Search results for: principles of adult learning scale
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15047

Search results for: principles of adult learning scale

14387 A Qualitative Student-Perspective Study of Student-Centered Learning Practices in the Context of Irish Teacher Education

Authors: Pauline Logue

Abstract:

In recent decades, the Irish Department of Education and Skills has pro-actively promoted student-center learning methodologies. Similarly, the National Forum for the Enhancement of Teaching and Learning has advocated such strategies, aligning them with student success. These developments have informed the author’s professional practice as a teacher educator. This qualitative student-perspective study focuses on a review of one pilot initiative in the academic year 2020-2021, namely, the implementation of universal design for learning strategies within teacher education, employing student-centered learning strategies. Findings included: that student-centered strategies enhanced student performance and success overall, with some minor evidence of student resistance. It was concluded that a dialogical review with student teachers on prior learning experiences (from intellectual and affective perspectives) and learning environments (physical, virtual, and emotional) could facilitate greater student ownership of learning. It is recommended to more formally structure such a dialogical review in a future delivery.

Keywords: professional practice, student-centered learning, teacher education, universal design for learning

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14386 Bubble Scrum: How to Run in Organizations That Only Know How to Walk

Authors: Zaheer A. Ali, George Szabo

Abstract:

SCRUM has roots in software and web development and works very well on that in that space. However, any technical person who has watched a typical waterfall managed project spiral out of control or into an abyss, has thought: "there must be a better way". I will discuss how that thought leads naturally to adopting Agile principles and SCRUM, as well as how Agile and SCRUM can be implemented in large institutions with long histories via a method I developed: Bubble Scrum. We will also see how SCRUM can be implemented in interesting places outside of the technical sphere and also discuss where and how to subtly bring Agility and SCRUM into large, rigid, institutions.

Keywords: agile, enterprise-agile, agile at scale, agile transition, project management, scrum

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14385 Development and Psychometric Properties of the Relational Mobility Scale for the Indonesian Population

Authors: Sukaesi Marianti

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This study aims to develop the Relational Mobility Scale for the Indonesian population and to investigate its psychometric properties. New items of the scale were created taking into account the Indonesian population which consists of two parallel forms (A and A’). This study uses 30 newly orchestrated items while keeping in mind the characteristics of the targeted population. The scale was administered to 433 public high school students in Malang, Indonesia. Construct validity of its factor structure was demonstrated using exploratory factor analysis and confirmatory factor analysis. The result exhibits that he model fits the data, and that the delayed alternate form method shows acceptable result. Results yielded that 21 items of the three-dimensional Relational Mobility Scale is suitable for measuring relational mobility in high school students of Indonesian population.

Keywords: confirmatory factor analysis, delayed alternate form, Indonesian population, relational mobility scale

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14384 The Implications of Technological Advancements on the Constitutional Principles of Contract Law

Authors: Laura Çami (Vorpsi), Xhon Skënderi

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In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.

Keywords: technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract

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14383 Ethical Artificial Intelligence: An Exploratory Study of Guidelines

Authors: Ahmad Haidar

Abstract:

