Search results for: social and emotional learning

Authors: Christa Beyers

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Investing in the health of youth is essential for the well-being of society. If youth do not live a healthy life, the future of the global workforce and overall development of adolescents looks bleak given the challenges posed in this developmental stage. The idea of sexuality education at home and in our schools is a controversial and contentious subject, as many parents and teachers do not hold the same beliefs as to what content should be taught. Despite high incidence of HIV and STD infections, early school dropout and teen pregnancies, sexuality education has still not been given the recognition or importance it deserves. By giving youth a voice can lead to both behavioural and policy changes. This article is based on a literature review of sex and sexuality education from a social studies approach. This article argues that adults tend to teach from their own perspective, which does not meet the needs of youth, thereby ignoring the social aspects of sexual behaviour.

Keywords: sexuality education, adolescents, communication, cycle of socialization

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Authors: Jelena Kovačević Vorgučin, Sibila Petenji Arbutina

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The postmodern age brings a rapid development of technology which inevitably leads to man's need to adapt to modern lifestyle. On the one hand, technological achievements have made human life easier, but there are numerous risks involved. Moreover, man's awareness and perception is changing and adapting unconsciously to the world we live in, while communication in the 21st century is predominantly based on the consumption of images. This paper presents sociological aspects of a community which is confined due to turbulent political-economic circumstances and its impact on the development of media literacy in Serbia. Previous researches led to the conclusion that the media culture is on an extremely low level, and that it can have a strong influence on the general development of the society, starting from the youngest segment of the population. Our aim is to use the conceptual authorial photographs inspired by the obtained research results to emphasize the importance that the impact of visual art has in delivering the message, its role in education and in raising awareness of universal social problems. The paper presents a number of stages involved in the conceptual project which is designed to last over a longer period of time in order to facilitate dissemination of information. First, a survey was carried out in several preschool institutions. This resulted in obtaining the necessary information on the habitual use of the medium of television in children and their carers-parents. The second stage focused on the relationship between the parent and the child in TV consumption. Further, an overview of the visual part of the project was made, which consisted of photographs in various dimensions, ranging from miniature to large dimensions, and following various exhibition principles in both gallery and alternative spaces. This stage of the project placed particular emphasis on the non-standard exhibiting formats and alternative exhibition principles which are increasingly present in all kinds of visual art aimed at achieving a higher level of information noticing and memorizing. The motif on the authorial photographs is children's portraits taken while they are watching different television contents, with emphasis on their emotional response. The importance of the medium of TV is particularly emphasized due to the fact that its consumption is the highest, even though there are newer and more advanced information-technological achievements. The already realized part of the project was used for an analysis of the results in the last stage of the project, which led to the conclusion that the response to the entire visual expression campaign was extremely positive, and action as such very useful indeed. The results obtained speak in favour of widening and continuation of the project, both on a greater number of sites locally as well as in other communities in Serbia with the aim of guiding people towards meaningful consumption of the television medium.

Keywords: alternative space exhibiting, children and TV, conceptual portrait photography, media literacy

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Authors: Frederick Nyakudya

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In this paper, we examine the relationship between human capital, personal wealth and social capital to explain the differential start-up rates between female and male entrepreneurs. Since our dependent variable is dichotomous, we examine the determinants of these using a maximum likelihood logit estimator. We used the Global Entrepreneurship Monitor database covering the period 2006 to 2009 with 421 usable cases drawn from drawn from the Lower Layer Super Output Areas in the East Midlands in the United Kingdom. we found evidence that indicates that a female positively moderate the positive relationships between indicators of human capital, personal wealth and social capital with start-up activity. The findings have implications for programs, policies, and practices to encourage more females to engage in start-up activity.

