Search results for: skills gained through learning

Authors: Lori L. Scarlatos, Ryan Courtney

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This paper explores the impact that playing a casual game can have on a player's learning and subsequent behavior. A casual mobile game, Container Chaos, was created to teach undergraduate students about the carbon footprint of various disposable beverage containers. Learning was tested with a short quiz, and behavior was tested by observing which beverage containers players choose when offered a drink and a snack. The game was tested multiple times, under a variety of different circumstances. Findings of these tests indicate that, with extended play over time, players can learn new information and sometimes even change their behavior as a result. This has implications for how other casual games can be used to teach concepts and possibly modify behavior.

Keywords: behavior, carbon footprint, casual games, environmental impact, material sciences

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Authors: Eny Syatriana, Ardiansyah

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The purpose of recent study was to develop a learning model on writing, based on the reading texts which will be read by the students using reflection strategy. The strategy would allow the students to read the text and then they would write back the main idea and to develop the text by using their own sentences. So, the writing practice was begun by reading an interesting text, then the students would develop the text which has been read into their writing. The problem questions are (1) what kind of learning model that can develop the students writing ability? (2) what is the achievement of the students of STKIP YPUP through reflection strategy? (3) is the using of the strategy effective to develop students competence In writing? (4) in what level are the students interest toward the using of a strategy In writing subject? This development research consisted of some steps, they are (1) need analysis (2) model design (3) implementation (4) model evaluation. The need analysis was applied through discussion among the writing lecturers to create a learning model for writing subject. To see the effectiveness of the model, an experiment would be delivered for one class. The instrument and learning material would be validated by the experts. In every steps of material development, there was a learning process, where would be validated by an expert. The research used development design. These Principles and procedures or research design and development .This study, researcher would do need analysis, creating prototype, content validation, and limited empiric experiment to the sample. In each steps, there should be an assessment and revision to the drafts before continue to the next steps. The second year, the prototype would be tested empirically to four classes in STKIP YPUP for English department. Implementing the test greatly was done through the action research and followed by evaluation and validation from the experts.

Keywords: learning model, reflection, strategy, reading, writing, development

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Authors: Victor William Harris

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Objective. This study examined the impact of the Positive Behavioral Management Skills (PBMS) online educational program on participants (n = 624) in a Southeastern region of the United States. The PBMS program incorporates established positive psychology behavioral management principles with new research-based practices designed to promote healthy and satisfying relationships between adults and children while constructively managing and preventing problematic behavior. Additionally, the PBMS program assists parents and teachers in recognizing the motivations behind a wide range of misbehaviors. The program also offers to forewarn some of the most common mistakes (or “parent traps”) in child behavioral management and describes how they can be avoided. It also describes how to recognize and capitalize on “teachable moments,” which are indispensable in the developmental process. Design. A retrospective-pre-test-then-post-test design was used to reduce response shift bias when assessing knowledge and skill intervention outcomes for twenty-two behavioral management variables. Results. The PBMS program was shown to be effective for increasing knowledge and skills related to managing misbehavior while reinforcing interpersonal relationships and fostering a sense of responsibility and capability within the child. Large standardized mean effect size changes from before to after program intervention was documented for PBMS participants on all twenty-two variables studied. Conclusion. The PBMS program showed initial positive outcomes to assist participants in the sample studied to increase their knowledge and skills in managing child behavior successfully. Implications for parents, educators and practitioners are discussed.

Keywords: behavioral management, discipline, parent education, positive parenting, positive psychology-parenting

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Authors: Marziyeh Yousefi, Hossein Nassaji

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This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: meta-analysis, effect size, L2 pragmatics, comprehensive meta-analysis, face-to-face, computer-assisted language learning

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Authors: Nabil El Kadhi, Minerva M. Bunagan

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The dynamism in education, particularly in the area of teaching, learning and assessment has caused Higher Education Institutions (HEIs) worldwide to seek for ways to continuously improve their educational processes. HEIs use outcomes of institutional audits, assessments and accreditations, for improvement. In this study, the published institutional audit reports of HEIs in the Sultanate of Oman were analyzed to produce features of good practice; identify challenges along Teaching, Learning Assessment (TLA); and propose a framework that puts major emphasis in having a quality-assured TLA, including a set of principles that can be used as basis in succeeding an institutional visit. The TLA framework, which shows the TLA components, characteristics of the components, related expectation, including implementation tool/ strategy and pitfalls can be used by HEIs to have an adequate understanding of the scope of audit and be able to satisfy institutional audit requirements. The scope of this study can be widened by exploring the other requirements of the Institutional Audits in the Sultanate of Oman, particularly the area on Governance and Management and Student Support Services.