The rapid adoption of Artificial Intelligence (AI) technology holds unforeseen risks like privacy violation, unemployment, and algorithmic bias, triggering research institutions, governments, and companies to develop principles of AI ethics. The extensive and diverse literature on AI lacks an analysis of the evolution of principles developed in recent years. There are two fundamental purposes of this paper. The first is to provide insights into how the principles of AI ethics have been changed recently, including concepts like risk management and public participation. In doing so, a NOISE (Needs, Opportunities, Improvements, Strengths, & Exceptions) analysis will be presented. Second, offering a framework for building Ethical AI linked to sustainability. This research adopts an explorative approach, more specifically, an inductive approach to address the theoretical gap. Consequently, this paper tracks the different efforts to have “trustworthy AI” and “ethical AI,” concluding a list of 12 documents released from 2017 to 2022. The analysis of this list unifies the different approaches toward trustworthy AI in two steps. First, splitting the principles into two categories, technical and net benefit, and second, testing the frequency of each principle, providing the different technical principles that may be useful for stakeholders considering the lifecycle of AI, or what is known as sustainable AI. Sustainable AI is the third wave of AI ethics and a movement to drive change throughout the entire lifecycle of AI products (i.e., idea generation, training, re-tuning, implementation, and governance) in the direction of greater ecological integrity and social fairness. In this vein, results suggest transparency, privacy, fairness, safety, autonomy, and accountability as recommended technical principles to include in the lifecycle of AI. Another contribution is to capture the different basis that aid the process of AI for sustainability (e.g., towards sustainable development goals). The results indicate data governance, do no harm, human well-being, and risk management as crucial AI for sustainability principles. This study’s last contribution clarifies how the principles evolved. To illustrate, in 2018, the Montreal declaration mentioned eight principles well-being, autonomy, privacy, solidarity, democratic participation, equity, and diversity. In 2021, notions emerged from the European Commission proposal, including public trust, public participation, scientific integrity, risk assessment, flexibility, benefit and cost, and interagency coordination. The study design will strengthen the validity of previous studies. Yet, we advance knowledge in trustworthy AI by considering recent documents, linking principles with sustainable AI and AI for sustainability, and shedding light on the evolution of guidelines over time.

Keywords: artificial intelligence, AI for sustainability, declarations, framework, regulations, risks, sustainable AI

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14382 The Teacher’s Role in Generating and Maintaining the Motivation of Adult Learners of English: A Mixed Methods Study in Hungarian Corporate Contexts

Authors: Csaba Kalman

Abstract:

In spite of the existence of numerous second language (L2) motivation theories, the teacher’s role in motivating learners has remained an under-researched niche to this day. If we narrow down our focus on the teacher’s role on motivating adult learners of English in an English as a Foreign Language (EFL) context in corporate environments, empirical research is practically non-existent. This study fills the above research niche by exploring the most motivating aspects of the teacher’s personality, behaviour, and teaching practices that affect adult learners’ L2 motivation in corporate contexts in Hungary. The study was conducted in a wide range of industries in 18 organisations that employ over 250 people in Hungary. In order to triangulate the research, 21 human resources managers, 18 language teachers, and 466 adult learners of English were involved in the investigation by participating in interview studies, and quantitative questionnaire studies that measured ten scales related to the teacher’s role, as well as two criterion measure scales of intrinsic and extrinsic motivation. The qualitative data were analysed using a template organising style, while descriptive, inferential statistics, as well as multivariate statistical techniques, such as correlation and regression analyses, were used for analysing the quantitative data. The results showed that certain aspects of the teacher’s personality (thoroughness, enthusiasm, credibility, and flexibility), as well as preparedness, incorporating English for Specific Purposes (ESP) in the syllabus, and focusing on the present, proved to be the most salient aspects of the teacher’s motivating influence. The regression analyses conducted with the criterion measure scales revealed that 22% of the variance in learners’ intrinsic motivation could be explained by the teacher’s preparedness and appearance, and 23% of the variance in learners’ extrinsic motivation could be attributed to the teacher’s personal branding and incorporating ESP in the syllabus. The findings confirm the pivotal role teachers play in motivating L2 learners independent of the context they teach in; and, at the same time, call for further research so that we can better conceptualise the motivating influence of L2 teachers.

Keywords: adult learners, corporate contexts, motivation, teacher’s role

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14381 A Case Study of Meaningful Learning in Play for Young Children

Authors: Baoliang Xu

Abstract:

The future of education should focus on creating meaningful learning for learners. Play is a basic form and an important means of carrying out kindergarten educational activities, which promotes the creation and development of meaningful learning and is of great importance in the harmonious physical and mental development of young children. Through literature research and case studies, this paper finds that: meaningful learning has the characteristics of contextuality, interaction and constructiveness; teachers should pay great attention to the guidance of children's games, fully respect children's autonomy and create a prepared game environment; children's meaningful learning exists in games and hidden in things that interest them, and "the generation of questions The "generation of questions" fuels the depth of children's meaningful learning, and teachers' professional support helps children's meaningful learning to develop continuously. In short, teachers' guidance of young children's play should be emphasized to effectively provide scaffolding instruction to promote meaningful learning in a holistic manner.

