Search results for: learning management systems
20804 Enhancing Teachers’ Professional Development Programmes by the Implementation of Flipped Learning Instruction: A Qualitative Study
Authors: Badriah Algarni
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The pedagogy of ‘flipped learning’ is a form of blended instruction which is gaining widespread attention throughout the world. However, there is a lack of research concerning teachers’ professional development (TPD) in teachers who use flipping. The aim of this study was, therefore, to identify teachers’ perspectives on their experience of flipped PD. The study used a qualitative approach. Purposive sampling recruited nineteen teachers who participated in semi-structured, in-depth interviews. Thematic analysis was used to analyse the interview data. Overall, the teachers reported feeling more confident in their knowledge and skills after participating in flipped TPD. The analysis of the interview data revealed five overarching themes:1) increased engagement with the content; 2) better use of resources; 3) a social, collaborative environment; 4) exchange of practices and experiences; and 5) valuable online activities. These findings can encourage educators, policymakers, and trainers to consider flipped TPD as a form of PD to promote the building of teachers’ knowledge and stimulate reflective practices to improve teaching and learning practices.Keywords: engagement, flipped learning, teachers’ professional development, collaboration
Procedia PDF Downloads 9620803 The Nuclear Energy Museum in Brazil: Creative Solutions to Transform Science Education into Meaningful Learning
Authors: Denise Levy, Helen J. Khoury
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Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.Keywords: nuclear technology, multimedia learning tools, science museum, society and education
Procedia PDF Downloads 32420802 Engaging Students in Multimedia Constructivist Learning: Analysis of Students' Science Achievement
Authors: Maria Georgiou
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This study examined whether there was a statistically significant difference between pretest and posttest achievement scores for students who received multimedia-based instructions in science. The paired samples t-test was used to address the research question and to establish whether there was a significant difference between pretest and posttest scores that may have occurred based on the students’ learning experience with multimedia technology. Findings indicated that there was a significant difference in students’ achievement scores before and after a multimedia-based instruction. Students’ achievement scores were increased by approximately two points, after students received multimedia-based instruction. On a paired samples t-test, a high level of significance was found, p = 0.000. Opportunities to learn with multimedia are more likely to result in sustained improvements in student achievement and a deeper understanding of science content. Multimedia can make learning more active and student-centered and activate student motivation.Keywords: constructivist learning, hyperstudio, multimedia, multimedia-based instruction
Procedia PDF Downloads 16220801 Exploring the Potential of Mobile Learning in Distance Higher Education: A Case Study of the University of Jammu, Jammu, and Kashmir
Authors: Darshana Sharma
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Distance Education has emerged as a viable alternative to serve the higher educational needs of the socially and economically disadvantaged people of the remote, rural areas of Jammu region. The University of Jammu is a National Accreditation, and Assessment Council accredited, A+ university and has been accorded graded autonomy by the University Grants Commission. It is a dual mode university offering academic programmes through the regular departments and through the Directorate of Distance Education. The Directorate of Distance Education, University of Jammu still uses printed study material as a mode of instructional delivery. The development of technologies has assured increased interaction and communication for distance learners throughout the distance open learning institutions. Though it is tempting and convenient to adopt technology already being used by others, it may not prove effective for the simple reason that two institutions may be unlike in some respect. The use of technology must be conceived in view of the needs of the learners; geographical socio-economic-cultural and technological contexts and financial, administrative and academic resources of the institution. Mobile learning (m-learning) is a novel approach to knowledge acquisition and dissemination and is gaining global attention. It has evolved as one of the useful channels of distance learning promoting interaction between learners and teachers. It is felt that the Directorate of Distance Education, University of Jammu also needs to adopt new technologies to provide more effective academic and information support to distance learners in order to keep them motivated and also to develop self-learning skills. The chief objective of the research on which this paper is based was to measure the opinion of the distance learners of the DDE, the University of Jammu about the merits of mobile learning. It also explores their preferences for implementing mobile learning. The survey research design of descriptive