Keywords: entrepreneurship, star-up, gender, GEM

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Csilla Marianna Szabó

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In Hungary, the society has changes a lot for the past 25 years, and these changes could be detected in educational situations as well. The number and the intensity of conflicts have been increased in most fields of life, as well as at schools. Teachers have difficulties to be able to handle school conflicts. What is more, the new net generation, generation Z has values and behavioural patterns different from those of the previous one, which might generate more serious conflicts at school, especially with teachers who were mainly socialising in a traditional teacher – student relationships. In Hungary, the bill CCIV, 2011 declared the foundation of Institutes of Teacher Training in higher education institutes. One of the tasks of the Institutes is to survey the competences and needs of teachers working in public education and to provide further trainings and services for them according to their needs and requirements. This job is supported by the Social Renewal Operative Programs 4.1.2.B. The Institute of Teacher Training at the College of Dunaújváros, Hungary carried out a questionnaire and surveyed the needs and the requirements of teachers working in the Central Transdanubian region. Based on the results, the professors of the Institute of Teacher Training decided to meet the requirements of teachers and launch short courses in spring 2015. One of the courses is going to focus on school conflict management through mediation. The aim of the pilot course is to provide conflict management techniques for teachers presenting different mediation techniques to them. The theoretical part of the course (5 hours) will enable participants to understand the main points and the advantages of mediation, while the practical part (10 hours) will involve teachers in role plays to learn how to cope with conflict situations applying mediation. We hope if conflicts could be reduced, it would influence school atmosphere in a positive way and the teaching – learning process could be more successful and effective.

Keywords: conflict resolution, generation Z, mediation, teacher training

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Authors: Deepak Jugran

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Purpose: The purpose of this study is to identify how past Pandemics shaped social evolution and cities. Methodology: A historical and comparative analysis of major historical pandemics in human history their origin, transmission route, biological response and the aftereffects. A Comprehensive pre & post pandemic scenario and focuses selectively on major issues and pandemics that have deepest & lasting impact on society with available secondary data. Results: Past pandemics shaped the behavior of human societies and their cities and made them more resilient biologically, intellectually & socially endorsing the theory of “Survival of the fittest” by Sir Charles Darwin. Pandemics & Infectious diseases are here to stay and as a human society, we need to strengthen our collective response & preparedness besides evolving mechanisms for strict controls on inter-continental movements of people, & especially animals who become carriers for these viruses. Conclusion: Pandemics always resulted in great mortality, but they also improved the overall individual human immunology & collective social response; at the same time, they also improved the public health system of cities, health delivery systems, water, sewage distribution system, institutionalized various welfare reforms and overall collective social response by the societies. It made human beings more resilient biologically, intellectually, and socially hence endorsing the theory of “AGIL” by Prof Talcott Parsons. Pandemics & infectious diseases are here to stay and as humans, we need to strengthen our city response & preparedness besides evolving mechanisms for strict controls on inter-continental movements of people, especially animals who always acted as carriers for these novel viruses. Pandemics over the years acted like natural storms, mitigated the prevailing social imbalances and laid the foundation for scientific discoveries. We understand that post-Covid-19, institutionalized city, state and national mechanisms will get strengthened and the recommendations issued by the various expert groups which were ignored earlier will now be implemented for reliable anticipation, better preparedness & help to minimize the impact of Pandemics. Our analysis does not intend to present chronological findings of pandemics but rather focuses selectively on major pandemics in history, their causes and how they wiped out an entire city’s population and influenced the societies, their behavior and facilitated social evolution.

Keywords: pandemics, Covid-19, social evolution, cities

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Authors: Madifedile Thasi, Azola Mayeza

