Search results for: learning style scale
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13356

Search results for: learning style scale

11166 Assessing the Competence of Oral Surgery Trainees: A Systematic Review

Authors: Chana Pavneet

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Background: In more recent years in dentistry, a greater emphasis has been placed on competency-based education (CBE) programmes. Undergraduate and postgraduate curriculums have been reformed to reflect these changes, and adopting a CBE approach has shown to be beneficial to trainees and places an emphasis on continuous lifelong learning. The literature is vast; however, very little work has been done specifically to the assessment of competence in dentistry and even less so in oral surgery. The majority of the literature tends to opinion pieces. Some small-scale studies have been undertaken in this area researching assessment tools which can be used to assess competence in oral surgery. However, there is a lack of general consensus on the preferable assessment methods. The aim of this review is to identify the assessment methods available and their usefulness. Methods: Electronic databases (Medline, Embase, and the Cochrane Database of systematic reviews) were searched. PRISMA guidelines were followed to identify relevant papers. Abstracts of studies were reviewed, and if they met the inclusion criteria, they were included in the review. Papers were reviewed against the critical appraisal skills programme (CASP) checklist and medical education research quality instrument (MERQSI) to assess their quality and identify any bias in a systematic manner. The validity and reliability of each assessment method or tool were assessed. Results: A number of assessment methods were identified, including self-assessment, peer assessment, and direct observation of skills by someone senior. Senior assessment tended to be the preferred method, followed by self-assessment and, finally, peer assessment. The level of training was shown to affect the preferred assessment method, with one study finding peer assessment more useful in postgraduate trainees as opposed to undergraduate trainees. Numerous tools for assessment were identified, including a checklist scale and a global rating scale. Both had their strengths and weaknesses, but the evidence was more favourable for global rating scales in terms of reliability, applicability to more clinical situations, and easier to use for examiners. Studies also looked into trainees’ opinions on assessment tools. Logbooks were not found to be significant in measuring the competence of trainees. Conclusion: There is limited literature exploring the methods and tools which assess the competence of oral surgery trainees. Current evidence shows that the most favourable assessment method and tool may differ depending on the stage of training. More research is required in this area to streamline assessment methods and tools.

Keywords: competence, oral surgery, assessment, trainees, education

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11165 Contribution for Rural Development Trough Training in Organic Farming

Authors: Raquel P. F. Guiné, Daniela V. T. A. Costa, Paula M. R. Correia, Moisés Castro, Luis T. Guerra, Cristina A. Costa

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The aim of this work was to characterize a potential target group of people interested in participating into a training program in organic farming in the context of mobile-learning. The information sought addressed in particular, but not exclusively, possible contents, formats and forms of evaluation that will contribute to define the course objectives and curriculum, as well as to ensure that the course meets the needs of the learners and their preferences. The sample was selected among different European countries. The questionnaires were delivered electronically for answering online and in the end 135 consented valid questionnaires were obtained. The results allowed characterizing the target group and identifying their training needs and preferences towards m-learning formats, giving valuable tools to design the training offer.

Keywords: mobile-learning, organic farming, rural development, survey

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11164 Educational Tours as a Learning Tool to the Third Years Tourism Students of De La Salle University, Dasmarinas

Authors: Jackqueline Uy, Hannah Miriam Verano, Crysler Luis Verbo, Irene Gueco

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Educational tours are part of the curriculum of the College of Tourism and Hospitality Management, De La Salle University-Dasmarinas. They are highly significant to the students, especially Tourism students. The purpose of this study was to determine how effective educational tours were as a learning tool using the Experiential Learning Theory by David Kolb. This study determined the demographic profile of the third year tourism students in terms of gender, section, educational tours joined, and monthly family income and lastly, this study determined if there is a significant difference between the demographic profile of the respondents and their assessment of educational tours as a learning tool. The researchers used a historical research design with the third-year students of the bachelor of science in tourism management as the population size and used a random sampling method. The researchers made a survey questionnaire and utilized statistical tools such as weighted mean, frequency distribution, percentage, standard deviation, T-test, and ANOVA. The result of the study answered the profile of the respondents such as the gender, section, educational tour/s joined, and family monthly income. The findings of the study showed that the 3rd year tourism management students strongly agree that educational tours are a highly effective learning tool in terms of active experimentation, concrete experience, reflective observation, and abstract conceptualisation based on the data gathered from the respondents.

