Search results for: English learning strategies

Authors: Se-Hyuk Park, Hee-Jung Seo

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Previous studies have investigated effective coping strategies for excessive stress, positive adaptation, resilience, mental health, and personal growth. However, to the best of the authors' knowledge, little research has been conducted to investigate how Koreans with physical disabilities deal with the COVID-19 pandemic. The purpose of this study was to identify coping strategies and coping resources that Koreans with physical disabilities utilized during the COVID-19 crisis. This study used semi-structured, in-depth interviews with 15 participants. Data were qualitatively analyzed using the constant comparative method with content mapping and content mining questions. We identified three salient themes that were used by participants as coping strategies to deal with various COVID-related challenges: (a) engagement in meaningful activities, (b) improvement of social and emotional support, and (c) experience of resilience. The findings of the present study highlighted that Korean adults with SCI actively engaged in various leisure activities, maintained and developed closer social relationships, and experienced resilience to face COVID-19-related stressors. These coping strategies were noted as a catalyst for physical health as well as psychological well-being of individuals with SCI.

Keywords: spinal cord injury, covid-19 pandemic, coping strategies, coping resources, leisure

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Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

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The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) program, thanks to their in-house technological abilities. This paper tries to study the various knowledge-based incentive programs and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM incentives, knowledge sharing, and learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: knowledge management, knowledge management incentives, knowledge sharing, learning

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Siddhartha Dhungana

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This article primarily explores dimensions in English language teacher's professionalism so that a teacher could reflect and make a strategic professional devotion to implement effective educational programs for the present and the future. The paper substantially incorporates the eastern Hindu practices, especially life values from the Bhagavad Gita, as a basis of teacher’s professional enrichment. Basically, it applies three categorical practices, i.e., Karma Yoga, Jnana Yoga, and Bhakti Yoga, in teachers’ professionality to illustrate, ignite further ahead and sharpen academic journey, professional journey, and professional devotion reflecting common practices. In this journey, a teacher comes to a stage of professional essence as s/he surpasses Karma Yoga, Jnana Yoga, and Bhakti Yoga with their basic quality formation. To illustrate their essence-making process, the three narrative stories for each category mentioned above are analyzed. The data collected from a research participant who has a high level of professional success and who inspires all English Language teachers in Nepal to develop stories for narrative analysis. The narrative analysis is based on eastern themes that are supported by Vygotsky's concept of developmental psychology. Moreover, the structural analysis is based on Gary Barkhuizen's narrative analysis.

Keywords: Karma Yoga, Jnana Yoga, Bhakti Yoga, Vygotsky's concepts, narrative analysis

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Authors: Khomsan Laosillapacharoen

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This research paper was aimed to analyze the current situation of the furniture industry and embark a plan to enhance the export volume of Thai furniture. This is a qualitative research which utilized meta-analysis and focus group. A total of 24 experts in both government and private sectors were interviewed. The findings revealed that Thai furniture had some advantages of access to raw material, high quality of labors, and have a unique skill. However, the threat included a tendency to have more foreign competitors in domestic market. In addition, the strategies to enhance the level of export included increase the standard quality of Thai furniture, offer new and modern designs, use marketing on the internet, use modern technology, and gain tax incentive from the government.

Keywords: export, furniture, strategies, marketing

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Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

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Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Krongthong Khairiree

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The purpose of this research study is to explore mathematics project-based learning approach and the use of technology in the context of school mathematics in Thailand. Data of the study were collected from 6 sample secondary schools and the students were 6-14 years old. Research findings show that through mathematics project-based learning approach and the use of GSP, students were able to make mathematics learning fun and challenging. Based on the students’ interviews they revealed that, with GSP, they were able to visualize and create graphical representations, which will enable them to develop their mathematical thinking skills, concepts and understanding. The students had fun in creating variety of graphs of functions which they can not do by drawing on graph paper. In addition, there are evidences to show the students’ abilities in connecting mathematics to real life outside the classroom and commercial products, such as weaving, patterning of broomstick, and ceramics design.