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In South Africa, provision of housing to the growing population has been described as one of the greatest challenges facing the government. Between 1994 to 2015, more than 2.5 million housing units were provided by the government for the poorest households and the low-income earners under the Reconstruction and Development Programme (RDP). Yet, the latest census figure revealed that about 2.1 million households still live in shacks and informal dwellings. Human settlements patterns remain dysfunctional across in South Africa because of rapid urbanisation. The housing backlog is growing at a rate of 178 000 units a year. The aforementioned predicament calls the need for innovative approaches to address the issue in a sustainable way and this need not be overemphasized. Aside from the issue of cost, the delivery of more housing units comes with environmental and sustainability issues. The prefabrication building technology has resulted into accelerated housing delivery to a satisfactory level in some countries such as Nigeria and Malaysia that are facing similar issue. It is therefore expected to be a foremost option to address the social housing backlog in South Africa and within the country housing sustainability agenda. This paper appraises the factors responsible for the limited implementation of prefabrication technology in South African housing projects. The objective is to recommend the method and materials that can be best sustained in the country in terms of local availability, cost effectiveness and environmental friendliness. It presents empirical data to support the hypothesis that a wider implementation of prefabrication technology in the social housing projects will be of significant benefit, by providing fast turnaround, cost-effective and sustainable solution that will dent the housing backlog, as well as improving the quality of the social housings. It was found that only 17 000 units of the RDP housings provided were constructed using alternative building technologies. Furthermore, there are variety of prefabricated technologies in the market but mostly have limited production capacity, minimal manufacturing capacity and most materials are imported, which leads to unavailability of the technology for large scale delivery and utilization despite its obvious advantages.

Keywords: prefabrication technology, sustainable social housings, South Africa, housing delivery

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Authors: Rose Hattab

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Women have been an important dynamic in religious context and the state-building process of Arab countries throughout history. During the 1970s as the movement for women’s activism and rights developed, the Iraqi state under the Ba’ath Party began to provide Iraqi women with legal and civil rights. This was done to liberate women from the grasps of social traditions and was a tangible espousing of equality between men and women in the process of nation-building. Whereas women’s rights were stronger and more supported throughout the earliest years of the Ba’ath Regime (1970-1990), the aftermath of the Gulf War and economic sanctions on the conditions of Iraqi society laid the foundation for a division of women’s rights between civil and religious authorities. Personal status codes that were secured in 1959 were being pushed back by amendments made in coordination with religious leaders. Civil laws were present on paper, but religious authority took prominence in practice. The written legal codes were inclusive of women’s rights, but there is not an active or ensured practice of these rights within Iraqi society. This is due to many different factors, such as religious, sectarian, political and conservative reasons that hold back or limit the ability for Iraqi women to have autonomy in aspects such as participation in the workforce, getting married, and ensuring social justice. This paper argues that the Personal Status Code introduced in 1959 – which replaced Sharia-run courts with personal status courts – provided Iraqi women with equality and increased mobility in social and economic dynamics. The statewide crisis felt after the Gulf War and the economic sanctions imposed by the United Nations led to a stark shift in the Ba’ath party’s political ideology. This ideological turn guided the social system to the embracement of social conservatism and religious traditions in the 1990s. The effect of this implementation continued after the establishment of a new Iraqi government during 2003-2005. Consequently, Iraqi women's rights in employment, marriage, and family became divided into paper and practice by religious authorities and civil law from that period to the present day. This paper also contributes to the literature by expanding on the gap between legal codes on paper and in practice, through providing an analysis of Iraqi women’s rights in the Iraqi Constitution of 2005 and Iraq’s Penal Code. The turn to conservative and religious traditions is derived from the multiplicity of identities that make up the Iraqi social fabric. In the aftermath of a totalitarian regime, active wars, and economic sanctions, the Iraqi people attempted to unite together through their different identities to create a sense of security in the midst of violence and chaos. This is not an excuse to diminish the importance of women’s rights, but in the process of building a new nation-state, women were lost from the narrative. Thus, the presence of gender equity is found in the written text but is not practiced and upheld in the social context.

Keywords: civil rights, Iraqi women, nation building, religion and conflict

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Authors: Lama Ajinah

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Luxury brands witnessed continuous growth which followed women’s desire towards individual distinctiveness and social glare. Bags are a woman’s best friend either for aesthetic or functional purposes when she leaves her home for leisure or work. One way of women constant aspiration for being distinguished while reflecting their wealth is through handbags. Subsequently, the demand and attraction by consumers towards the dazzle of luxurious brands for personal pleasure and social status have flourished. According to the literature review, a visual analysis on luxury brands has been explored yet a focus on bags was not discussed in details. Hence, a deep analysis will be dedicated on the two segments by showcasing examples of high-end bag advertising. The research is conducted to understand advertising strategies used in promoting for luxurious products. Furthermore, the paper explores the definition of the term luxury, the condition in which it is used in, and the visual language used along with the term. As luxury is an indicator of superior satisfaction, it is obtained on two levels: a personal and a social level. The examples of luxury brand ads are selected from the last five years to uncover the latest, most common strategies used to promote for luxurious brands. The methods employed in this paper consist of literature review, semiotic analysis, and content analysis. The researcher concludes with revealing the methods used in advertising while categorizing them into various themes.

