Search results for: human behaviors of learning and cooperation

Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Ammal M. Metwally, Lobna A. ElEtreby, Rehan M. Saleh, Ghada Abdrabou, Somia I. Salama, Amira Orabi, Mohamed Abdelrahman

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Hepatitis C virus infection is a public health threat in Egypt. To control infection, efforts should be spent to encourage healthy behavior. This study aimed to assess the level of behavioral development in order to create a positive environment for the adoption of the recommended behaviors. The study was conducted over one year from Jan. 2011 till Jan. 2012. Knowledge, attitude and behavior of 540 HCV patients and 102 of their contacts were assessed and the level of behavioral development was determined. The study revealed that the majority of patients and contacts knew that HCV infection is dangerous with perceived concern for early diagnosis and treatment. More than 75% knew the correct modes of transmission. The assessment showed positive attitudes towards the recommended practices with the intention to adopt those practices. Strategies to create opportunities to continue the recommended behaviors should be adopted together with the reinforcement of social support.

Keywords: hepatitis C virus, level of behavioral development, recommended behaviors

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Authors: Fiffy Hanisdah Saikim, Bruce Prideaux

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One of the aims of wildlife tourism is to educate visitors about the threats facing wildlife, in general, and the actions needed to protect the environment and maintain biodiversity. Annually, millions of tourists visit natural areas and zoos primarily to view flagship species such as rhinos and elephants. Venues rely on the inherent charisma of these species to increase visitation and anchor conservation efforts. Expected visitor outcomes from the use of flagships include raised levels of awareness and pro-conservation behaviors. However, the role of flagships in wildlife tourism has been criticized for not delivering conservation benefits for species of interest or biodiversity and producing negative site impacts. Furthermore, little is known about how the connection to a species influences conservation behaviors. This paper addresses this gap in knowledge by extending previous work exploring wildlife tourism to include the emotional connection formed with wildlife species and pro-conservation behaviors for individual species and biodiversity. This paper represents a substantial contribution to the field because (a) it incorporates the role of the experience in understanding how tourists connect with a species and how this connection influences pro-conservation behaviors; and (b) is the first attempt to operationalize Conservation Caring as a measure of tourists’ connection with a species. Existing studies have investigated how specific elements, such as interpretation or species’ morphology may influence programmatic goals or awareness. However, awareness is a poor measure of an emotional connection with an animal. Furthermore, there has not been work done to address the holistic nature of the wildlife viewing experience, and its subsequent influence on behaviors. Results based on the structural equation modelling, support the validity of Conservation Caring as a factor; the ability of wildlife tourism to influence Conservation Caring; and that this connection is a strong predictor of conservation awareness behaviors. These findings suggest wildlife tourism can deliver conservation outcomes. The studies in this paper also provide a valuable framework for structuring wildlife tourism experiences to align with flagship related conservation outcomes, and exploring a wider assemblage of species as potential flagships.

Keywords: wildlife tourism, conservation caring, conservation awareness, structural equation modelling

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Authors: Kuliya Muhammed

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This paper examines the potentials of online learning and the challenges to its adoption in Nigeria’s higher institutions of learning. The research would assist in tackling the challenges of online learning adoption and enlighten institutions on the numerous benefits of online learning in Nigeria. The researcher used survey method for the study and questionnaires were used to obtain the needed data from 230 respondents cut across 20 higher institutions in the country. The findings revealed that online learning has the prospect to boost access to learning tools, assist students’ to learn from the comfort of their offices or homes, reduce the cost of learning, and enable individuals to gain self-knowledge. The major challenges in the adoption of e-learning are poor Information and Communication Technology infrastructures, poor internet connectivity where available, lack of Information and Communication Technology background, problem of power supply, lack of commitment by institutions, poor maintenance of Information and Communication Technology tools, inadequate facilities, lack of government funding and fraud. Recommendations were also made at the end of the research work.