Keywords: meaningful learning, young childhood, game, case study

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14380 Challenges in E-Government: Conceptual Views and Solutions

Authors: Rasim Alguliev, Farhad Yusifov

Abstract:

Considering the international experience, conceptual and architectural principles of forming of electron government are researched and some suggestions were made. The assessment of monitoring of forming processes of electron government, intellectual analysis of web-resources, provision of information security, electron democracy problems were researched, conceptual approaches were suggested. By taking into consideration main principles of electron government theory, important research directions were specified.

Keywords: electron government, public administration, information security, web-analytics, social networks, data mining

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14379 Use of a Symptom Scale Based on Degree of Functional Impairment for Acute Concussion

Authors: Matthew T. McCarthy, Sarah Janse, Natalie M. Pizzimenti, Anthony K. Savino, Brian Crosser, Sean C. Rose

Abstract:

Concussion is diagnosed clinically using a comprehensive history and exam, supported by ancillary testing. Frequently, symptom checklists are used as part of the evaluation of concussion. Existing symptom scales are based on a subjective Likert scale, without relation of symptoms to clinical or functional impairment. This is a retrospective review of 133 patients under age 30 seen in an outpatient neurology practice within 30 days of a probable or definite concussion. Each patient completed 2 symptom checklists at the initial visit – the SCAT-3 symptom evaluation (22 symptoms, 0-6 scale) and a scale based on the degree of clinical impairment for each symptom (22 symptoms, 0-3 scale related to functional impact of the symptom). Final clearance date was determined by the treating physician. 60.9% of patients were male with mean age 15.7 years (SD 2.3). Mean time from concussion to first visit was 6.9 days (SD 6.2), and 101 patients had definite concussions (75.9%), while 32 were diagnosed as probable (24.1%). 94 patients had a known clearance date (70.7%) with mean clearance time of 20.6 days (SD 18.6) and median clearance time of 19 days (95% CI 16-21). Mean total symptom score was 27.2 (SD 22.9) on the SCAT-3 and 14.7 (SD 11.9) for the functional impairment scale. Pearson’s correlation between the two scales was 0.98 (p < 0.001). After adjusting for patient and injury characteristics, an equivalent increase in score on each scale was associated with longer time to clearance (SCAT-3 hazard ratio 0.885, 95%CI 0.835-0.938, p < 0.001; functional impairment scale hazard ratio 0.851, 95%CI 0.802-0.902, p < 0.001). A concussion symptom scale based on degree of functional impairment correlates strongly with the SCAT-3 scale and demonstrates a similar association with time to clearance. By assessing the degree of impact on clinical functioning, this symptom scale reflects a more intuitive approach to rating symptoms and can be used in the management of concussion.

Keywords: checklist, concussion, neurology, scale, sports, symptoms

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14378 Disparity of Learning Styles and Cognitive Abilities in Vocational Education

Authors: Mimi Mohaffyza Mohamad, Yee Mei Heong, Nurfirdawati Muhammad Hanafi, Tee Tze Kiong

Abstract:

This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education. Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. The study discovered that students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.

Keywords: learning styles, cognitive abilities, dimension of learning styles, learning preferences

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14377 Systems and Procedures in Indonesian Administrative Law

Authors: Andhika Danesjvara

Abstract:

Governance of the Republic of Indonesia should be based on the principle of sovereignty and the rule of law. Based on these principles, all forms of decisions and/or actions of government administration should be based on the sovereignty of the people and the law. Decisions and/or actions for citizens should be based on the provisions of the legislation and the general principles of good governance. Control of the decisions and/or actions is a part of administrative review and also judicial control. The control is part of the administrative justice system, which is intended for people affected by the decisions or administrative actions. This control is the duty and authority of the government or independent administrative court. Therefore, systems and procedures for the implementation of the task of governance and development must be regulated by law. Systems and procedures of governance is a subject studied in administrative law, therefore, the research also includes a review of the principles of law in administrative law. The administrative law procedure is important for the government to make decisions, the question is whether the procedures are part of the justice system itself.