research has been used. The data was collected from 400 distance learners enrolled with undergraduate and post-graduate programmes using self-constructed questionnaire containing five-point Likert scale items arranging from strongly agree, agree, indifferent, disagree and strongly disagree. Percentages were used to analyze the data. The findings lead to conclude that mobile learning has a great potential for the DDE for reaching out to the rural, remotely located distance learners of the Jammu region and also to improve the teaching-learning environment. The paper also finds out the challenges in the implementation of mobile learning in the region and further makes suggestions for effective implementation of mobile learning in DDE, University of Jammu.Keywords: directorate of distance education, mobile learning, national accreditation and assessment council, university of Jammu
Procedia PDF Downloads 12320800 The Effectiveness of Gamified Learning on Student Learning in Computer Science Education: A Systematic Review (2010-2018)
Authors: Shurui Bai, Biyun Huang, Khe Foon Hew
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Gamification is defined as the use of game design elements in non-game contexts. The primary purpose of using gamification in an educational context is to engage students in school activities such that their likelihood of completion is increased. But how actually effective is gamification in improving student learning? In order to answer this question, this paper provides a systematic review of prior research studies on gamification in K-12 and university contexts limited to computer science discipline. Unlike other published gamification review works, we specifically analyzed comparison-based studies in quasi-experiment, historical control, and randomization rather than studies with mere anecdotal or phenomenological results. The main purpose for this is to discuss possible causal effects of gamified practices on student performance, behavior change, and perceptual skills following an integrative model. Implications for practice are discussed, along with several suggestions for future research studies.Keywords: computer science, gamification, learning performance, systematic review
Procedia PDF Downloads 13120799 Conceptual Modeling of the Relationship between Project Management Practices and Knowledge Absorptive Capacity Using Interpretive Structural Modeling Method
Authors: Seyed Abdolreza Mosavi, Alireza Babakhan, Elham Sadat Hoseinifard
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Knowledge-based firms need to design mechanisms for continuous absorptive and creation of knowledge in order to ensure their survival in the competitive arena and to follow the path of development. Considering the project-oriented nature of product development activities in knowledge-based firms on the one hand and the importance of analyzing the factors affecting knowledge absorptive capacity in these firms on the other, the purpose of this study is to identify and classify the factors affecting project management practices on absorptive knowledge capacity. For this purpose, we have studied and reviewed the theoretical literature in the field of project management and absorptive knowledge capacity so as to clarify its dimensions and indexes. Then, using the ISM method, the relationship between them has been studied. To collect data, 21 questionnaires were distributed in project-oriented knowledge-based companies. The results of the ISM method analysis provide a model for the relationship between project management activities and knowledge absorptive capacity, which includes knowledge acquisition capacity, scope management, time management, cost management, quality management, human resource management, communications management, procurement management, risk management, stakeholders management and integration management. Having conducted the MICMAC analysis, we divided the variables into three groups of independent, relational and dependent variables and came up with no variables to be included in the group of autonomous variables.Keywords: knowledge absorptive capacity, project management practices, knowledge-based firms, interpretive structural modeling
Procedia PDF Downloads 19720798 Hybrid GNN Based Machine Learning Forecasting Model For Industrial IoT Applications
Authors: Atish Bagchi, Siva Chandrasekaran
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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning
Procedia PDF Downloads 15020797 Through 7S Model to Promote the Service Innovation Management
Authors: Cheng Fang Hsu
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Call center is the core of building customer relationship management system. Under the strong competitive stress, it becomes a new profiting challenge for a successful enterprise. Call center is a department not only to provide customer service but also to bring business profit. This is the qualitative case study in Taiwan bank service industry which goes on deeper exploration, and analysis by business interviews and industrial analysis. This study starts from the establishment, development, and management after the reforming of the case call center. Through SWOT analysis, and industrial analysis, this study adopted 7S model to explain how the call center reforms from service oriented to profit oriented and from cost management to profit management. The results indicated how service innovation management promotes call center to be operated as a market profit competition center. The recommendations are indicated to support the call center on marketing profit by service innovation management.Keywords: call center, 7S model, service innovation management, bioinformatics