Keywords: accreditation, audit, teaching, learning and assessment, quality assurance

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Zoe Wong

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The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

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Authors: Krishna Chandra Paudel

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This paper explores the association between the perceived classroom environment and mathematics learning and test anxiety among secondary level students in Nepal. Categorizing the students in three dominant variables- gender, ethnicity and previous schooling, and selecting sample students with respect to higher mathematics anxiety from five heterogeneous classes, the research explores disparities in student's mathematics cognition and reveals nexus between classroom environment and mathematics learning and test anxiety. This research incorporates social learning theory and social development theory as interpretive tool for analyzing themes through qualitative data. Focussing on the interviews with highly mathematics learning anxious students, the study sheds light on how mathematics anxiety among the targeted students is interlinked with multiple factors. The research basically exposes the students’ lack of mathematical passion, their association with other students and participation in classroom learning, asymmetrical content and their lack of preparedness for the tests as caustic factors behind such anxieties. The study further reveals that students’ lack of foundational knowledge and complexity of mathematical content have jointly contributed to mathematics anxiety. Admitting learning as a reciprocal experience, the study points out that the students’ gender, ethnicity and disparities in previous schooling in the context of Nepal has very insignificant impact on students’ mathematics anxiety. It finally recommends that the students who get trapped into the vicious cycle of mathematics anxiety require positive and supportive classroom environment along with inspiring comments/compliments and symmetrical course contents.

Keywords: anxiety, asymmetry, cognition, habitus, pedagogy, preparedness

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Authors: Bello Theodora O., Animola Odunayo V., Owoade Johnson T.

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With the advent of Covid-19, online classroom instruction became a very important mode of instruction delivery during which learners were engaged in both collaborative and online interactive learning process, but along with it are challenges as well as its deliverables. This study therefore investigated the various online platform used by the students for learning among fresh undergraduate students of Obafemi Awolowo University, Ile-Ife, Osun Sate. It also assessed the student’s perception towards online learning in the university and examined the influence of collaborative learning among the students. Lastly, it examined the problems that are associated with collaborative online learning instruction in the university. These were with a view to providing empirical information on problems and prospects of online classroom instruction among fresh undergraduate physical science students of Obafemi Awolowo University, Ile-Ife. The study employed a descriptive survey research technique. The population comprised all the fresh undergraduates in physical science departments of Obafemi Awolowo University, Ile-Ife. The sample consisted two hundred freshmen in physical science departments of Obafemi Awolowo University, Ile-Ife, who were selected using simple random techniques. During the selection, a questionnaire was used to collect data from the respondents. The data were analyzed using appropriate descriptive of frequency, simple percentage, and mean. Results showed that Google Meet 149(74.5%), Telegram 120(60.0%), and Google Classroom 143(71.5%), are the prominent online classroom instruction used by the students in Obafemi Awolowo University, Ile-Ife. The results also showed that the freshmen’s perception towards online classroom instruction in Obafemi Awolowo University, Ile-Ife is low with cluster mean of 2.97. It further revealed that collaborative learning enhances the learning ability of below average learners more than that of the above average and average students (73.6%). Finally, the result showed that they are affirmative of the problems associated with online classroom instruction in Obafemi Awolowo University, Ile-Ife with cluster mean of 3.01. The result concluded that most Online platform used by the fresher’s students in Obafemi Awolowo University, Ile-Ife are Google Meet, Telegram and Google Classroom. The students have negatives perception towards online classroom instruction and the students are affirmative of the problems associated with online classroom instruction among physical science freshmen in Obafemi Awolowo University, Ile-Ife.