Keywords: CTHM, educational tours, experiential learning theory, De La Salle University Dasmarinas, tourism

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11163 Different Perceptions of Distance and Full-time Teaching Depending on Different Cultural Backgrounds: A Comparative Study

Authors: Daniel Ecler

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This paper aims to compare the data obtained using semi-structured questionnaires and find some connections between them, which could help to understand what factors affect the perception of the advantages and disadvantages of distance learning compared to conventional education. The data collected came from respondents from Czech and Chinese university students, and expectations were such that the different cultural environments from which the two groups come would have an impact on different experiences of distance education. With the help of variation-finding comparison, it turned out that Chinese students did not have such difficulties with the transition to distance learning as students from the Czech Republic, as most of them came into contact with some form of distance education in the past. In addition, it has also been shown that Chinese students use modern technology to a much greater extent, which has also made it easier for them to become accustomed to another form of teaching. In conclusion, Chinese students have greater preconditions for easier management of distance learning, while Czech students prefer more personal contact, and thus full-time teaching. It is obvious that both approaches have their pros and cons; now, it is necessary to find out how to use them for maximum efficiency of the educational process.

Keywords: Chinese college students, cultural background, Czech college students, distance learning, full-time teaching

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11162 Cirrhosis Mortality Prediction as Classification using Frequent Subgraph Mining

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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11161 Intercultural Strategies of Chinese Composers in the Organizational Structure of Their Works

Authors: Bingqing Chen

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The Opium War unlocked the gate of China. Since then, modern western culture has been imported strongly and spread throughout this Asian country. The monologue of traditional Chinese culture in the past has been replaced by the hustle and bustle of multiculturalism. In the field of music, starting from school music, China, a country without the concept of composition, was deeply influenced by western culture and professional music composition, and entered the era of professional music composition. Recognizing the importance of national culture, a group of insightful artists began to try to add ‘China’ to musical composition. However, due to the special historical origin of Chinese professional musical composition and the three times of cultural nihilism in China, professional musical composition at this time failed to interpret the deep language structure of local culture within Chinese traditional culture, but only regarded Chinese traditional music as a ‘melody material library.’ At this time, the cross-cultural composition still takes Western music as its ‘norm,’ while our own music culture only exists as the sound of the contrast of Western music. However, after reading scores extensively, watching video performances, and interviewing several active composers, we found that at least in the past 30 years, China has created some works that can be called intercultural music. In these kinds of music, composers put Chinese and Western, traditional and modern in an almost equal position to have a dialogue based on their deep understanding and respect for the two cultures. This kind of music connects two music worlds, and links the two cultural and ideological worlds behind it, and communicates and grows together. This paper chose the works of three composers with different educational backgrounds, and pay attention to how composers can make a dialogue at the organizational structure level of their works. Based on the strategies adopted by composers in structuring their works, this paper expounds on how the composer's music procedure shows intercultural in terms of whole sound effects and cultural symbols. By actively participating in this intercultural practice, composers resorting to various musical and extra-musical procedures to arrive at the so-called ‘innovation within tradition.’ Through the dialogue, we can activate the space of creative thinking and explore the potential contained in culture. This interdisciplinary research promotes the rethinking of the possibility of innovation in contemporary Chinese intercultural music composition, spanning the fields of sound studies, dialogue theory, cultural research, music theory, and so on. Recently, China is calling for actively promoting 'the construction of Chinese music canonization,’ expecting to form a particular music style to show national-cultural identity. In the era of globalization, it is possible to form a brand-new Chinese music style through intercultural composition, but it is a question about talents, and the key lies in how composers do it. There is no recipe for the formation of the Chinese music style, only the composers constantly trying and tries to solve problems in their works.

