequality, health issues, mental illness, addiction, and other social issues. So, how do we improve the human condition in a world driven by advanced technology? The answer is simple: we will have to leverage technology to address some of the most important social challenges of the day. AI, or artificial intelligence, has emerged as a critical tool in the battle against issues that deprive marginalized and disadvantaged groups of the right to enjoy benefits that a society offers. Social work professionals can transform their lives by harnessing it. The lack of reliable data is one of the reasons why a lot of social work projects fail. Social work professionals continue to rely on expensive and time-consuming primary data collection methods, such as observation, surveys, questionnaires, and interviews, instead of tapping into AI-based technology to generate useful, real-time data and necessary insights. By leveraging AI’s data-mining ability, we can gain a deeper understanding of how to solve complex social problems and change lives of people. We can do the right work for the right people and at the right time. For example, AI can enable social work professionals to focus their humanitarian efforts on some of the world’s poorest regions, where there is extreme poverty. An interdisciplinary team of Stanford scientists, Marshall Burke, Stefano Ermon, David Lobell, Michael Xie, and Neal Jean, used AI to spot global poverty zones – identifying such zones is a key step in the fight against poverty. The scientists combined daytime and nighttime satellite imagery with machine learning algorithms to predict poverty in Nigeria, Uganda, Tanzania, Rwanda, and Malawi. In an article published by Stanford News, Stanford researchers use dark of night and machine learning, Ermon explained that they provided the machine-learning system, an application of AI, with the high-resolution satellite images and asked it to predict poverty in the African region. “The system essentially learned how to solve the problem by comparing those two sets of images [daytime and nighttime].” This is one example of how AI can be used by social work professionals to reach regions that need their aid the most. It can also help identify sources of inequality and conflict, which could reduce inequalities, according to Nature’s study, titled The role of artificial intelligence in achieving the Sustainable Development Goals, published in 2020. The report also notes that AI can help achieve 79 percent of the United Nation’s (UN) Sustainable Development Goals (SDG). AI is impacting our everyday lives in multiple amazing ways, yet some people do not know much about it. If someone is not familiar with this technology, they may be reluctant to use it to solve social issues. So, before we talk more about the use of AI to accomplish social work objectives, let’s put the spotlight on how AI and social work can complement each other.

Keywords: social work, artificial intelligence, AI based social work, machine learning, technology

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: José Francisco Urrutia Reyes, Judith Espinosa Real

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This paper is meant to re-examine the role of street art in the contemporary world. By studying this form of art in Brussels, it can be explained how murals show the socio-political reality of a given community and influence on its interaction. Through the definitions of street art, murals and street artists, and analysing their role in Brussels, it is possible to understand how this counter culture movement serves as an engine of social development, as it interacts with its surroundings sending a clear message to a wider audience. Street art impacts on its environment because it interacts with the people who occupies the day-to-day public space. This has proven to be effective in the arouse of social consciousness, up to the point of being adopted by the government of Brussels to promote social movements such as the AIDS-HIV campaign along with the Plate-Forme Prévention Sida. It can be concluded that street art has evolved since its vandalic beginnings, to become a form of art that has not lost it counter official status, but now has a critical vision that can promote social awakening. Street art is now a global trend that uses visual inputs to create a positive impact.

Keywords: street art, Brussels, social impact, political perspective

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Authors: Mark Anthony Casimiro, Ivan Culaba, Cornelia Soto