Keywords: online, instruction, freshmen, physical science, collaborative

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Authors: A. Karunasena, P. Bandara, J. A. T. P. Jayasuriya, P. D. Gallage, J. M. S. D. Jayasundara, L. A. P. Y. P. Nuwanjaya

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Usage of smart learning concepts has increased rapidly all over the world recently as better teaching and learning methods. Most educational institutes such as universities are experimenting those concepts with their students. Smart learning concepts are especially useful for students to learn better in large classes. In large classes, the lecture method is the most popular method of teaching. In the lecture method, the lecturer presents the content mostly using lecture slides, and the students make their own notes based on the content presented. However, some students may find difficulties with the above method due to various issues such as speed in delivery. The purpose of this research is to assist students in large classes in the following content. The research proposes a solution with four components, namely note-taker, slide matcher, reference finder, and question presenter, which are helpful for the students to obtain a summarized version of the lecture note, easily navigate to the content and find resources, and revise content using questions.

Keywords: automatic summarization, extractive text summarization, speech recognition library, sentence extraction, automatic web search, automatic question generator, sentence scoring, the term weight

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Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Peter Adly Hamdy Fahmy

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The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Tamara Zappaterra

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The Learning Difficulties have an evolutionary nature. The international research has focused its analysis on the characteristics of Learning Difficulties in childhood, but we are still far from a thorough understanding of the nature of such disorders in adolescence and adulthood. Such issues become even more urgent in the university context. Spelling, meaning, and appropriate use of the specific vocabulary of the various disciplines represent an additional challenge for the dyslexic student. This paper explores the characteristics of Learning Difficulties in adulthood and the impact with the university teaching. It presents the results of an interdisciplinary project (educational, medical and engineering area) at University of Florence. The purpose of project is to design of a protocol for usability of teaching and individual study at university level. The project, after a first reconnaissance of user needs that have been reached with the participation of the very same protagonists, is at the stage of guidelines drafting for inclusion and education, to be used by teachers, students and administrative staff. The methodologies used are a questionnaire built on purpose and a series of focus groups with users. For collecting data during the focus groups it was decided to use a method typical of the Quality Function Deployment, a tool originally used for quality management, whose versatility makes it easy to use in a number of different context. The paper presents furthermore the findings of the project, the most significant elements of the guidelines for teaching, i.e. the section for teachers, whose aim is to implement a Learning Difficulties-friendly teaching, even at the university level, in compliance with italian Law 170/2010. The Guidelines for the didactic and inclusion of Learning Difficulties students of the University of Florence are articulated around a global and systemic plan of action, meant to accompany and protect the students during their study career, even before enrolling at the University, with different declination: the logistical, relational, educational, and didactic levels have been considered. These guidelines in Italy received the endorsement of the CNUDD. It is a systemic intervention plan for Learning Difficulties students, which roused and keeps rousing the interest of all the university system, with a radical consideration on academic teaching. Since while we try to provide the best Learning Difficulties-friendly didactic in compliance with the rules, no one can be exempted from a wider consideration on the nature and the quality of university teaching offered to all students.

Keywords: didactic tools, learning difficulties, special and inclusive education, university teaching

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Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

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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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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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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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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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Authors: Aboubacar Garba Konte, Wei Jun, Li Xiaohui

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Nowadays companies are facing increasing pressure. The market environment changes more frequently than ever. Therefore, managers have to develop their agility, their performance and their capacity for innovation. Most companies look for managerial innovations to develop in their employees qualities such as motivation, commitment, creativity, autonomy or even the ability to adapt to change and manage intensive pressure. On a more collective level, companies are looking for teams that are able to organize, communicate and develop a form of collective intelligence based on cooperation and solidarity. Among the many managerial innovations that are currently developing, mindfulness (or mindfulness) is drawing the attention of a growing number of companies (Google, Apple, Sony, ING ...), These companies have implemented programs based on mindfulness. Although the concept of mindfulness and its effects have been the subject of in-depth research in the psychological field, research on mindfulness in the field of management is still in its infancy and it is necessary to evaluate its contribution to organizations. The purpose of this research is to evaluate the effects of a mindfulness training among the managers of a Malian textile company (CMDT). We conducted a case study on their experience and their managerial practices. In addition, we discuss the innovative nature of mindfulness in terms of managerial practice The results show significant positive effects on two major skills identified by managers that raise significant difficulties in their daily lives: their ability to supervise a team of employees with all that this implies in terms of interpersonal skills and their ability to organize and prioritize their activities. In addition, the research methodology sheds light on the innovative nature of mindfulness in a favorable organizational environment.