Keywords: advertising, brands, fashion, graphic design, luxury, semiotic analysis, semiology, visual analysis, visual communication

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Authors: Yu Ling Chang

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Since the United Nations announced Universal Declaration of Human Rights in 1948, people are paying more and more attention to the value of lives. On the other hand, life education is being vigorously pushed in different countries. Unfortunately, the results have been only moderately successful by reason that the concept is not implemented in everyone’s daily life. Even worse, animal abuse and killing events keep happening. This research is focused on generalizing a conclusion from different countries’ Animal Protection Act and actual execution by case studies, in order to make an approach of whether the number of animal abuse is directly influenced by different laws and regimes or not. It concludes the central notion and spirit of Animal Protection Act in German, Japan, and Taiwan. Providing the reference of specific schemes and analysis based on Taiwanese social culture.

Keywords: animal abuse, Animal Management Act, Animal Protection Act, social culture

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Authors: Tam Nguyen

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Self-leadership is strongly tied to the ability to be resilient in the face of adversity. This study aims to demonstrate how a strategy based on a culturally relevant "bamboo metaphor" enables Asian students to cross cultural boundaries and to engage in online discussions to unlock their self-leadership potential. Asian students are influenced to varying degrees by the Confucian heritage culture, which educates students to respect authority, maintain harmony, and avoid public confrontations. This has a significant impact on the cultural readiness of Asian students to express their development as self-leaders. In this research project, researchers as mentors individually assist students, cultivate cognitive progress, encourage and personally ask students to join a process of mentorship program. This study analyzes and interprets the data from a large online seminar in Ho Chi Minh City, Vietnam, where students were trained in self-leadership skills. Focus-group interviews were implemented among 90 students in the program. Findings reveal the emotional needs of Asian students and suggest a cognitive model for developing students' self-awareness, self-confidence, and self-efficacy. The research results are anticipated to be applicable to a broader Asian population with a comparable cultural environment to Vietnam.

Keywords: self-leadership, bamboo resilience, cognitive modeling, Asian culture

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Authors: Ampai Muensit, Maniemai Thongyou, Patcharin Lapanun

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Teen mothers have been viewed as ‘a powerless’ facing numerous pressures including poverty, immaturity of motherhood, and especially social blame.This paper argues that, to endure as an agent, they keep struggling to overcome all difficulties in their everyday life by using certain symbols to negotiate the situations they encounter, and to obtain a social position without surrendering to the dominating socio-cultural structure. Guided by Bourdieu’s theory of practice, this study looks at how teen mothers use symbolic capital in their motherhood practices. Although motherhood practices can be found in different contexts with various types of capital utilization, this paper focuses on the use of symbolic capitals in teen mothers’ practices within the contexts of the community. The study employs a qualitative methodology; data was collected from 12 informants through life history, in-depth interview, observation and the content analytical method was employed for data analysis. The findings show that child and motherhood were key symbolic capitals in motherhood practices. Employing such capitals teen mothers can achieve an acceptance from community – particularly from the new community. These symbolic capitals were the important sources of teen mothers’ power to turn the tide by changing their status – from “the powerless” to be “the agent”. The use of symbolic capitals also related to habitus of teen mothers in better compromising for an appropriate social position.