Keywords: administrative court, administrative justice, administrative law, administrative procedures

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14376 E–Learning System in Virtual Learning Environment to Develop Problem Solving Ability and Team Learning for Learners in Higher Education

Authors: Noawanit Songkram

Abstract:

This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.

Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment

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14375 The Effect of Four Local Plant Extract on the Control of Rice Weevil, Sitophilus oryzae L.

Authors: Banaz Sdiq Abdulla

Abstract:

Four local species (Allium sativum, Capsicum annum, Anethum graveolens, and Ocimum basilicum) were evaluated in the laboratory of Biolog Department, College of Education, for their ability to protect stored rice from the infection by weevil Sitophilus oryzae. Aqueous extracts of the plant species were applied as direct admixture of three concentrations levels of 1%, 2.5%, and 5% (W/V) to assess for mortality, adult emergence, and repellency and weight losses. The results showed that Al. sativum extracts was the most effective as it gave the highest mortality (90%)at 5% concentration followed by Capsicum annum (80%) on the 4th day post treatment, the result showed that the plant extract of different concentrations exhibited different level of reduction in adult emergence and different repellency of adults of Sitophilus oryzae. Allium sativum recorded the lowest mean number of adult emergence (8) followed by Capsicum annum (10) at 5% concentration, while Capsicum annum was found to be revealed complete repellent agent (100%) repellency on the 6th hours against Sitophilus oryzae followed by Allium sativum and Anethum graveolens (81.8%). There was a significant (P>0.05) reduction in the weight lossed by the weevils with less damaged recorded on grain treated with Allium sativum and Capsicum annum (1.6%) and (2.3%) respectively.

Keywords: plant extraction, rice, protectant, pest

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14374 E-Learning Approaches Based on Artificial Intelligence Techniques: A Survey

Authors: Nabila Daly, Hamdi Ellouzi, Hela Ltifi

Abstract:

In last year’s, several recent researches’ that focus on e-learning approaches having as goal to improve pedagogy and student’s academy level assessment. E-learning-related works have become an important research file nowadays due to several problems that make it impossible for students join classrooms, especially in last year’s. Among those problems, we note the current epidemic problems in the word case of Covid-19. For those reasons, several e-learning-related works based on Artificial Intelligence techniques are proposed to improve distant education targets. In the current paper, we will present a short survey of the most relevant e-learning based on Artificial Intelligence techniques giving birth to newly developed e-learning tools that rely on new technologies.

Keywords: artificial intelligence techniques, decision, e-learning, support system, survey

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14373 Machine Learning Analysis of Eating Disorders Risk, Physical Activity and Psychological Factors in Adolescents: A Community Sample Study

Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

Abstract:

Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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14372 The Link Between Knowledge Management, Organizational Learning and Collective Competence

Authors: Amira Khelil, Habib Affes

Abstract:

The XXIst century is characterized by promoting teamwork as one of the main drivers of firms` performance. Collective competence is becoming crucial in developing and maintaining a firm’s competitive advantage, as well as its contributions to organizational innovation. In other words, the improvement of collective competence for a firm is no longer a choice, but rather an obligation. Learning capabilities of a firm in the context of knowledge management are assumed to be the main drivers of collective competence. Although there are some efforts to consider these concepts together; they are mostly discussed separately in the management theory. Thus, this paper aims to offer a holistic approach for development collective competence on the basis of Knowledge Management and Organizational Learning Capabilities. A theoretical model that defines a relationship between knowledge management, organizational learning and collective competence is presented at the end of this paper.

Keywords: collective competence, exploitation learning, exploration learning, knowledge management, organizational learning capabilities

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14371 Strategies for Enhancing Academic Honesty as an Ethical Concern in Electronic Learning (E-learning) among University Students: A Philosophical Perspective

Authors: Ekeh Greg

Abstract:

Learning has been part of human existence from time immemorial. The aim of every learning is to know the truth. In education, it is desirable that true knowledge is imparted and imbibed. For this to be achieved, there is need for honesty, in this context, academic honesty among students, especially in e-learning. This is an ethical issue since honesty bothers on human conduct. However, research findings have shown that academic honesty has remained a big challenge to online learners, especially among the university students. This is worrisome since the university education is the final education system and a gateway to life in the wider society after schooling. If they are practicing honesty in their academic life, it is likely that they will practice honesty in the in the society, thereby bringing positive contributions to the society wherever they find themselves. With this in mind, the significance of this study becomes obvious. On grounds of this significance, this paper focuses on strategies that are adjudged certain to enhance the practice of honesty in e-learning so as to enable learners to be well equipped to contribute to the society through honest ways. The aim of the paper is to contribute to the efforts of instilling the consciousness and practice of honesty in the minds and hearts of learners. This will, in turn, promote effective teaching and learning, academic high standard, competence and self-confidence in university education. Philosophical methods of conceptual analysis, clarification, description and prescription are adopted for the study. Philosophical perspective is chosen so as to ground the paper on the basis of rationality rather than emotional sentiments and biases emanating from cultural, religious and ethnic differences and orientations. Such sentiments and biases can becloud objective reasoning and sound judgment. A review of related literature is also carried out. The findings show that academic honesty in e-learning is a cherished value, but it is bedeviled by some challenges, such as care-free attitude on the part of students and absence of monitoring. The findings also show that despite the challenges facing academic honesty, strategies such as self-discipline, determination, hard work, imbibing ethical and philosophical principles, among others, can certainly enhance the practice of honesty in e-learning among university students. The paper, therefore, concludes that these constitute strategies for enhancing academic honesty among students. Consequently, it is suggested that instructors, school counsellors and other stakeholders should endeavour to see that students are helped to imbibe these strategies and put them into practice. Students themselves are enjoined to cherish honesty in their academic pursuit and avoid short-cuts. Short-cuts can only lead to mediocrity and incompetence on the part of the learners, which may have long adverse consequences, both on themselves and others.

Keywords: academic, ethical, philosophical, strategies

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14370 A Preliminary Conceptual Scale to Discretize the Distributed Manufacturing Continuum

Authors: Ijaz Ul Haq, Fiorenzo Franceschini

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The distributed manufacturing methodology brings a new concept of decentralized manufacturing operations close to the proximity of end users. A preliminary scale, to measure distributed capacity and evaluate positioning of firms, is developed in this research. In the first part of the paper, a literature review has been performed which highlights the explorative nature of the studies conducted to present definitions and classifications due to novelty of this topic. From literature, five dimensions of distributed manufacturing development stages have been identified: localization, manufacturing technologies, customization and personalization, digitalization and democratization of design. Based on these determinants a conceptual scale is proposed to measure the status of distributed manufacturing of a generic firm. A multiple case study is then conducted in two steps to test the conceptual scale and to identify the corresponding level of distributed potential in each case study firm.

Keywords: distributed manufacturing, distributed capacity, localized production, ordinal scale

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14369 PYTHEIA: A Scale for Assessing Rehabilitation and Assistive Robotics

Authors: Yiannis Koumpouros, Effie Papageorgiou, Alexandra Karavasili, Foteini Koureta

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The objective of the present study was to develop a scale called PYTHEIA. The PYTHEIA is a self-reported measure for the assessment of rehabilitation and assistive robotics and other assistive technology devices. The development of PYTHEIA faced the absence of a valid instrument that can be used to evaluate the assistive robotic devices both as a whole, as well as any of their individual components or functionalities implemented. According to the results presented, PYTHEIA is a valid and reliable scale able to be applied to different target groups for the subjective evaluation of various assistive technology devices.

Keywords: rehabilitation, assistive technology, assistive robots, rehabilitation robots, scale, psychometric test, assessment, validation, user satisfaction

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14368 Impact of Organic Architecture in Building Design