Keywords: electronic, ICT, institution, internet, learning, technology

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Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

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To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

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Authors: Maroonisha Maharajh

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Based on the Black Swan and Disruptive Innovation Theories, this study proposes an educational game based learning model within the context of the traditional classroom learning environment. In the proposed model, the perceived e-learning component is decomposed into accessibility, perceived quality and perceived usability within the traditional rural classroom environment. A sample of 92 respondents took part in this study. The results suggest that users’ continuance intention is determined by both economic and grassroots internet accessibility, which in turn is jointly determined by perceived usefulness, information quality, service quality, system quality, perceived ease of use and cognitive absorption of learning.

Keywords: blended learning, flipped classroom, e-learning, gaming

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Authors: Randa El Bedawy

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Exchanging best practices in the scope of entrepreneurship education and the use of experiential learning approaches are growing lately at a very fast pace. Educators should be challenged to promote such a learning approach to bridge the gap between entrepreneurship students and the actual business work environment. The study aims to share best practices, experiences, and knowledge to support entrepreneurship education. The study is exploratory qualitative research based on a case study approach to demonstrate how experiential learning can be used for supporting learning effectiveness in entrepreneurship education through demonstrating a set of fourteen tasks that were used to engage practically the students who were studying a course of entrepreneurship at the American University in Cairo. The study sheds the light on the rational process of using experiential learning to endorse entrepreneurship education through the illustration of each task along with its learning outcomes. The study explores the benefits and obstacles that educators may face when implementing such an experiential approach. The results of the study confirm that developing an experiential learning approach based on constructing a set of well designed practical tasks that complement the overall intended learning outcomes has proven very effective for promoting the students’ learning of entrepreneurship education. However, good preparation for both educators and students is needed primarily to ensure the effective implementation of such an experiential learning approach.

Keywords: business education, entrepreneurship, entrepreneurship education, experiential learning

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Authors: Joshua Osondu

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This research explores how Artificial Intelligence (AI) can be utilized as a policy response to address teaching and learning (TL) issues in education in Ghana. The dual (AI and human) instructor model is used as a theoretical framework to examine how AI can be employed to improve teaching and learning processes and to equip learners with the necessary skills in the emerging AI society. A qualitative research design was employed to assess the impact of AI on various TL issues, such as teacher workloads, a lack of qualified educators, low academic performance, unequal access to education and educational resources, a lack of participation in learning, and poor access and participation based on gender, place of origin, and disability. The study concludes that AI can be an effective policy response to TL issues in Ghana, as it has the potential to increase students’ participation in learning, increase access to quality education, reduce teacher workloads, and provide more personalized instruction. The findings of this study are significant for filling in the gaps in AI research in Ghana and other developing countries and for motivating the government and educational institutions to implement AI in TL, as this would ensure quality, access, and participation in education and help Ghana industrialize.

Keywords: artificial intelligence, teacher, learner, students, policy response

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Sa-Kil Kim, Jang-Soo Lee

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On March 31, 1993, a severe fire accident took place in a nuclear power plant located in Narora in North India. The event involved a major fire in the turbine building of NAPS unit-1 and resulted in a total loss of power to the unit for 17 hours. In addition, there was a heavy ingress of smoke in the control room, mainly through the intake of the ventilation system, forcing the operators to vacate the control room. The Narora fire accident provides us lessons indicating that operators could lose their mind and predictable behaviors during a fire. After the Fukushima accident, which resulted from a natural disaster, unanticipated external events are also required to be prepared and controlled for the ultimate safety of nuclear power plants. From last year, our research team has developed a test and evaluation facility that can simulate external events such as an earthquake and fire based on the operators’ real-sense. As one of the results of the project, we proposed a unit real-sense-based facility that can simulate fire events in a control room for utilizing a test-bed of human factor validation. The test-bed has the operator’s workstation shape and functions to simulate fire conditions such as smoke, heat, and auditory alarms in accordance with the prepared fire scenarios. Furthermore, the test-bed can be used for the operators’ training and experience.