Keywords: dialogism, intercultural music, national-cultural identity, organization/structure, sound

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11160 Serious Game for Learning: A Model for Efficient Game Development

Authors: Zahara Abdulhussan Al-Awadai

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In recent years, serious games have started to gain an increasing interest as a tool to support learning across different educational and training fields. It began to serve as a powerful educational tool for improving learning outcomes. In this research, we discuss the potential of virtual experiences and games research outside of the games industry and explore the multifaceted impact of serious games and related technologies on various aspects of our lives. We highlight the usage of serious games as a tool to improve education and other applications with a purpose beyond the entertainment industry. One of the main contributions of this research is proposing a model that facilitates the design and development of serious games in a flexible and easy-to-use way. This is achieved by exploring different requirements to develop a model that describes a serious game structure with a focus on both aspects of serious games (educational and entertainment aspects).

Keywords: game development, requirements, serious games, serious game model

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11159 Individual Differences and Paired Learning in Virtual Environments

Authors: Patricia M. Boechler, Heather M. Gautreau

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In this research study, postsecondary students completed an information learning task in an avatar-based 3D virtual learning environment. Three factors were of interest in relation to learning; 1) the influence of collaborative vs. independent conditions, 2) the influence of the spatial arrangement of the virtual environment (linear, random and clustered), and 3) the relationship of individual differences such as spatial skill, general computer experience and video game experience to learning. Students completed pretest measures of prior computer experience and prior spatial skill. Following the premeasure administration, students were given instruction to move through the virtual environment and study all the material within 10 information stations. In the collaborative condition, students proceeded in randomly assigned pairs, while in the independent condition they proceeded alone. After this learning phase, all students individually completed a multiple choice test to determine information retention. The overall results indicated that students in pairs did not perform any better or worse than independent students. As far as individual differences, only spatial ability predicted the performance of students. General computer experience and video game experience did not. Taking a closer look at the pairs and spatial ability, comparisons were made on pairs high/matched spatial ability, pairs low/matched spatial ability and pairs that were mismatched on spatial ability. The results showed that both high/matched pairs and mismatched pairs outperformed low/matched pairs. That is, if a pair had even one individual with strong spatial ability they would perform better than pairs with only low spatial ability individuals. This suggests that, in virtual environments, the specific individuals that are paired together are important for performance outcomes. The paper also includes a discussion of trends within the data that have implications for virtual environment education.

Keywords: avatar-based, virtual environment, paired learning, individual differences

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11158 Uplink Throughput Prediction in Cellular Mobile Networks

Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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11157 Meta-Instruction Theory in Mathematics Education and Critique of Bloom’s Theory

Authors: Abdollah Aliesmaeili

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The purpose of this research is to present a different perspective on the basic math teaching method called meta-instruction, which reverses the learning path. Meta-instruction is a method of teaching in which the teaching trajectory starts from brain education into learning. This research focuses on the behavior of the mind during learning. In this method, students are not instructed in mathematics, but they are educated. Another goal of the research is to "criticize Bloom's classification in the cognitive domain and reverse it", because it cannot meet the educational and instructional needs of the new generation and "substituting math education instead of math teaching". This is an indirect method of teaching. The method of research is longitudinal through four years. Statistical samples included students ages 6 to 11. The research focuses on improving the mental abilities of children to explore mathematical rules and operations by playing only with eight measurements (any years 2 examinations). The results showed that there is a significant difference between groups in remembering, understanding, and applying. Moreover, educating math is more effective than instructing in overall learning abilities.

Keywords: applying, Bloom's taxonomy, brain education, mathematics teaching method, meta-instruction, remembering, starmath method, understanding

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11156 Examining The Effects of Parenting Style and Parents’ Social Attitudes on Social Development in Early Childhood