Keywords: teen mother, motherhood practice, symbolic capital, community

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Authors: Elisa Monteiro, Kiiko Ikegami

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The inclusion of children with diverse learning needs and/or disabilities in regular classrooms has been identified as crucial to the provision of educational equity and quality for all students. In this, teachers play an essential role, as they have a strong impact on student attainment. Whilst the adoption of inclusive practice is increasing, with potential benefits for the teaching profession, there is also a rise in the level of its challenges in Macao as many more students with learning disabilities are now being included in general education classes. Consequently, there has been a significant focus on teacher professional development to ensure that teachers are adequately prepared to teach in inclusive classrooms that give access to diverse students. Major changes in teacher education will need to take place to include more inclusive education content and to equip teachers with the necessary skills in the area of inclusive practice. This paper draws on data from in-depth interviews with 20 teachers to examine teachers’ views of support, challenges, and barriers to inclusive practices at the school and classroom levels. Thematic analysis was utilised to determine major themes within the data. Several themes emerged and serve to illustrate the identified barriers and the potential value of effective teacher education. Suggestions for increased professional development opportunities for inclusive education specific to higher education institutions are presented and the implications for practice and teacher education are discussed.

Keywords: inclusion, inclusive practice, teacher education, higher education

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Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Wan-I Chen, Tsung-I Pai

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Future the society aging of population will create the social problem has not had the good mechanism solution in the Asian country, especially in Taiwan. In the future ten year the people in Taiwan must facing the condition which is localization aging social problem. In this situation, how to use the spatial in eco way to development space use to solve the old age spatial demand is the way which might develop in the future Taiwan society. Over the next 10 years, taking care of the aging people will become part of the social problem of aging phenomenon. The research concentrate in the feasibility of spatial substitution, secondary use of spatial might solve out of spatial problem for aging people. In order to prove the space usable, the research required to review the project with the support system and infill system for space experiment, by using network grid way. That defined community level of space elements location relationship, make new definitions of space and return to cooperation. Research to innovation in the the appraisal space causes the possibility, by spatial replacement way solution on spatial insufficient suitable condition. To evaluation community spatial by using the support system and infill system in order to see possibilities of use in replacement inner space and modular architecture into housing. The study is discovering the solution on the Eco way to develop space use to figure out the old age spatial demand.

Keywords: sustainable use, space conversion, integration, replacement


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Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla

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Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.

Keywords: open source communities, social network Analysis, time series, virtual communities

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Anne Allmrodt

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Regions of South-East Europe are characterised by high out-migration for decades. The reasons for leaving range from the hope of a better work situation to a better health care system and beyond. In Serbia, this high out-migration hits the rural areas in particular so that the population number is in the red repeatedly. It might not be hard to guess that this negative population growth has the potential to create different challenges for those who stay in rural areas. So how are they coping with the – statistically proven – high out-migration? Having this in mind, the study is investigating the people‘s individual awareness of the social phenomenon high out-migration and their daily life strategies in rural areas. Furthermore, the study seeks to find out the people’s resilient skills in that context. Is the condition of high out-migration conducive for resilience? The methodology combines a quantitative and a qualitative approach (mixed methods). For the quantitative part, a standardised questionnaire has been developed, including a multiple choice section and a choice experiment. The questionnaire was handed out to people living in rural areas of Serbia only (n = 100). The sheet included questions about people’s awareness of high out-migration, their own daily life strategies or challenges and their social network situation (data about the social network was necessary here since it is supposed to be an influencing variable for resilience). Furthermore, test persons were asked to make different choices of coping with high out-migration in a self-designed choice experiment. Additionally, the study included qualitative interviews asking citizens from rural areas of Serbia. The topics asked during the interview focused on their awareness of high out-migration, their daily life strategies, and challenges as well as their social network situation. Results have shown the following major findings. The awareness of high out-migration is not the same with all test persons. Some declare it as something positive for their own life, others as negative or not effecting at all. The way of coping generally depended – maybe not surprising – on the people’s social network. However – and this might be the most important finding - not everybody with a certain number of contacts had better coping strategies and was, therefore, more resilient. Here the results show that especially people with high affiliation and proximity inside their network were able to cope better and shew higher resilience skills. The study took one step forward in terms of knowledge about societal resilience as well as coping strategies of societies in rural areas. It has shown part of the other side of nowadays migration‘s coin and gives a hint for a more sustainable rural development and community empowerment.