Keywords: human behavior in fire, human factors validation, nuclear power plants, real-sense-based fire simulation

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Authors: Jeonghwan Jeon

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Recently, the industry and academia have been planning development through industry/university cooperation (IUC), and the government has been promoting alternative methods to achieve successful IUC. Representatively, business cultivation involves the lead university (regarding IUC), research and development (R&D), company support, professional manpower cultivation, and marketing, etc., and the scale of support expands every year. Research is performed by many academic researchers to achieve IUC and although satisfaction of their results is high, expectations are not being met and study of the main factor is insufficient. Therefore, this research improves on theirs by analysing the main factors influencing their satisfaction. Each factor is analysed by AHP, and portfolio analysis is performed on the importance and current satisfaction level. This will help improve satisfaction of business participants and ensure effective IUC in the future.

Keywords: industry/university cooperation, satisfaction, portfolio analysis, research and development

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Rady Farag Aziz Ibrahim

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The gap between Islamic terrorism and human rights has become an important issue in the fight against Islamic terrorism worldwide. This situation is repeated because terrorism and human rights are interconnected in such a way that when the former begins, the latter becomes subject to violence. This unknown relationship was recognized in the Vienna Declaration and Program of Action adopted at the International Conference on Human Rights held in Vienna on 25 June 1993, confirming that terrorist acts, in all their forms and manifestations, aim to destroy the rights of individuals. humanity to destroy. Therefore, Islamic terrorism is a violation of basic human rights. For this purpose, the first part of the article will focus on the relationship between terrorism and human rights and the synergy between these two concepts. The second part then explores the emerging concept of cyber threats and how they exist. Additionally, technology analysis will be conducted against threats based on human rights. This will be achieved through analysis of the concept of 'securitization' of human rights and by striking a balance between counter-terrorism measures and the protection of human rights at all costs. This article concludes with recommendations on how to balance terrorism and human rights today.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development

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Authors: Lucia Silveira Alda

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This research aims to analyze critically a set of studies published in the Proceedings of the International Conference on Mobile Learning of IADIS, from 2008 until 2012, which addresses the issue of foreign language learning mediated by mobile phones. The theoretical review of this study is based on the Vygotskian assumptions about tools and mediated learning and the concepts of mobile learning, CALL and MALL. In addition, the diffusion rates of the mobile phone and especially its potential are considered. Through systematic review and meta-analysis, this research intended to identify similarities and differences between the identified characteristics in the studies on the subject of language learning and mobile phone. From the analysis of the results, this study verifies that the mobile phone stands out for its mobility and portability. Furthermore, this device presented positive aspects towards student motivation in language learning. The studies were favorable to mobile phone use for learning. It was also found that the challenges in using this tool are not technical, but didactic and methodological, including the need to reflect on practical proposals. The findings of this study may direct further research in the area of language learning mediated by mobile phones.

Keywords: language learning, mobile learning, mobile phones, technology

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Authors: Aline Woine, Moïra Mikolajczak, Virginie Dardier, Isabelle Roskam