Keywords: mindfulness, manager, managerial innovation, relational skills, organization and prioritization

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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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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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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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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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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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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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Authors: Joanna Konstantinou

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The study is about the challenges faced by entrepreneurs in a crisis context and in turbulent economies. The scope is to determine which factors, if any, are related to the success of a new business venture, such as innovation, access to funding and capital, enhanced digital skills, employment relations and organizational culture as well as a company’s strategic orientation towards international markets. The crisis context has been recorded to have affected the number of SMEs in the Greek economy, the number of people employed as well as the volume of the output produced. Although not all SMEs have been equally impacted by the crisis, which has been identified to affect certain sectors more than others, and although research is not exhaustive in that end, employment relations and patterns, firm’s age, and innovation practices in relation to employees’ learning curve seem to have a positive correlation with the successful survival and resilience of the firm. The aim is to identify important factors that can contribute positively to the success of a startup business, and that will allow businesses to acquire resilience and survive economic adversities, and it will focus on businesses of the Greek economy, the country with the longer lasting economic crisis and the findings will be lessons to learn for other economies.

Keywords: entrepreneurship, innovation, crisis, challenges

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Authors: Kishor Chandra Kandpal, Amit Kumar

Abstract:

The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

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Authors: Jaana Sepp, Ulvi Kõrgemaa, Kristi Puusepp, Õie Tähtla

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COVID-19 was officially recognized as a pandemic in late 2019 by the WHO, and it has led to changes in the education sector. Educational institutions were closed, and most schools adopted distance learning. Estonia is known as a digitally well-developed country. Based on that, in the pandemic time, nursing education continued, and new technological solutions were implemented. To provide nursing education, special focus was paid on quality and flexibility. The aim of this paper is to present administrative, digital, and technological solutions which support Estonian nursing educators to continue the study process in the pandemic time and to develop a sustainable solution for nursing education for the future. This paper includes the authors’ analysis of the documents and decisions implemented in the institutions through the pandemic time. It is a case study of Estonian nursing educators. Results of the analysis show that the implementation of distance learning principles challenges the development of innovative strategies and technics for the assessment of student performance and educational outcomes and implement new strategies to encourage student engagement in the virtual classroom. Additionally, hospital internships were canceled, and the simulation approach was deeply implemented as a new opportunity to develop and assess students’ practical skills. There are many other technical and administrative changes that have also been carried out, such as students’ support and assessment systems, the designing and conducting of hybrid and blended studies, etc. All services were redesigned and made more available, individual, and flexible. Hence, the feedback system was changed, the information was collected in parallel with educational activities. Experiences of nursing education during the pandemic time are widely presented in scientific literature. However, to conclude our study, authors have found evidence that solutions implemented in Estonian nursing education allowed the students to graduate within the nominal study period without any decline in education quality. Operative information system and flexibility provided the minimum distance between the students, support, and academic staff, and likewise, the changes were implemented quickly and efficiently. Institution memberships were updated with the appropriate information, and it positively affected their satisfaction, motivation, and commitment. We recommend that the feedback process and the system should be permanently changed in the future to place all members in the same information area, redefine the hospital internship process, implement hybrid learning, as well as to improve the communication system between stakeholders inside and outside the organization. The main limitation of this study relates to the size of Estonia. Nursing education is provided by two institutions only, and similarly, the number of students is low. The result could be generated to the institutions with a similar size and administrative system. In the future, the relationship between nurses’ performance and organizational outcomes should be deeply investigated and influences of the pandemic time education analyzed at workplaces.

Keywords: hybrid learning, nursing education, nursing, COVID-19

Procedia PDF Downloads 111

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

Abstract:

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

Procedia PDF Downloads 63