Authors: Amber Lim, Ted Ruffman

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A vast amount of research evidence indicates that children develop social attitudes that are similar to those of their parents. When using general measures of social attitudes, such as social dominance orientation (SDO), right-wing authoritarianism (RWA), and prejudice, studies show that parents' and children’s attitudes were correlated. However, the mechanisms behind the intergenerational transmission of attitudes remain largely unexplained. Since it was speculated that the origins of RWA could be traced back to one’s relationship with their parents, the aim of this study was to assess how parents’ social attitudes and parenting behavior are related to children’s social development. One line of research suggests that the different ways in which authoritarian and authoritative parents reason with their children may impact Theory of Mind (ToM) development. That is, inductive discipline (e.g., emphasising how the child’s actions affect others) facilitates empathy and ToM development. Conversely, past evidence shows that children have poorer ToM development when parents enforce rules without explanation. Thus, this study addresses the question of how parent behavior plays a role in the gradual acquisition of a ToM and social attitudes. Seventy parents reported their social attitudes, parenting behavior, and their child’s mental state and non-mental state vocabulary. Their children were given ToM and perspective-taking tasks, along with a friend choice task to measure racial bias and anti-fat bias. As hypothesised, parents’ use of inductive reasoning correlated with children’s performance on Theory of Mind tasks. Mothers’ inductive reasoning facilitated children’s acquisition of mental state vocabulary. Parents’ autonomy granting was associated with improved mental state vocabulary. Authoritarian parenting traits such as verbal hostility were linked to children’s racial bias. These findings highlight the importance of parent-child discussion in shaping children’s social understanding.

Keywords: parenting style, prejudice, social attitudes, social understanding, theory of mind

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11155 Analyzing the Feasibility of Low-Cost Composite Wind Turbine Blades for Residential Energy Production

Authors: Aravindhan Nepolean, Chidamabaranathan Bibin, Rajesh K., Gopinath S., Ashok Kumar R., Arun Kumar S., Sadasivan N.

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Wind turbine blades are an important parameter for surging renewable energy production. Optimizing blade profiles and developing new materials for wind turbine blades take a lot of time and effort. Even though many standards for wind turbine blades have been developed for large-scale applications, they are not more effective in small-scale applications. We used acrylonitrile-butadiene-styrene to make small-scale wind turbine blades in this study (ABS). We chose the material because it is inexpensive and easy to machine into the desired form. They also have outstanding chemical, stress, and creep resistance. The blade measures 332 mm in length and has a 664 mm rotor diameter. A modal study of blades is carried out, as well as a comparison with current e-glass fiber. They were able to balance the output with less vibration, according to the findings. Q blade software is used to simulate rotating output. The modal analysis testing and prototype validation of wind turbine blades were used for experimental validation.

Keywords: acrylonitrile-butadiene-styrene, e-glass fiber, modal, renewable energy, q-blade

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11154 Comparing the Willingness to Communicate in a Foreign Language of Bilinguals and Monolinguals

Authors: S. Tarighat, F. Shateri

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This study explored the relationship between L2 Willingness to Communicate (WTC) of bilinguals and monolinguals in a foreign language using a snowball sampling method to collect questionnaire data from 200 bilinguals and monolinguals studying a foreign language (FL). The results indicated a higher willingness to communicate in a foreign language (WTC-FL) performed by bilinguals compared to that of the monolinguals with a weak significance. Yet a stronger significance was found in the relationship between the age of onset of bilingualism and WTC-FL. The researcher proposed that L2 WTC is indirectly influenced by knowledge of other languages, which can boost L2 confidence and reduce L2 anxiety and consequently lead to higher L2 WTC when learning a different L2. The study also found the age of onset of bilingualism to be a predictor of L2 WTC when learning a FL. The results emphasize the importance of bilingualism and early bilingualism in particular.

Keywords: bilingualism, foreign language learning, l2 acquisition, willingness to communicate

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11153 Impact of Personality on Vengeance and Forgiveness in Young Adults

Authors: Marium Javaid Bajwa, Ruhi Khalid

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This study aimed to identify personality traits that affect vengeful and forgiving behavior among people. Big Five Personality Inventory, Vengeance Scale and Trait Forgiveness Scale were administered to 159 male and female students to have a base-line data for the study. Overall, agreeableness trait predicted forgiveness. Vengeance showed significant negative relation with agreeableness, conscientiousness and openness. Whereas Independent T-test indicated that personality traits plays crucial role in determining vengeful and forgiving behaviors in contrast to gender in young adults.