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Background information: Becoming a parent is said to be the happiest event one can ever experience in one’s life. This popular (and almost absolute) truth–which no reasonable and decent human being would ever dare question on pain of being singled out as a bad parent–contrasts with the nuances that reality offers. Indeed, while many parents do thrive in their parenting role, some others falter and become progressively overwhelmed by their parenting role, ineluctably caught in a spiral of exhaustion. Parental burnout (henceforth PB) sets in when parental demands (stressors) exceed parental resources. While it is now generally acknowledged that PB affects the parent’s behavior in terms of neglect and violence toward their offspring, little is known about the impact that the syndrome might have on the children’s internalized (anxious and depressive symptoms, somatic complaints, etc.) and/or externalized (irritability, violence, aggressiveness, conduct disorder, oppositional disorder, etc.) behaviors. Furthermore, at the time of writing, to our best knowledge, no research has yet tested the reverse effect, namely, that of the child's internalized and/or externalized behaviors on the onset and/or maintenance of parental burnout symptoms. Goals and hypotheses: The present pioneering research proposes to fill an important gap in the existing literature related to PB by investigating the bidirectional effect between PB and the child’s internalized and/or externalized behaviors. Relying on a cross-lagged longitudinal study with three waves of data collection (4 months apart), our study tests a transactional model with bidirectional and recursive relations between observed variables and at the three waves, as well as autoregressive paths and cross-sectional correlations. Methods: As we write this, wave-two data are being collected via Qualtrics, and we expect a final sample of about 600 participants composed of French-speaking (snowball sample) and English-speaking (Prolific sample) parents. Structural equation modeling is employed using Stata version 17. In order to retain as much statistical power as possible, we use all available data and therefore apply the maximum likelihood with a missing value (mlmv) as the method of estimation to compute the parameter estimates. To limit (in so far is possible) the shared method variance bias in the evaluation of the child’s behavior, the study relies on a multi-informant evaluation approach. Expected results: We expect our three-wave longitudinal study to show that PB symptoms (measured at T1) raise the occurrence/intensity of the child’s externalized and/or internalized behaviors (measured at T2 and T3). We further expect the child’s occurrence/intensity of externalized and/or internalized behaviors (measured at T1) to augment the risk for PB (measured at T2 and T3). Conclusion: Should our hypotheses be confirmed, our results will make an important contribution to the understanding of both PB and children’s behavioral issues, thereby opening interesting theoretical and clinical avenues.

Keywords: exhaustion, structural equation modeling, cross-lagged longitudinal study, violence and neglect, child-parent relationship

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Authors: Sresha Yadav, Ishwar Kumar

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Second language learning is an important area of research in the language and linguistic domains. Literature suggests that several factors impact second language learning, including age, motivation, objectives, teacher, instructional material, classroom interaction, intelligence and previous background, previous linguistic experience, other student characteristics. Previous researchers have also highlighted that classroom atmospherics has a significant impact on learning as well as on the performance of students. However, the impact of classroom atmospherics on second language learning is still not known in the existing literature. Therefore, the purpose of the present study is to explore whether classroom atmospherics has an impact on second language learning or not? And if it does, it would be worthwhile to explore the nature of such relationship. The present study aims to explore the impact of classroom atmospherics on second language learning by dwelling into the existing literature to explore factors which impact second language learning, classroom atmospherics which impact language learning and the metrics through which such learning impacts could be measured. Based on the findings of literature review, the researchers have adopted a clustering approach for categorization and positioning of various measures of second language learning. Based on the clustering approach, the researchers have approach for measuring the impact of classroom atmospherics on second language learning by drawing a student sample consisting of 80 respondents. The results of the study uncover various basic premises of second language learning, especially with regard to classroom atmospherics. The present study is important not only from the point of view of language learning but implications could be drawn with regard to the design of classroom atmospherics, environmental psychology, anthropometrics, etc as well.

Keywords: classroom atmospherics, cluster analysis, linguistics, second language learning

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Authors: Tanya Beran, Michelle Drefs, Ghazwan Altabbaa, Nouf Al Harbi, Noof Al Baz, Elizabeth Oddone Paolucci

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Although research shows that interprofessional practice has desirable effects on patient care, its implementation can present challenges to its team members. In particular, they may feel pressured to agree with or conform to other members who share information that is contrary to their own understanding. Obtaining evidence of this phenomenon is challenging, as team members may underreport their conformity behaviors due to reasons such as social desirability. In this paper, a series of studies are reviewed in which several approaches to assessing conformity in the health care professions are tested. Simulations, questionnaires, and behavior checklists were developed to measure conformity behaviors. Insights from these studies show that a significant proportion of people conform either in the presence or absence of others, express a variety of verbal and nonverbal behaviors when considering whether to conform to others, may shift between conforming and moments later not conforming (and vice versa), and may not accurately report whether they conformed. A new method of measuring conformity using the implicit bias test is also discussed. People at all levels in the healthcare system are encouraged to develop both formal and informal.