Keywords: mathematics, project-based learning, Geometer’s Sketchpad (GSP), commercial products

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Authors: Tajinder Pal Singh

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Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: application based learning, conceptual learning, engineering mathematics, word problem

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Authors: Joao Carlos Koch Junior, Risa Takashima

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Learning disabilities have been extensively and increasingly studied in recent times. In spite of this, there is arguably a scarce number of studies addressing a key issue, which is the impact of foreign-language requirements on students with learning disabilities in higher education, and the lack of training or awareness of teachers regarding language learning disabilities. This study is an attempt to address this issue. An extensive review of the literature in multiple fields will be summarised. This, paired with a case-analysis of a university adopting a more inclusive approach towards special-needs students in its foreign-language programme, this presentation aims to establish a link between different studies and propose a number of suggestions to make language classrooms more inclusive.

Keywords: foreign language teaching, higher education, language teacher education, learning disabilities

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Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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Authors: Shan-Ken Chine

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This research aims to a one-year course run of String Music Appreciation, an international online course launched on the British open education platform. It explains how to present music teaching videos with three main features. They are music lesson explanations, instrumental playing demonstrations, and live music performances. The plan of this course is with four major themes and a total of 97 steps. In addition, the paper also uses the testing data provided by the education platform to analyze the performance of learners and to understand the operation of the course. It contains three test data in the statistics dashboard. They are course-run measures, total statistics, and statistics by week. The paper ends with a review of the course's star rating in this one-year run. The result of this course run will be adjusted when it starts again in the future.

Keywords: music online courses, MOOCs, ubiquitous learning, string music, general music education

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

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The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: Jacinta Ifeoma Obidile

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The study sought to ascertain from the opinions of the business educators, effective strategies for funding public tertiary institutions in Anambra State Nigeria, for effective functioning and delivery. Funding of tertiary institutions has become so important following the dilapidated state of most of the public tertiary institutions in Nigeria. Tertiary institutions are known for the production of competitive and competent workforce in the nation. Considering the state of public tertiary institutions currently, one wonders if their objectives are achieved. Many scholars have identified funding as one of the major barriers to effective functioning of tertiary institutions. Although federal and state governments have been supporting the tertiary institutions, but their support seems not to be adequate. This study therefore ascertained from the perspective of business educators, other strategies for funding public tertiary institutions in Anambra State Nigeria, for effective functioning and delivery. Survey research design was adopted for the study. A total of 104 business educators from the public tertiary institutions in the State constituted the population. There was no sampling, hence the whole population was used. Structured questionnaire validated by three experts with a reliability coefficient of 0.82 was the instrument for data collection. Data collected were analyzed using mean and standard deviation. Findings from the study revealed that public-private partnership and external aids were among the strategies considered effective for funding public tertiary institutions. It was therefore recommended among others that associations like alumni should be strongly instituted in each of the public tertiary institutions so as to assist in the funding of tertiary institutions for effective functioning and delivery.

Keywords: strategies, funding, tertiary institutions, business educators

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Authors: Aiydh Aljeddani

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Sustainable learning is an emerging concept that aims at enhancing sustainability literacy and competency in educational contexts. Mobile learning is one of the means increasingly used in sustainable development education nowadays. Studies which have explored this issue in the Saudi educational context so far are rare. Therefore, the current study attempted to explore the current situation of the usage of mobile learning in the Saudi elementary and secondary schools as a means of promoting sustainable learning. It also focused on how mobile learning has been implemented in those schools to promote sustainable learning and what factors have contributed to the success/failure of the implementation of mobile learning and possible ways to improve the current practice. An interpretive approach was followed in this study to gain a thorough understanding of the explored issue in the Saudi educational context using the activity theory as a lens to do so. A qualitative case study methodology in which semi-structured interviews, documents analysis and nominal group were used to gather the data for this study. Two hundred and twenty-nine participants representing several main stakeholders in the educational system took part in this study. Those included six general education schools, head teachers, teachers, students’ parents, educational supervisors, one curriculum designer and academic curriculum specialists. Through the lens of activity theory, the results of the study showed that there were contradictions in the current practice between the elements of the activity system and within each of its elements. Furthermore, several sociocultural factors have influenced both the division of labour and the community's members. These have acted as obstacles which have impeded the usage of mobile learning to promote sustainable learning in this context. It was found that shifting from the current practice to sustainable learning via the usage of mobile learning requires appropriate interrelationship between the different elements of the activity system. The study finally offers a number of recommendations to improve on the current practices and suggests areas for further studies.