Keywords: personality, traits, vengeance, forgiveness

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11152 Introducing a Video-Based E-Learning Module to Improve Disaster Preparedness at a Tertiary Hospital in Oman

Authors: Ahmed Al Khamisi

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The Disaster Preparedness Standard (DPS) is one of the elements that is evaluated by the Accreditation Canada International (ACI). ACI emphasizes to train and educate all staff, including service providers and senior leaders, on emergency and disaster preparedness upon the orientation and annually thereafter. Lack of awareness and deficit of knowledge among the healthcare providers about DPS have been noticed in a tertiary hospital where ACI standards were implemented. Therefore, this paper aims to introduce a video-based e-learning (VB-EL) module that explains the hospital’s disaster plan in a simple language which will be easily accessible to all healthcare providers through the hospital’s website. The healthcare disaster preparedness coordinator in the targeted hospital will be responsible to ensure that VB-EL is ready by 25 April 2019. This module will be developed based on the Kirkpatrick evaluation method. In fact, VB-EL combines different data forms such as images, motion, sounds, text in a complementary fashion which will suit diverse learning styles and individual learning pace of healthcare providers. Moreover, the module can be adjusted easily than other tools to control the information that healthcare providers receive. It will enable healthcare providers to stop, rewind, fast-forward, and replay content as many times as needed. Some anticipated limitations in the development of this module include challenges of preparing VB-EL content and resistance from healthcare providers.

Keywords: Accreditation Canada International, Disaster Preparedness Standard, Kirkpatrick evaluation method, video-based e-learning

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11151 Learning Materials of Atmospheric Pressure Plasma Process: Turning Hydrophilic Surface to Hydrophobic

Authors: C.W. Kan

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This paper investigates the use of atmospheric pressure plasma for improving the surface hydrophobicity of polyurethane synthetic leather with tetramethylsilane (TMS). The atmospheric pressure plasma treatment with TMS is a single-step process to enhance the hydrophobicity of polyurethane synthetic leather. The hydrophobicity of the treated surface was examined by contact angle measurement. The physical and chemical surface changes were evaluated by scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). The purpose of this paper is to provide learning materials for understanding how to use atmospheric pressure plasma in the textile finishing process to transform a hydrophilic surface to hydrophobic.

Keywords: Learning materials, atmospheric pressure plasma treatment, hydrophobic, hydrophilic, surface

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11150 STEM (Science–Technology–Engineering–Mathematics) Based Entrepreneurship Training, Within a Learning Company

Authors: Diana Mitova, Krassimir Mitrev

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To prepare the current generation for the future, education systems need to change. It implies a way of learning that meets the demands of the times and the environment in which we live. Productive interaction in the educational process implies an interactive learning environment and the possibility of personal development of learners based on communication and mutual dialogue, cooperation and good partnership in decision-making. Students need not only theoretical knowledge, but transferable skills that will help them to become inventors and entrepreneurs, to implement ideas. STEM education , is now a real necessity for the modern school. Through learning in a "learning company", students master examples from classroom practice, simulate real life situations, group activities and apply basic interactive learning strategies and techniques. The learning company is the subject of this study, reduced to entrepreneurship training in STEM - technologies that encourage students to think outside the traditional box. STEM learning focuses the teacher's efforts on modeling entrepreneurial thinking and behavior in students and helping them solve problems in the world of business and entrepreneurship. Learning based on the implementation of various STEM projects in extracurricular activities, experiential learning, and an interdisciplinary approach are means by which educators better connect the local community and private businesses. Learners learn to be creative, experiment and take risks and work in teams - the leading characteristics of any innovator and future entrepreneur. This article presents some European policies on STEM and entrepreneurship education. It also shares best practices for training company training , with the integration of STEM in the learning company training environment. The main results boil down to identifying some advantages and problems in STEM entrepreneurship education. The benefits of using integrative approaches to teach STEM within a training company are identified, as well as the positive effects of project-based learning in a training company using STEM. Best practices for teaching entrepreneurship through extracurricular activities using STEM within a training company are shared. The following research methods are applied in this research paper: Theoretical and comparative analysis of principles and policies of European Union countries and Bulgaria in the field of entrepreneurship education through a training company. Experiences in entrepreneurship education through extracurricular activities with STEM application within a training company are shared. A questionnaire survey to investigate the motivation of secondary vocational school students to learn entrepreneurship through a training company and their readiness to start their own business after completing their education. Within the framework of learning through a "learning company" with the integration of STEM, the activity of the teacher-facilitator includes the methods: counseling, supervising and advising students during work. The expectation is that students acquire the key competence "initiative and entrepreneurship" and that the cooperation between the vocational education system and the business in Bulgaria is more effective.