Keywords: coping, out-migration, resilience, rural development, social networks, south-east Europe

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Adriana Salgado, Sandra Castaneda, Ivan Perez

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Learning to read and write is a complex process involving several cognitive skills, contextual, and cultural environments. The basis of this development is linguistic skills, such as the ability to name and understand vocabulary, retell a story, phonological awareness, letter knowledge, among others. In children with autism spectrum disorder (ASD), one of the main concerns is related to language disorders. Nevertheless, most of the children with ASD are able to decode written information but have difficulties in reading comprehension. The research of these processes in the Spanish-speaking population is limited. However, the increasing prevalence of this diagnosis (1 in 115 children) in Mexico has implications at different levels. Educational research is an important area of interest in ASD children, such as emergent literacy. Reading and writing expand the possibilities of academic, cultural, and social information access. Taking this information into account, the objective of this research was to identify the relationship between language skills, alphabet knowledge, phonological awareness, and early reading and writing in ASD Spanish-speaking children. The method used for this research was based on tasks that were selected, adapted and in some cases designed to measure initial reading and writing, as well as language skills (naming, receptive vocabulary, and narrative skills), phonological awareness (similar phonological word pairs, beginning sound awareness and spelling) and letter knowledge, in a sample of 45 children (38 boys and 7 girls) with prior diagnosis of ASD. Descriptive analyses, as well as bivariate correlations, cluster analysis, and canonical correspondence, were obtained for the data results. Results showed that variability was large; however, it was possible to characterize the sample in low, medium, and high score groups regarding children performance. The low score group (46.7% of the sample), had a null or deficient performance in language skills and phonological awareness, some could identify up to five letters of the alphabet, showed no early reading skills but they could scribble. The middle score group was characterized by a highly variable performance in different tasks, with better language skills in receptive and naming vocabulary, some narrative, letter knowledge, and phonological awareness (beginning sound awareness) skills. The high score group, (24.4% of the sample) had the best performance in language skills in relation to the sample data, as well as in the rest of the measured skills. Finally, scores were canonically correlated between naming, receptive vocabulary, narrative, phonological awareness, letter knowledge and initial learning of reading and writing skills for the high score group and letter knowledge, naming and receptive vocabulary for the lower score group, which is consistent with previous research in typical and ASD children. In conclusion, the obtained data is consistent with previous studies. Despite large variability, it was possible to identify performance profiles and relations based on linguistic, phonological awareness, and letter knowledge skills. These skills were predictor variables of the initial development of reading and writing. The above has implications for a future program and strategies development that may benefit the acquisition of reading and writing in ASD children.

Keywords: autism, autism spectrum disorders, early literacy, emergent literacy

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Selinda England, Ben Bodnaryk

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With an unprecedented increase in provincial immigration and government support for greater international and culturally diverse learners, a trade/applied learning-focused polytechnic with four campuses within one Canadian province saw the need for intercultural awareness and an intercultural teaching competence strategy for faculty training. An institution-wide pre-assessment needs survey was conducted in 2018, in which 87% of faculty professed to have some/no training when working with international and/or culturally diverse learners. After researching fellow Polytechnics in Canada and seeing very little in the way of faculty support for intercultural competence, an institutional project team comprised of members from all facets of the Polytechnic was created and included: Indigenous experts, Academic Chairs, Directors, Human Resource Managers, and international/settlement subject matter experts. The project team was organized to develop and implement a new academic model focused on enriching intercultural competence among faculty. Utilizing a competency based model, the project team incorporated inclusive terminology into competency indicators and devised a four-phase proposal for implementing intercultural teacher training: a series of workshops focused on the needs of international and culturally diverse learners, including teaching strategies based on current TESOL methodologies, literature and online resources for quick access when planning lessons, faculty assessment examples and models of interculturally proficient instructors, and future job descriptions - all which promote and encourage development of specific intercultural skills. Results from a post-assessment survey (to be conducted in Spring 2020) and caveats regarding improvements and next steps will be shared. The project team believes its intercultural and inclusive teaching competency-based model is one of the first, institution-wide faculty supported initiatives within the Canadian college and Polytechnic post-secondary educational environment; it aims to become a leader in both the province and nation regarding intercultural competency training for trades, industry, and business minded community colleges and applied learning institutions.