Authors: Zainab Yahaya Suleiman

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Physical fitness, as one of the most important keys to a healthy wellbeing, is the basis of dynamic and creative intellectual activity. As a result, the fitness world is expanding every day. It is believed that a fitness centre is a place of healing and also the natural environment is vital to speedy recovery. The aim of this paper is to propose and designs a suitable location for a fitness centre in Batagarawa metropolis. Batagarawa city is enriched with four tertiary institutions with diverse commerce and culture but lacks the facility of a well-equipped fitness centre. The proposed fitness centre intends to be an organically sound centre that will make use of principles of organic architecture to create a new pleasant environment between man and his environments. Organic architecture is the science of designing a building within pleasant natural resources and features surrounding the environment. It is regarded as visual poetry and reinterpretation of nature’s principles; as well as embodies a settlement of person, place, and materials. Using organic architecture, the design was interlaced with the dynamic, organic and monumental features surrounding the environment. The city has inadequate/no facility that is considered organic where one can keep fit in a friendly, conducive and adequate location. Thus, the need for establishing a fitness centre to cater for this need cannot be over-emphasised. Conclusively, a fitness centre will be an added advantage to this fast growing centre of learning.

Keywords: organic architecture, fitness center, environment, natural resources, natural features, building design

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14367 Current Methods for Drug Property Prediction in the Real World

Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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14366 Ubiquitous Learning Environments in Higher Education: A Scoping Literature Review

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

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Ubiquitous learning and the use of ubiquitous learning environments herald a new era in higher education. Ubiquitous environments fuse together authentic learning situations and digital learning spaces where students can seamlessly immerse themselves into the learning process. Definitions of ubiquitous learning are wide and vary in the previous literature and learning environments are not systemically described. The aim of this scoping review was to identify the criteria and the use of ubiquitous learning environments in higher education contexts. The objective was to provide a clear scope and a wide view for this research area. The original studies were collected from nine electronic databases. Seven publications in total were defined as eligible and included in the final review. An inductive content analysis was used for the data analysis. The reviewed publications described the use of ubiquitous learning environments (ULE) in higher education. Components, contents and outcomes varied between studies, but there were also many similarities. In these studies, the concept of ubiquitousness was defined as context-awareness, embeddedness, content-personalization, location-based, interactivity and flexibility and these were supported by using smart devices, wireless networks and sensing technologies. Contents varied between studies and were customized to specific uses. Measured outcomes in these studies were focused on multiple aspects as learning effectiveness, cost-effectiveness, satisfaction, and usefulness. This study provides a clear scope for ULE used in higher education. It also raises the need for transparent development and publication processes, and for practical implications of ubiquitous learning environments.

Keywords: higher education, learning environment, scoping review, ubiquitous learning, u-learning

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14365 Effect of Hybrid Learning in Higher Education

Authors: A. Meydanlioglu, F. Arikan

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In recent years, thanks to the development of information and communication technologies, the computer and internet have been used widely in higher education. Internet-based education is impacting traditional higher education as online components increasingly become integrated into face-to-face (FTF) courses. The goal of combined internet-based and traditional education is to take full advantage of the benefits of each platform in order to provide an educational opportunity that can promote student learning better than can either platform alone. Research results show that the use of hybrid learning is more effective than online or FTF models in higher education. Due to the potential benefits, an increasing number of institutions are interested in developing hybrid courses, programs, and degrees. Future research should evaluate the effectiveness of hybrid learning. This paper is designed to determine the impact of hybrid learning on higher education.

Keywords: e-learning, higher education, hybrid learning, online education

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14364 Pros and Cons of Distance Learning in Europe and Perspective for the Future

Authors: Aleksandra Ristic

Abstract:

The Coronavirus Disease – 2019 hit Europe in February 2020, and infections took place in four waves. It left consequences and demanded changes for the future. More than half of European countries responded quickly by declaring a state of emergency and introducing various containment measures that have had a major impact on individuals’ lives in recent years. Closing public lives was largely achieved by limited access and/or closing public institutions and services, including the closure of educational institutions. Teaching in classrooms converted to distance learning. In the research, we used a quantitative study to analyze various factors of distance learning that influenced pupils in different segments: teachers’ availability, family support, entire online conference learning, successful distance learning, time for themselves, reliable sources, teachers’ feedback, successful distance learning, online participation classes, motivation and teachers’ communication and theoretical review of the importance of digital skills, e-learning Index, World comparison of e-learning in the past, digital education plans for the field of Europe. We have gathered recommendations and distance learning solutions to improve the learning process by strengthening teachers and creating more tiered strategies for setting and achieving learning goals by the children.