Keywords: STEM, entrepreneurship, training company, extracurricular activities

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11149 Defect Identification in Partial Discharge Patterns of Gas Insulated Switchgear and Straight Cable Joint

Authors: Chien-Kuo Chang, Yu-Hsiang Lin, Yi-Yun Tang, Min-Chiu Wu

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With the trend of technological advancement, the harm caused by power outages is substantial, mostly due to problems in the power grid. This highlights the necessity for further improvement in the reliability of the power system. In the power system, gas-insulated switches (GIS) and power cables play a crucial role. Long-term operation under high voltage can cause insulation materials in the equipment to crack, potentially leading to partial discharges. If these partial discharges (PD) can be analyzed, preventative maintenance and replacement of equipment can be carried out, there by improving the reliability of the power grid. This research will diagnose defects by identifying three different defects in GIS and three different defects in straight cable joints, for a total of six types of defects. The partial discharge data measured will be converted through phase analysis diagrams and pulse sequence analysis. Discharge features will be extracted using convolutional image processing, and three different deep learning models, CNN, ResNet18, and MobileNet, will be used for training and evaluation. Class Activation Mapping will be utilized to interpret the black-box problem of deep learning models, with each model achieving an accuracy rate of over 95%. Lastly, the overall model performance will be enhanced through an ensemble learning voting method.

Keywords: partial discharge, gas-insulated switches, straight cable joint, defect identification, deep learning, ensemble learning

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11148 Meta Mask Correction for Nuclei Segmentation in Histopathological Image

Authors: Jiangbo Shi, Zeyu Gao, Chen Li

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Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

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11147 The Psychology of Virtual Relationships Provides Solutions to the Challenges of Online Learning: A Pragmatic Review and Case Study from the University of Birmingham, UK

Authors: Catherine Mangan, Beth Anderson

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There has been a significant drive to use online or hybrid learning in Higher Education (HE) over recent years. HEs with a virtual presence offer their communities a range of benefits, including the potential for greater inclusivity, diversity, and collaboration; more flexible learning packages; and more engaging, dynamic content. Institutions can also experience significant challenges when seeking to extend learning spaces in this way, as can learners themselves. For example, staff members’ and learners’ digital literacy varies (as do their perceptions of technologies in use), and there can be confusion about optimal approaches to implementation. Furthermore, the speed with which HE institutions have needed to shift to fully online or hybrid models, owing to the COVID19 pandemic, has highlighted the significant barriers to successful implementation. HE environments have been shown to predict a range of organisational, academic, and experiential outcomes, both positive and negative. Much research has focused on the social aspect of virtual platforms, as well as the nature and effectiveness of the technologies themselves. There remains, however, a relative paucity of synthesised knowledge on the psychology of learners’ relationships with their institutions; specifically, how individual difference and interpersonal factors predict students’ ability and willingness to engage with novel virtual learning spaces. Accordingly, extending learning spaces remains challenging for institutions, and wholly remote courses, in particular, can experience high attrition rates. Focusing on the last five years, this pragmatic review summarises evidence from the psychological and pedagogical literature. In particular, the review highlights the importance of addressing the psychological and relational complexities of students’ shift from offline to online engagement. In doing so, it identifies considerations for HE institutions looking to deliver in this way.