Keywords: conformity, decision-making, inter-professional teams, simulation

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo, Linhang Zhu

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This study proposed a 3D human body reconstruction method, which integrates multi-view joint information into a set of joints and processes it with a parametric human body template. Firstly, we obtained human body image information captured from multiple perspectives. The multi-view information can avoid self-occlusion and occlusion problems during the reconstruction process. Then, we used the MvP algorithm to integrate multi-view joint information into a set of joints. Next, we used the parametric human body template SMPL-X to obtain more accurate three-dimensional human body reconstruction results. Compared with the traditional single-view parametric human body template reconstruction, this method significantly improved the accuracy and stability of the reconstruction.

Keywords: parametric human body templates, reconstruction of the human body, multi-view, joint

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Authors: Aungkana Kmonpetch

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Protection of trafficked victims and partnership among stakeholders are established as core principles in 5P’ strategies in international and national anti-human trafficking policies. In this article, it is of interest to discuss how the role of public-private partnerships in promoting the occupation development for employment in wage will enhance the better protection for victims of trafficking who affirmatively decide they want a criminal justice intervention, using Thailand as a case. Most of the victims who have accepted to be witness in the criminal justice system have lost income during their absence from work. The analysis of Thailand case is based on two methodological approaches: 1) interview with victims of trafficking, protection authorities, service providers, trainers and teachers, social workers, NGOs, police, prosecutors, business owners and enterprises, ILO, UNDP etc.; 2) create collaborative effort through workshops/consultation meetings in participation of all stakeholders – governmental agencies, private organizations, UN and international agencies. The linking of protection and partnership is anchored in international conventions and human trafficking directives. While this is actually framed as a responsive advantage for 5P strategies of anti-human trafficking – prevention, protection, persecution, punishment, and partnership, in reality, there might have more practical requirements of care and support. The article addresses how the partnership between governmental agencies and private organizations provide opportunities for trafficked victims to engage in high-skilled occupational development such as Silk-Sewing and Tailoring. The discussion is also focused how this approach of capacity building of the trainer for trainee, be enable the trafficked victims to cultivate the practices of high-skilled training to engage them into the business of social enterprise with employment in wage. The partnership coordination draws specifically to two aspects: firstly, to formulate appropriate assistance for promotion and protection of human rights of the trafficked victims in response to the 5P’ strategies of anti-human trafficking policy; secondly, to empower them to settle some economic stability for livelihood opportunity in the country of origin on their return and reintegration. Therefore, they can define how they want to move forward to prevent them at risk of vulnerable situations where they might being trafficked again or going on to work in exploitative conditions. It strengthens proper access to protection and assistance, depending on how the incentive of protection for cooperation is perceived to be and how useful the capacity building in occupation development for employment in wage will be implemented practically both in the host country and in the country of origin. This also brings into question how the victim of trafficking are able to access to the trade of market and are supported the employment opportunity according to the concept of decent work as they are constituted as witnesses. We discuss these issues in the area of a broader literature on social protection, economic security, gender, law, and victimhood.