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Misconceptions are the wrong concepts understood by the students which may come up based on what they experience and observe around their environment. This seemed to hinder students’ learning. In this study, six different misconceptions were determined by the researcher from the previous researches. Teachers play a vital role in the classroom. The use of appropriate strategies can contribute a lot in the success of teaching and learning Physics. The current study aimed to compare two strategies- Interactive Lecture Demonstration (ILD) and Inquiry-Based Instruction (IBI) in addressing students’ misconceptions in electric circuits. These two strategies are both interactive learning activities and student-centered. In ILD, the teacher demonstrates the activity and the students have their predictions while in IBI, students perform the experiments. The study used the mixed method in which quantitative and qualitative researches were combined. The main data of this study were the test scores of the students from the pretest and posttest. Likewise, an interview with the teacher, observer and students was done before, during and after the execution of the activities. Determining and Interpreting Resistive Electric Circuits Test version 2 (DIRECT v.2) was the instrument used in the study. Two sections of Grade 9 students from Kalumpang National High School were the respondents of the study. The two strategies were executed to each section; one class was assigned as the ILD group and the other class was the IBI group. The Physics teacher of the said school was the one who taught and executed the activities. The researcher taught the teacher the steps in doing the two strategies. The Department of Education level of proficiency in the Philippines was adopted in scoring and interpretation. The students’ level of proficiency was used in assessing students’ knowledge on electric circuits. The pretest result of the two groups had a p-value of 0.493 which was greater than the level of significance 0.05 (p >0.05) and it implied that the students’ level of understanding in the topic was the same before the execution of the strategies. The posttest results showed that the p-value (0.228) obtained was greater than the level of significance which is 0.05 (p> 0.05). This implied that the students from the ILD and IBI groups had the same level of understanding after the execution of the two strategies. This could be inferred that either of the two strategies- Interactive Lecture Demonstration and Inquiry-Based Instruction could be used in addressing students’ misconception in electric circuit as both had similar effect on the students’ level of understanding in the topic. The result of this study may greatly help teachers, administration, school heads think of appropriate strategies that can address misconceptions depending on the availability of their materials of their school.

Keywords: inquiry- based instruction, interactive lecture demonstration, misconceptions, mixed method

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Authors: Keneilwe Matlhaku

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Crosslinguistic studies (theoretical and clinical) have shown delays and significant misarticulation in the acquisition of the rhotics. This article provides a detailed analysis of the early development of the rhotic phoneme, an apical trill /r/, by monolingual Setswana (Tswana S30) children of age ranges between 1 and 4 years. The data display the following trends: (1) late acquisition of /r/; (2) a wide range of substitution patterns involving this phoneme (i.e., gliding, coronal stopping, affrication, deletion, lateralization, as well as, substitution to a dental and uvular fricative). The primary focus of the article is on the potential origins of these variations of /r/, even within the same language. Our data comprises naturalistic longitudinal audio recordings of 6 children (2 males and 4 females) whose speech was recorded in their homes over a period of 4 months with no or only minimal disruptions in their daily environments. Phon software (Rose et al. 2013; Rose & MacWhinney 2014) was used to carry out the orthographic and phonetic transcriptions of the children’s data. Phon also enabled the generation of the children’s phonological inventories for comparison with adult target IPA forms. We explain the children’s patterns through current models of phonological emergence (MacWhinney 2015) as well as McAllister Byun, Inkelas & Rose (2016); Rose et al., (2022), which highlight the perceptual and articulatory factors influencing the development of sounds and sound classes. We highlight how the substitution patterns observed in the data can be captured through a consideration of the auditory properties of the target speech sounds, combined with an understanding of the types of articulatory gestures involved in the production of these sounds. These considerations, in turn, highlight some of the most central aspects of the challenges faced by the child toward learning these auditory-articulatory mappings. We provide a cross-linguistic survey of the acquisition of rhotic consonants in a sample of related and unrelated languages in which we show that the variability and volatility in the substitution patterns of /r/ is also brought about by the properties of the children’s ambient languages. Beyond theoretical issues, this article sets an initial foundation for developing speech-language pathology materials and services for Setswana learning children, an emerging area of public service in Botswana.