Keywords: higher education, individual differences, interpersonal relationships, online learning, virtual environment

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11146 The Role of Vocabulary in Task-based Language Teaching in International and Iranian Contexts

Authors: Parima Fasih

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The present review of literature explored the role of vocabulary in task-based language teaching (TBLT). The first focus of the present paper is to explain different aspects of vocabulary knowledge, and it continues with an introduction to TBLT. Second, the role of vocabulary and vocabulary tasks in TBLT is explained. Next, an overview of the recent empirical studies about task-based vocabulary teaching in international and Iranian contexts context is presented to address the research question concerning the effect of task-based vocabulary teaching on EFL learners' vocabulary learning. Based on the conclusions that are drawn from the previous studies, the implications reveal how the findings influence students' vocabulary learning and teachers' vocabulary teaching methods.

Keywords: vocabulary, task, task-based, task-based language teaching, vocabulary learning, vocabulary teaching

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11145 Defect Detection for Nanofibrous Images with Deep Learning-Based Approaches

Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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11144 Learning Gains and Constraints Resulting from Haptic Sensory Feedback among Preschoolers' Engagement during Science Experimentation

Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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11143 A Deep Learning Based Method for Faster 3D Structural Topology Optimization

Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

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Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

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11142 Building the Professional Readiness of Graduates from Day One: An Empirical Approach to Curriculum Continuous Improvement

Authors: Fiona Wahr, Sitalakshmi Venkatraman

Abstract:

Industry employers require new graduates to bring with them a range of knowledge, skills and abilities which mean these new employees can immediately make valuable work contributions. These will be a combination of discipline and professional knowledge, skills and abilities which give graduates the technical capabilities to solve practical problems whilst interacting with a range of stakeholders. Underpinning the development of these disciplines and professional knowledge, skills and abilities, are “enabling” knowledge, skills and abilities which assist students to engage in learning. These are academic and learning skills which are essential to common starting points for both the learning process of students entering the course as well as forming the foundation for the fully developed graduate knowledge, skills and abilities. This paper reports on a project created to introduce and strengthen these enabling skills into the first semester of a Bachelor of Information Technology degree in an Australian polytechnic. The project uses an action research approach in the context of ongoing continuous improvement for the course to enhance the overall learning experience, learning sequencing, graduate outcomes, and most importantly, in the first semester, student engagement and retention. The focus of this is implementing the new curriculum in first semester subjects of the course with the aim of developing the “enabling” learning skills, such as literacy, research and numeracy based knowledge, skills and abilities (KSAs). The approach used for the introduction and embedding of these KSAs, (as both enablers of learning and to underpin graduate attribute development), is presented. Building on previous publications which reported different aspects of this longitudinal study, this paper recaps on the rationale for the curriculum redevelopment and then presents the quantitative findings of entering students’ reading literacy and numeracy knowledge and skills degree as well as their perceived research ability. The paper presents the methodology and findings for this stage of the research. Overall, the cohort exhibits mixed KSA levels in these areas, with a relatively low aggregated score. In addition, the paper describes the considerations for adjusting the design and delivery of the new subjects with a targeted learning experience, in response to the feedback gained through continuous monitoring. Such a strategy is aimed at accommodating the changing learning needs of the students and serves to support them towards achieving the enabling learning goals starting from day one of their higher education studies.

Keywords: enabling skills, student retention, embedded learning support, continuous improvement

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11141 Investigating the Factors Affecting the Innovation of Firms in Metropolitan Regions: The Case of Mashhad Metropolitan Region, Iran

Authors: Hashem Dadashpoor, Sadegh Saeidi Shirvan

Abstract:

While with the evolution of the economy towards a knowledge-based economy, innovation is a requirement for metropolitan regions, the adoption of an open innovation strategy is an option and a requirement for many industrial firms in these regions. Studies show that investing in research and development units cannot alone increase innovation. Within the framework of the theory of learning regions, this gap, which scholars call it the ‘innovation gap’, is filled with regional features of firms. This paper attempts to investigate the factors affecting the open innovation of firms in metropolitan regions, and it searches for these in territorial innovation models and, in particular, the theory of learning regions. In the next step, the effect of identified factors which is considered as regional learning factors in this research is analyzed on the innovation of sample firms by SPSS software using multiple linear regression. The case study of this research is constituted of industrial enterprises from two groups of food industry and auto parts in Toos industrial town in Mashhad metropolitan region. For data gathering of this research, interviews were conducted with managers of industrial firms using structured questionnaires. Based on this study, the effect of factors such as size of firms, inter-firm competition, the use of local labor force and institutional infrastructures were significant in the innovation of the firms studied, and 44% of the changes in the firms’ innovation occurred as a result of the change in these factors.