Keywords: activity theory, mobile learning, sustainability competency, sustainability literacy, sustainable learning

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Authors: J. Chow

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In laboratory settings, this study measured and reported the effects of undergraduate students watching animated videos on learning microeconomics as compared with the effectiveness of reading written texts. The study described an experiment on learning microeconomics in higher education using two different types of learning materials. It reported the effectiveness on microeconomics learning of watching animated videos and reading written texts. Undergraduate students in the university were randomly assigned to either a ‘video group’ or a ‘text group’ in the experiment. Previously-validated multiple-choice questions on fundamental concepts of microeconomics were administered. Both groups showed improvement between the pre-test and post-test. The experience of learning using text and video materials was also assessed. After controlling the student characteristics variables, the analyses showed that both types of materials showed comparable level of perceived learning experience. The effect size and statistical significance of these results supported the hypothesis that animated video is an effective alternative to text materials as a learning tool for students. The findings suggest that such animated videos may support teaching microeconomics in higher education.

Keywords: animated videos for education, laboratory experiment, microeconomics education, undergraduate economics education

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Authors: Paulo Sérgio Ribeiro de Araújo Bogas

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Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

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Authors: Yong Wook Kim

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The purpose of this study is to develop an instruction analysis checklist applicable to inclusive setting based on the Universal Design for Learning Guideline 2.0. To do this, two self-validation reviews, two expert validity reviews, and two usability evaluations were conducted based on the Universal Design for Learning Guideline 2.0. After validation and usability evaluation, a total of 36 items consisting of 4 items for each instruction was developed. In all questions, examples are presented for the purpose of reinforcing concrete. All the items were judged by the 3-point scale. The observation results were provided through a radial chart allowing SWOT analysis of the universal design for learning of teachers. The developed checklist provides a description of the principles and guidelines in the checklist itself as it requires a thorough understanding by the observer of the universal design for learning through prior education. Based on the results of the study, the instruction criteria, the specificity of the criteria, the number of questions, and the method of arrangement were discussed. As a future research, this study proposed the characteristics of application of universal design for learning for each subject, the comparison with the observation results through the self-report teaching tool, and the continual revision and supplementation of the lecture checklist.

Keywords: inclusion, universal design for learning, instruction analysis, instruction checklist

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Authors: Bruno Mazorra Roig

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In the realm of cost-sharing mechanisms, the vulnerability to Sybil strategies, where agents can create fake identities to manipulate outcomes, has not yet been studied. In this paper, we delve into the intricacies of different cost-sharing mechanisms proposed in the literature, highlighting its non-Sybil-resistance nature. Furthermore, we prove that under mild conditions, a Sybil-proof cost-sharing mechanism for public excludable goods is at least (n/2 + 1)−approximate. This finding reveals an exponential increase in the worst-case social cost in environments where agents are restricted from using Sybil strategies. We introduce the concept of Sybil Welfare Invariant mechanisms, where a mechanism maintains its worst-case welfare under Sybil strategies for every set of prior beliefs with full support even when the mechanism is not Sybil-proof. Finally, we prove that the Shapley value mechanism for public excludable goods holds this property and so deduce that the worst-case social cost of this mechanism is the nth harmonic number Hn under the equilibrium of the game with Sybil strategies, matching the worst-case social cost bound for cost-sharing mechanisms. This finding carries important implications for decentralized autonomous organizations (DAOs), indicating that they are capable of funding public excludable goods efficiently, even when the total number of agents is unknown.

Keywords: game theory, mechanism design, cost sharing, false-name proofness

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Catarina Ramos Pereira, Jorge Rodrigues, Natália Oliveira, Jorge Machado, Maria Begoña Criado, Jorge Machado, Henri J. Greten

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Background: Parkinson's disease is a multi-system neurodegenerative disorder characterized by motor and non-motor symptoms. To slow disorder progression, different treatment options are now available, but in most cases, these therapeutic strategies also involve the presence of important side effects. This has led many patients to pursue complementary therapies, such as acupuncture, to alleviate PD symptoms. Therefore, an update on the efficacy of this treatment for patients of PD is of great value. This work presents a systematic review of the efficacy of acupuncture treatments in relieving PD symptoms. Methods: EMBASE, Medline, Pubmed, Science Direct, The Cochrane Library, Cochrane Central Register of Controlled Trials (Central), and Scielo databases were systematically searched from January 2011 through July 2021. Randomized controlled trials (RCTs) published in English with all types of acupuncture treatment were included. The selection and analysis of the articles were conducted by two blinding authors through the Rayyan application. Results: 720 potentially relevant articles were identified; 52 RCTs met our inclusion criteria. After the exclusion of 35, we found 17 eligible. The included RCTs reported positive effects for acupuncture plus conventional treatment compared with conventional treatment alone in the UPDRS score. Conclusions: Additional evidence should be supported by rigorous methodological strategies. Although firm conclusions cannot be drawn, acupuncture treatment, in the framework of an interdisciplinary care team, appears to have positive effects on PD symptoms.