Keywords: employment opportunity, occupation development, protection for victim of trafficking, public-private partnership

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Authors: Reinzo Vittorio B. Cardenas, Heather Venice L. Abogado, Andrea Therese V. Afable, Rhea D. Avillanoza, Marie Abegail P. Ayagan, Catherine D. Bantayan

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As the Internet provides fast and reliable health-related information, the tendency to self-diagnose increases to further understand medical jargon in a diagnosis with a physician and decreases costly consultation fees. The study aimed to explore and understand the factors affecting online health-seeking behaviors in middle-income class adults in Metro Manila. The study was conducted from March to April of 2021 with a sample size of 200 individuals aged 20 to 49 years old. The study was delivered via an online survey that used a questionnaire adapted from the research of Lee et al. (2015). Specifically, the survey consisted of three sections: assessing web-based health-seeking behaviors, consultation with health professionals, and participants' hesitancy to consult with physicians, which used a mix of a 5-point Likert-type scale with multiple responses and multiple-choice options. The results showed that the age and educational attainment of the respondents had a negative effect while presenting a positive effect of socio-economic status on health-seeking behavior. Lastly, there was a significant effect of participant’s hesitancy for professional consultation on their health-seeking behavior. The results gleaned from the study indicated that various individual and socio-economic factors might significantly affect one’s health-seeking behaviors. Although hesitancy had a significant effect on the spectrum of health-seeking behaviors, this does not imply that certain factors are specifically related to an individual’s tendency to seek health information. This information instead becomes essential in understanding the patient-physician relationship and giving patients a more holistic treatment.

Keywords: health-seeking behavior, health information, Internet, physician consultation

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Authors: Stepanov Ivan, Musalimov Viktor, Monahov Uriy

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This report examines the current state of human gait simulator development based on the human hip joint model. This unit will create a database of human gait types, useful for setting up and calibrating mechano devices, as well as the creation of new systems of rehabilitation, exoskeletons and walking robots. The system has ample opportunity to configure the dimensions and stiffness, while maintaining relative simplicity.

Keywords: hip joint, human gait, physiotherapy, simulation

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: learning style, VARK, sensory preferences, identification model, didactic practices

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Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Anila Syed, Manzoor Ahmad

Abstract:

The relationship between United States and India has transformed from estrangement to wider engagement since 2004. With the convergence of interests and shared values both the US and India came close towards each other and evolved strategic partnership through civil nuclear cooperation. This paper analyze the cost and benefit of strategic partnership with India for US, the impact of India’s emergence as regional power on South Asian balance of power and its impact on Pak-US relationship. It also focuses on security structure of the region and challenges for the US to maintain strategic partnership with two rival states (India and Pakistan). The work also gives some recommendations for balancing power in the region in order to ensure durable peace not only between India and Pakistan but also in south Asia.

Keywords: US-India strategic partnership, civil-nuclear cooperation, balance of power, impacts on Pak-US relationship

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Authors: Erin Micali, Katerina Tolstikova, Cheryl Maykel, Elizabeth Harwood

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Female ASD is seldomly studied separately from males. Further, females with ASD are disproportionately underrepresented in the research at a rate of 3:1 (male to female). As such, much of the current understanding about female rigid repetitive behaviors (RRBs) stems from research’s understanding of male RRBs. This can be detrimental to understanding female ASD because this understanding of female RRBs largely discounts female camouflaging and the possibility that females present their autistic symptoms differently. Current literature suggests that females with ASD engage in fewer RRBs than males with ASD and when females do engage in RRBs, they are likely to engage in more subtle, less overt obsessions and repetitive behaviors than males. Method: The current study utilized a mixed methods research design to identify the type and frequency of RRBs that females with ASD engaged in by using a cross-sectional design. The researcher recruited only females to be part of the present study with the criteria they be at least age six and not have co-occurring cognitive impairment. Results: The researcher collected previous testing data (Autism Diagnostic Interview-Revised (ADI-R), Child or Adolescent/Adult Sensory Profile-2, Autism/ Empathy Quotient, Yale Brown Obsessive Compulsive Checklist, Rigid Repetitive Behavior Checklist (evaluator created list), and demographic questionnaire) from 25 total participants. The participants ages ranged from six to 52. The participants were 96% Caucasion and 4% Latin American. Qualitative analysis found the current participant pool engaged in six RRB themes including repetitive behaviors, socially restrictive behaviors, repetitive speech, difficulty with transition, obsessive behaviors, and restricted interests. The current dataset engaged in socially restrictive behaviors and restrictive interests most frequently. Within the main themes 40 subthemes were isolated, defined, and analyzed. Further, preliminary quantitative analysis was run to determine if age impacted camouflaging behaviors and overall presentation of RRBs. Within this dataset this was not founded. Further qualitative data will be run to determine if this dataset engaged in more overt or subtle RRBs to confirm or rebuff previous research. The researcher intends to run SPSS analysis to determine if there was statistical difference between each RRB theme and overall presentation. Secondly, each participant will be analyzed for presentation of RRB, age, and previous diagnoses. Conclusion: The present study aimed to assist in diagnostic clarity. This was achieved by collecting data from a female only participant pool across the lifespan. Current data aided in clarity of the type of RRBs engage in. A limited sample size was a barrier in this study.