Keywords: regional knowledge networks, learning regions, interactive learning, innovation

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11140 Deep Learning Based Unsupervised Sport Scene Recognition and Highlights Generation

Authors: Ksenia Meshkova

Abstract:

With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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11139 Machine Learning Methods for Network Intrusion Detection

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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11138 Building Successful Organizational Business Communication and Its Impact on Business Performance: An Intra- and Inter-Organizational Perspective

Authors: Aynura Valiyeva, Basil John Thomas

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Intra-firm communication is critical for building synergy amongst internal business units of a firm, where employees from various functional departments and ranks incorporate their decision-making, understanding of organizational objectives, as well as common norms and culture for better organizational effectiveness. This study builds on and assesses a framework of the causes and consequences of effective communication in business interactions between customer and supplier firms, and the path for efficient communication within a firm. The proposed study’s structural equation modeling (SEM) analysis based on 352 sample responses collected from firm representatives at different job positions ranging from marketing to logistics operations, reveals that, in the frame of reference of intra-organizational communication, organization characteristics and shared values, top management support and style of leadership, as well as information technology, are all significantly related to communication effectiveness. Furthermore, the frequency and variety of interactions enhance the outcome of communication, that improves a company’s performance. The results reveal that cultural factors are significantly related to communication effectiveness, as well as the shared beliefs and goals. In terms of organizational factors, leadership style, top management support and information technology are significant determinants of effective communication. Among the contextual factors, interaction frequency and diversity are found to be priority factors. This study also tests the relationship between supplier and supplier firm performance in the context of communication effectiveness, and finds that they are closely related, when trust and commitment is built between business partners. When firms do business in other multicultural contexts, language and shared values with destination country must be considered significant elements of communication process.

Keywords: business performance, intra-firm communication, inter-firm communication, structural equation modeling

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11137 Angiogenesis and Blood Flow: The Role of Blood Flow in Proliferation and Migration of Endothelial Cells

Authors: Hossein Bazmara, Kaamran Raahemifar, Mostafa Sefidgar, Madjid Soltani

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Angiogenesis is formation of new blood vessels from existing vessels. Due to flow of blood in vessels, during angiogenesis, blood flow plays an important role in regulating the angiogenesis process. Multiple mathematical models of angiogenesis have been proposed to simulate the formation of the complicated network of capillaries around a tumor. In this work, a multi-scale model of angiogenesis is developed to show the effect of blood flow on capillaries and network formation. This model spans multiple temporal and spatial scales, i.e. intracellular (molecular), cellular, and extracellular (tissue) scales. In intracellular or molecular scale, the signaling cascade of endothelial cells is obtained. Two main stages in development of a vessel are considered. In the first stage, single sprouts are extended toward the tumor. In this stage, the main regulator of endothelial cells behavior is the signals from extracellular matrix. After anastomosis and formation of closed loops, blood flow starts in the capillaries. In this stage, blood flow induced signals regulate endothelial cells behaviors. In cellular scale, growth and migration of endothelial cells is modeled with a discrete lattice Monte Carlo method called cellular Pott's model (CPM). In extracellular (tissue) scale, diffusion of tumor angiogenic factors in the extracellular matrix, formation of closed loops (anastomosis), and shear stress induced by blood flow is considered. The model is able to simulate the formation of a closed loop and its extension. The results are validated against experimental data. The results show that, without blood flow, the capillaries are not able to maintain their integrity.

Keywords: angiogenesis, endothelial cells, multi-scale model, cellular Pott's model, signaling cascade

Procedia PDF Downloads 425