Keywords: rhotic, apical trill, Phon, phonological emergence, auditory, articulatory, mapping

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Authors: Iyabo Aremu

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The role of the teacher in stirring a qualitative and distinctive knowledge-driven and value-laden environment with modern teaching practices cannot be over accentuated. In spite of the myriad advantages the use of Information and Communication Technology (ICT) promises, many teachers are still at the rear of this archetypical transition. These teachers; notable forces needed to elicit positive academic performances of students of higher learning are ill-equipped for the task. In view of this, the research work sought to assess how teachers have been able to effectively apply ICT tools to improve students’ academic performance in the higher institution and to evaluate the challenges faced by teachers in using these tools. Thus, the research adopted descriptive survey research design and involved a sample of 25 lecturers from five schools in the study area: Adeniran Ogunsanya College of Education (AOCOED). The barrier to Teachers’ Use of ICT Questionnaire (BTUICTQ) was used to gather data from these respondents. The data gathered was tested with chi-square at 0.05 level of significance. The results revealed that the perception and attitude of teachers towards the use of ICT is not favourable. It was also discovered that teachers suffer from gaps in ICT knowledge and skills. Finally, the research showed that lack of training and inadequate support is a major challenge teacher contend with. The study recommended that teachers should be given adequate training and support and that teachers’ unrestricted access to ICT gadgets should be ensured by schools.

Keywords: ICT, teachers, AOCOED, academic performance

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Authors: Jonathan Bolduc

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Studies have demonstrated the effectiveness of music training approaches to help children with language disabilities. Because music is closely associated with a number of cognitive functions, including language, it has been hypothesized that musical skills transfer to other domains. Research suggests that music training strengthens basic auditory processing skills in dyslexic children and may ameliorate phonological deficits. Furthermore, music instruction has the particular advantage of being non-literacy-based, thus removing the frustrations that can be associated with reading and writing activities among children with specific learning disabilities. In this study, we assessed the effect of implementing an intensive music program on the development of language skills (phonological and reading) in 4- to 9-year-old children. Seventeen children (N=17) participated in the study. The experiment took place over 6 weeks in a controlled environment. Eighteen lessons of 40 minutes were offered during this period by two music specialists. The Dalcroze, Orff, and Kodaly approaches were used. A series of qualitative measures were implemented to document the contribution of music training to this population. Currently, the data is being analyzed. The first results show that learning music seems to significantly improve verbal memory. We already know that language disabilities are considered one of the main causes of school dropout as well as later professional and social failure. We aim to corroborate that an integrated music education program can provide children with language disabilities with the same opportunities to develop and succeed in school as their classmates. Scientifically, the results will contribute to advance the knowledge by identifying the more effective music education strategies to improve the overall development of children worldwide.

Keywords: music education, music, art education, language diasabilities

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Authors: Nami Takase

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Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Jorge Cortés, Alejandra Martínez, Carlos Pérez, Anaid Simón

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The presence of government, news media, and general citizenry in social media allows considering interactions between them as a form of political communication (i.e. the public exchange of contradictory discourses about politics). Twitter’s asymmetrical following model (users can follow, mention or reply to other users that do not follow them) could foster alternative democratic practices and have an impact on Mexican political culture, which has been marked by a lack of direct communication channels between these actors. The research aim is to assess Twitter’s role in political communication practices through the analysis of interaction dynamics between government, news media, and citizens by extracting and visualizing data from Twitter’s API to observe general behavior patterns. The hypothesis is that regardless the fact that Twitter’s features enable direct and horizontal interactions between actors, users repeat traditional dynamics of interaction, without taking full advantage of the possibilities of this medium. Through an interdisciplinary team including Communication Strategies, Information Design, and Interaction Systems, the activity on Twitter generated by the controversy over the presence of Uber in Mexico City was analysed; an issue of public interest, involving aspects such as public opinion, economic interests and a legal dimension. This research includes techniques from social network analysis (SNA), a methodological approach focused on the comprehension of the relationships between actors through the visual representation and measurement of network characteristics. The analysis of the Uber event comprised data extraction, data categorization, corpus construction, corpus visualization and analysis. On the recovery stage TAGS, a Google Sheet template, was used to extract tweets that included the hashtags #UberSeQueda and #UberSeVa, posts containing the string Uber and tweets directed to @uber_mx. Using scripts written in Python, the data was filtered, discarding tweets with no interaction (replies, retweets or mentions) and locations outside of México. Considerations regarding bots and the omission of anecdotal posts were also taken into account. The utility of graphs to observe interactions of political communication in general was confirmed by the analysis of visualizations generated with programs such as Gephi and NodeXL. However, some aspects require improvements to obtain more useful visual representations for this type of research. For example, link¬crossings complicates following the direction of an interaction forcing users to manipulate the graph to see it clearly. It was concluded that some practices prevalent in political communication in Mexico are replicated in Twitter. Media actors tend to group together instead of interact with others. The political system tends to tweet as an advertising strategy rather than to generate dialogue. However, some actors were identified as bridges establishing communication between the three spheres, generating a more democratic exercise and taking advantage of Twitter’s possibilities. Although interactions in Twitter could become an alternative to political communication, this potential depends on the intentions of the participants and to what extent they are aiming for collaborative and direct communications. Further research is needed to get a deeper understanding on the political behavior of Twitter users and the possibilities of SNA for its analysis.