Keywords: systematic review, Parkinson disease, acupuncture, traditional Chinese medicine

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Authors: Oktawia Braniewicz

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The phenomenon of emigration and migration increasingly affects Poland's borders as well. For this reason, it is necessary to examine the level of protection of Human Rights in Polish Centres for Foreigners. The field study covered 11 centers for Foreigners in the provinces Kujawsko-Pomorskie Region, Lubelskie Region, Lodzkie Region, Mazowieckie Region and Podlaskie Region. Photographic documentation of living and social conditions, conversations with center employees and refugees allow to show a comprehensive picture of the situation prevailing in Centres for Foreigners. The object of reflection will be, in particular, the standards resulting from art. 8 and 13 of the Convention for the Protection of Human Rights and Fundamental Freedoms and article 2 of Protocol No. 1 to the Convention for the Protection of Human Rights and Fundamental Freedoms. The degree of realization of the right to education and the right to respect for family and private life will be shown. Issues related to learning the Polish language, access to a professional translator and psychological help will also be approximated. Learning Polish is not obligatory, which causes problems with assimilation and integration with other members of the new community. In centers for foreigners, there are no translators - a translator from an external company is rented if necessary. The waiting time for an interpreter makes the refugees feel anxious, unable to communicate with the employees of the centers (this is a situation in which the refugees do not know either English, Polish or Russian). Psychologist's help is available on designated days of the week. There is no separate specialist in child psychology, which is a serious problem.

Keywords: human rights, Polish centres, foreigners, fundamental freedoms

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Authors: John E. Boberg, Steven J. Bourgeois

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The decline in student engagement and motivation through the middle years is well documented and clearly associated with a decline in mathematics achievement that persists through high school. To combat this trend and, very often, to meet high-stakes accountability standards, a growing number of parents, teachers, and schools have implemented various methods to incentivize learning. However, according to Self-Determination Theory, forms of incentivized learning such as public praise, tangible rewards, or threats of punishment tend to undermine intrinsic motivation and learning. By focusing on external forms of motivation that thwart autonomy in children, adults also potentially threaten relatedness measures such as trust and emotional engagement. Furthermore, these controlling motivational techniques tend to promote shallow forms of cognitive engagement at the expense of more effective deep processing strategies. Therefore, any short-term gains in apparent engagement or test scores are overshadowed by long-term diminished motivation, resulting in inauthentic approaches to learning and lower achievement. The current study focuses on the relationships between student trust, engagement, and motivation during these crucial years as students transition from elementary to middle school. In order to test the effects of controlled motivational techniques on achievement in mathematics, this quantitative study was conducted on a convenience sample of 22 elementary and middle schools from a single public charter school district in the south-central United States. The study employed multi-source data from students (N = 1,054), parents (N = 7,166), and teachers (N = 356), along with student achievement data and contextual campus variables. Cross-sectional questionnaires were used to measure the students’ self-regulated learning, emotional and cognitive engagement, and trust in teachers. Parents responded to a single item on incentivizing the academic performance of their child, and teachers responded to a series of questions about their acceptance of various incentive strategies. Structural equation modeling (SEM) was used to evaluate model fit and analyze the direct and indirect effects of the predictor variables on achievement. Although a student’s trust in teacher positively predicted both emotional and cognitive engagement, none of these three predictors accounted for any variance in achievement in mathematics. The parents’ use of incentives, on the other hand, predicted a student’s perception of his or her controlled motivation, and these two variables had significant negative effects on achievement. While controlled motivation had the greatest effects on achievement, parental incentives demonstrated both direct and indirect effects on achievement through the students’ self-reported controlled motivation. Comparing upper elementary student data with middle-school student data revealed that controlling forms of motivation may be taking their toll on student trust and engagement over time. While parental incentives positively predicted both cognitive and emotional engagement in the younger sub-group, such forms of controlling motivation negatively predicted both trust in teachers and emotional engagement in the middle-school sub-group. These findings support the claims, posited by Self-Determination Theory, about the dangers of incentivizing learning. Short-term gains belie the underlying damage to motivational processes that lead to decreased intrinsic motivation and achievement. Such practices also appear to thwart basic human needs such as relatedness.