Keywords: cultural diversity and education, diversity training teacher training, teaching and learning, teacher training

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Authors: Stephanie Elizabeth Talder

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Art therapy is a field that is growing exponentially with new groundbreaking discoveries that allow for embodying trauma and mental healing. Applied theatre and performance is a continuously growing and developing field that can help people who are struggling to work through traumatic experiences plaguing their life. By using performance, there is an ability to target sensitive topics in a manner that does not lead to re-traumatization. The use of theatre as a healing agent has been going on for centuries, with clear applications beginning in Greek theatre and tragedy. When working with complex mental illness, issues such as PTSD, anxiety, and depression can be managed and worked through. A central component of drama therapy is the connection to community and self. The ability to connect mind-body to stories as well as to other people allows for healing to occur. There is the opportunity for healing through emotional catharsis and community building. Applied theatre in connection to the medical field can allow for there to be a meaningful impact made on mental health. Though there is still a significant amount of progress to be made within the stigmatization of mental health problems, bringing in a varying option that allows for there to be movement and community building possesses a strong ability to impact people in a positive way.

Keywords: applied theatre, drama therapy, art therapy, performance, theatre

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Authors: Elron Fouten

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Recently, debates surrounding the social relevance of psychology in South Africa have focussed on how the growing neoliberal rationality within academia has again resulted in the discipline catering to the needs of powerful social groupings to protect its own economic interests, rather than producing socially relevant knowledge. Consequently, this study aimed to conduct a content analysis of the recent research output of psychology masters students, to establish whether it has produced research that addresses local and national psychosocial issues and as such deemed socially relevant knowledge. The study sampled clinical, counselling, and research psychology masters theses from 16 South African universities submitted between 1998 and 2017. Overall, 2001 theses were sampled, which were analysed using qualitative content analysis predominantly based on the descriptive categories identified in similar studies using published journal articles. Results indicated that empirical qualitative theses, using systems-oriented theory and post-modern frameworks were most prevalent. Further, traditional topics within psychology had relatively more weighting compared to more social topics. Although a significant number of theses recruited participants from working-class or poor backgrounds, there was an overreliance on participants from urban areas located in some of the country’s wealthiest provinces. Despite a strong adult-centric focus, trends regarding participants’ race and gender roughly resembled current population demographics. Overall, the results indicate that psychology in South Africa, at least at university-level, is to some extent trying to engage with national psychosocial concerns. However, there are still several key areas which need to be addressed to ensure the continued social relevance of the discipline.

Keywords: adult-centric, content analysis, relevance, psychosocial

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Authors: Jana Beresova

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The paper presents a study carried out in 2015-2016 within the national scheme of research - VEGA 1/0106/15 based on theoretical research and empirical verification of the concept of intercultural communicative competence. It focuses on the current conception concerning target languages teaching compatible with the Common European Framework of Reference for Languages: Learning, teaching, assessment. Our research had revealed how the concept of intercultural communicative competence had been perceived by secondary-school teachers of English in Slovakia before they were intensively trained. Intensive workshops were based on the use of both authentic and instructional materials with the goal to support interculturally oriented language teaching aimed at challenging thinking. The former concept that supported the development of the students´ linguistic knowledge and the use of a target language to obtain information about the culture of the country whose language learners were learning was expanded by the meaning-making framework which views language as a typical means by which culture is mediated. The goal of the workshop was to influence English teachers to better understand the concept of intercultural communicative competence, combining theory and practice optimally. The results of the study will be presented and analysed, providing particular recommendations for language teachers and suggesting some changes in the National Educational Programme from which English learners should benefit in their future studies or professional careers.

Keywords: authentic materials, English language teaching, instructional materials, intercultural communicative competence

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

Procedia PDF Downloads 80