Keywords: interaction, political communication, social network analysis, Twitter

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Authors: Manal Alosaimi

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Many rehabilitation strategies exist to aid persons with neurological disorders relearn motor skills through intensive training. Evidence supporting the theory that cortical areas involved in motor execution can be triggered by observing actions performed by others is attributed to the function of the mirror neuron system (MNS) indicates that activation of the MNS is associated with improvements in physical action and motor learning. Therefore, it is important to investigate the relationship between motor training (in this case, playing the drums) and the activation of the MNS. To achieve this, 15 healthy right-handed participants received drum-kit training for 21 weeks, during which time blood oxygen level-dependent (BOLD) signals were monitored in the brain using functional magnetic resonance imaging (fMRI). Participants were required to perform action–observation and action–execution fMRI tasks. The main results are that BOLD signals in classical regions of the MNS such as supramarginal gyri, inferior parietal lobule, and supplementary motor area increase significantly over the training period. Activation of these areas indicates that passive-observation of others performing these same skills may facilitate recovery of persons suffering from neurological disorders, and complement conventional rehabilitation programs that focus on action execution or intense training.

Keywords: fMRI, mirror neuron system, magnetic resonance imaging, neuroplasticity, drumming, learning, music, action observation, action execution

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Authors: Tatiani D. Mousoura

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Specific learning disability (SLD) in higher education has been partially explored in Greece so far. Moreover, opinions on professional perspectives for university students with SLD, is scarcely encountered in Greek research. The perceptions of the hidden character of SLD along with the university policy towards it and professional perspectives that result from this policy have been examined in the present research. This study has applied the paradigm of a Greek Tertiary Pedagogical Education Department (Early Childhood Education). Via mixed methods, data have been collected from different groups of people in the Pedagogical Department: students with SLD and without SLD, academic staff and administration staff, all of which offer the opportunity for triangulation of the findings. Qualitative methods include ten interviews with students with SLD and 15 interviews with academic staff and 60 hours of observation of the students with SLD. Quantitative methods include 165 questionnaires completed by third and fourth-year students and five questionnaires completed by the administration staff. Thematic analyses of the interviews’ data and descriptive statistics on the questionnaires’ data have been applied for the processing of the results. The use of medical terms to define and understand SLD was common in the student cohort, regardless of them having an SLD diagnosis. However, this medical model approach is far more dominant in the group of students without SLD who, by majority, hold misconceptions on a definitional level. The academic staff group seems to be leaning towards a social approach concerning SLD. According to them, diagnoses may lead to social exclusion. The Pedagogical Department generally endorses the principles of inclusion and complies with the provision of oral exams for students with SLD. Nevertheless, in practice, there seems to be a lack of regular academic support for these students. When such support does exist, it is only through individual initiatives. With regards to their prospective profession, students with SLD can utilize their personal experience, as well as their empathy; these appear to be unique weapons in their hands –in comparison with other educators− when it comes to teaching students in the future. In the Department of Pedagogy, provision towards SLD results sporadic, however the vision of an inclusive department does exist. Based on their studies and their experience, pedagogy students with SLD claim that they have an experiential internalized advantage for their future career as educators.

Keywords: specific learning disability, SLD, dyslexia, pedagogy department, inclusion, professional role of SLDed educators, higher education, university policy

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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