Keywords: autism spectrum disorder, camouflaging, rigid repetitive behaviors, gender disparity

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Authors: Yingjin Cui, Xue Bai, Serena Reese

Abstract:

Student engagement and student interest during class instruction are important conditions for active learning. Engagement, which has an important relationship with learning motivation, influences students' levels of persistence in overcoming challenges. Lack of student engagement and absence from face-to-face lectures and tutorials, in turn, can lead to poor academic performance. However, keeping students motivated and engaged in the learning process in different instructional modes poses a significant challenge; students can easily become discouraged from attending lectures and tutorials across both online and face-to-face settings. Many factors impact students’ engagement in the learning process. If you want to keep students focused on learning, you have to invite them into the process of helping themselves by providing an active learning environment. Active learning is an excellent technique for enhancing student engagement and participation in the learning process because it provides means to motivate the student to engage themselves in the learning process through reflection, analyzing, applying, and synthesizing the material they learn during class. In this study, we discussed how to create an active learning class (both face-to-face and synchronous online) through engagement activities, including reflection, collaboration, screen messages, open poll, tournament, and transferring editing roles. These activities will provide an uncommon interactive learning environment that can result in improved learning outcomes. To evaluate the effectiveness of those engagement activities in the learning process, an experimental group and a control group will be explored in the study.

Keywords: active learning, academic performance, engagement activities, learning motivation

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Authors: Abiodun Ezekiel Adesina, Ijeoma Ginikanwa Akubugwo

Abstract:

Information and Communication Technology, ICT can heighten pre-service teachers’ attitudes toward learning and metacognitive learning; however, there is a dearth of literature on the perception of the pre-service teachers on heightening their attitude toward learning and metacognitive learning. Thus, this study investigates the perception of pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT. Two research questions and four hypotheses guided the research. A mixed methods research was adopted for the study in concurrent triangulation type of integrating qualitative and quantitative approaches to the study. The cluster random sampling technique was adopted to select 250 pre-service science teachers in Oyo township. Two self-constructed instruments: Heightening Pre-service Science Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology Scale (HPALMIS, r=.73), and an unstructured interview were used for data collection. Thematic analysis, frequency counts and percentages, t-tests, and analysis of variance were used for data analysis. The perception level of the pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT is above average, with the majority perceiving that ICT can enhance their thinking about their learning. The perception was significant (mean=92.68, SD=10.86, df=249, t=134.91, p<.05). The perception was significantly differentiated by gender (t=2.10, df= 248, p<.05) in favour of the female pre-service teachers and based on the first time of ICTs use (F(5,244)= 9.586, p<.05). Lecturers of science and science related courses should therefore imbibe the use of ICTs in heightening pre-service teachers’ attitude towards learning and metacognitive learning. Government should organize workshops, seminars, lectures, and symposia along with professional bodies for the science education lecturers to keep abreast of the trending ICT.

Keywords: pre-service teachers’ attitude towards learning, metacognitive learning, ICT, pre-service teachers’ perspectives

Procedia PDF Downloads 100