Keywords: availability, digital skills, distance learning, resources

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14363 Learning Environments in the Early Years: A Case Study of an Early Childhood Centre in Australia

Authors: Mingxi Xiao

Abstract:

Children’s experiences in the early years build and shape the brain. The early years learning environment plays a significantly important role in children’s development. A well-constructed environment will facilitate children’s physical and mental well-being. This case study used an early learning centre in Australia called SDN Hurstville as an example, describing the learning environment in the centre, as well as analyzing the functions of the affordances. In addition, this report talks about the sustainability of learning in the centre, and how the environment supports cultural diversity and indigenous learning. The early years for children are significant. Different elements in the early childhood centre should work together to help children develop better. This case study found that the natural environment and the artificial environment are both critical to children; only when they work together can children have better development in physical and mental well-being and have a sense of belonging when playing and learning in the centre.

Keywords: early childhood center, early childhood education, learning environment, Australia

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14362 The Training Demands of Nursing Assistants on Urinary Incontinence in Nursing Homes: A Mixed Methods Study

Authors: Lulu Liao, Huijing Chen, Yinan Zhao, Hongting Ning, Hui Feng

Abstract:

Urinary tract infection rate is an important index of care quality in nursing homes. The aim of the study is to understand the nursing assistant's current knowledge and attitudes of urinary incontinence and to explore related stakeholders' viewpoint about urinary incontinence training. This explanatory sequential study used Knowledge, Practice, and Attitude Model (KAP) and Adult Learning Theories, as the conceptual framework. The researchers collected data from 509 nursing assistants in sixteen nursing homes in Hunan province in China. The questionnaire survey was to assess the knowledge and attitude of urinary incontinence of nursing assistants. On the basis of quantitative research and combined with focus group, training demands were identified, which nurse managers should adopt to improve nursing assistants’ professional practice ability in urinary incontinence. Most nursing assistants held the poor knowledge (14.0 ± 4.18) but had positive attitudes (35.5 ± 3.19) toward urinary incontinence. There was a significant positive correlation between urinary incontinence knowledge and nursing assistants' year of work and educational level, urinary incontinence attitude, and education level (p < 0.001). Despite a general awareness of the importance of prevention of urinary tract infections, not all nurse managers fully valued the training in urinary incontinence compared with daily care training. And the nursing assistants required simple education resources to equip them with skills to address problem about urinary incontinence. The variety of learning methods also highlighted the need for educational materials, and nursing assistants had shown a strong interest in online learning. Related education material should be developed to meet the learning need of nurse assistants and provide suitable training method for planned quality improvement in urinary incontinence.

Keywords: mixed methods, nursing assistants, nursing homes, urinary incontinence

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14361 A Review of Deep Learning Methods in Computer-Aided Detection and Diagnosis Systems based on Whole Mammogram and Ultrasound Scan Classification

Authors: Ian Omung'a

Abstract:

Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

Procedia PDF Downloads 89
14360 Survey of Rate and Causes of Literacy Preservation in Adult Newly Learners

Authors: Mohammad Narimani, Zahra Rostamoghli

Abstract:

The main objective of this study is the survey of rate and causes of literacy preservation in adult newly learners. Statistical sample consists of 384 adults who are newly learners of literacy, at 2002, who were selected by stratified sampling method. This is a correlation cross-sectional survey research, in which authors-constructed measures were used for data collection. Results of survey showed that learners' literacy preservation rate after two years was 70%, 61% and 57%, in reading, dictation and mathematic tests, respectively.Following can be noted as factors correlated with literacy preservation; repetition of subjects and learners' subjective review, access to and using the library and publications, feeling of need to and interest in educated matters, socio cultural class of learners, and literacy level of learners' family.

Keywords: literacy preservation, new learner, literacy improvement movement, mathematic test

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14359 Hate Speech Detection Using Deep Learning and Machine Learning Models

Authors: Nabil Shawkat, Jamil Saquer

Abstract:

Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

Procedia PDF Downloads 129
14358 Intelligent Software Architecture and Automatic Re-Architecting Based on Machine Learning

Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

Abstract:

Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

Procedia PDF Downloads 114