Keywords: controlled motivation, student engagement, incentivized learning, mathematics achievement, self-determination theory, student trust

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Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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Authors: S. Umar, B. F. Umar

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This study was conducted at Giron Masa village, located 30 km from Yauri town. The study determines the socio-economic factors influencing the use of coping strategies among farmers and herders during post-conflict situation. Simple random sampling was employed to select one hundred respondents (50 farmers and 50 herders) from the study area. Logistic regression analysis (LR) was used to ascertain the socioeconomic variables that influenced the use of the coping strategies. The results of the study shows that age, income, family size and farming experience were individually significant and thus influenced the use of POCS by farmers. Annual income and production system influenced the use of POCS by herders. Age, farm size and farming experience were found to be individually significant in influencing the use of EOCS among farmers. Specifically, years of occupation experience among the herders increased the use of emotion oriented coping strategies among herders. The use of SSCS among farmers was influenced by educational level; farm size and farming experience, while the variables are not collectively significant in influencing the use of SSCS among the herders. The research recommends a need to adopt the strategy of community coping to cope with stress.

Keywords: farmers, herders, conflict, coping strategies

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

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Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

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Authors: Ali Abbas

Abstract:

This paper presents a descriptive model of organizational misconduct based on observed patterns that occur before and after an ethical collapse. The patterns were classified by categorizing media articles in both "for-profit" and "not-for-profit" organizations. Based on the model parameters, the paper provides a descriptive model of various organizational deflection strategies under numerous scenarios, including situations where ethical complaints build-up, situations under which whistleblowers become more prevalent, situations where large scandals that relate to leadership occur, and strategies by which organizations deflect blame when pressure builds up or when media finds out. The model parameters start with the premise of a tolerance to double standards in unethical acts when conducted by leadership or by members of corporate governance. Following this premise, the model explains how organizations engage in discursive strategies to cover up the potential conflicts that arise, including secret agreements and weakening stakeholders who may oppose the organizational acts. Deflection strategies include "preemptive" and "post-complaint" secret agreements, absence of (or vague) documented procedures, engaging in blame and scapegoating, remaining silent on complaints until the media finds out, as well as being slow (if at all) to acknowledge misconduct and fast to cover it up. The results of this paper may be used to guide organizational leaders into the implications of such shortsighted strategies toward unethical acts, even if they are deemed legal. Validation of the model assumptions through numerous media articles is provided.

Keywords: ethical decision making, prediction, scandals, organizational strategies

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Authors: M. Vassou, A. Karasimos

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A primary concern in the field of Second Language Acquisition (SLA) research is to determine the innate mechanisms of second language learning and acquisition through the systematic study of a learner's interlanguage. Errors emerge while a learner attempts to communicate using the target-language and can be seen either as the observable linguistic product of the latent cognitive and language process of mental representations or as an indispensable learning mechanism. Therefore, the study of the learner’s erroneous forms may depict the various strategies and mechanisms that take place during the language acquisition process resulting in deviations from the target-language norms and difficulties in communication. Mapping the erroneous utterances of a late adult learner in the process of acquiring Greek as a second language constitutes one of the main aims of this study. For our research purposes, we created an error-tagged learner corpus composed of the participant’s written texts produced throughout a period of a 4- year instructed language acquisition. Error analysis and interlanguage theory constitute the methodological and theoretical framework, respectively. The research questions pertain to the learner's most frequent errors per linguistic category and per year as well as his choices concerning the Greek Article System. According to the quantitative analysis of the data, the most frequent errors are observed in the categories of the stress system and syntax, whereas a significant fluctuation and/or gradual reduction throughout the 4 years of instructed acquisition indicate the emergence of developmental stages. The findings with regard to the article usage bespeak fossilization of erroneous structures in certain contexts. In general, our results point towards the existence and further development of an established learner’s (inter-) language system governed not only by mother- tongue and target-language influences but also by the learner’s assumptions and set of rules as the result of a complex cognitive process. It is expected that this study will contribute not only to the knowledge in the field of Greek as a second language and SLA generally, but it will also provide an insight into the cognitive mechanisms and strategies developed by multilingual learners of late adulthood.

Keywords: Greek as a second language, error analysis, interlanguage, late adult learner

Procedia PDF Downloads 115