Procedia PDF Downloads 48820796 Credit Cooperatives: A Factor for Improving the Sustainable Management of Private Forests
Authors: Todor Nickolov Stoyanov
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Cooperatives are present in all countries and in almost all sectors, including agriculture, forestry, food, finance, health, marketing, insurance and credit. Strong cooperatives are able to overcome many of the difficulties faced by private owners. Cooperatives use seven principles, including the 'Community Concern" principle, which enables cooperatives to work for the sustainable development of the community. The members of cooperatives may use different systems for generating year-round employment and for receiving sustainable income through performing different forestry activities. Various methods are used during the preparation of the report. These include literature reviews, statistics, secondary data and expert interviews. The members of the cooperatives are benefits exclusively from increasing the efficiency of the various products and from the overall yield of the harvest, and ultimately from achieving better profit through cooperative efforts. Cooperatives also use other types of activities that are an additional opportunity for cooperative income. There are many heterogeneous activities in the production and service sectors of the forest cooperatives under consideration. Some cooperatives serve dairies, distilleries, woodworking enterprises, tourist homes, hotels and motels, shops, ski slopes, sheep breeding, etc. Through the revenue generated by the activity, cooperatives have the opportunity to carry out various environmental and protective activities - recreation, water protection, protection of endangered and endemic species, etc., which in the case of small-scale forests cannot be achieved and the management is not sustainable. The conclusions indicate the results received in the analysis. Cooperative management of forests and forest lands gives higher incomes to individual owners. The management of forests and forest lands through cooperatives helps to carry out different environmental and protective activities. Cooperative forest management provides additional means of subsistence to the owners of poor forest lands. Cooperative management of forests and forest lands support owners to implement the forest management plans and to apply sustainable management of these territories.Keywords: cooperative, forestry, forest owners, principles of cooperation
Procedia PDF Downloads 24520795 Gradient Boosted Trees on Spark Platform for Supervised Learning in Health Care Big Data
Authors: Gayathri Nagarajan, L. D. Dhinesh Babu
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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform
Procedia PDF Downloads 24120794 A Performance Study of Fixed, Single-Axis and Dual-Axis Photovoltaic Systems in Kuwait
Authors: A. Al-Rashidi, A. El-Hamalawi
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In this paper, a performance study was conducted to investigate single and dual-axis PV systems to generate electricity in five different sites in Kuwait. Relevant data were obtained by using two sources for validation purposes. A commercial software, PVsyst, was used to analyse the data, such as metrological data and other input parameters, and compute the performance parameters such as capacity factor (CF) and final yield (YF). The results indicated that single and dual-axis PV systems would be very beneficial to electricity generation in Kuwait as an alternative source to conventional power plants, especially with the increased demand over time. The ranges were also found to be competitive in comparison to leading countries using similar systems. A significant increase in CF and YF values around 24% and 28.8% was achieved related to the use of single and dual systems, respectively.Keywords: single-axis and dual-axis photovoltaic systems, capacity factor, final yield, Kuwait
Procedia PDF Downloads 29620793 Simulation of Obstacle Avoidance for Multiple Autonomous Vehicles in a Dynamic Environment Using Q-Learning
Authors: Andreas D. Jansson
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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation
Procedia PDF Downloads 13820792 Changing MBA Identities: Using Critical Reflection inside and out in Finding a New Narrative
Authors: Keith Schofield, Leigh Morland
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Storytelling is an established means of leadership and management development and is also considered a form of leadership of self and others in its own right. This study focuses on the utility of storytelling in the development of management narratives in an MBA programme; sources include programme participants as well as international recruiters, whose voices are often only heard in terms of economic contribution and globalisation. For many MBA candidates, the return to study requires the development of a new identity which complements their professional identity; each candidate has their own journey and expectations, the use of story can enable candidates to explore their aspirations and assumptions and give voice to previously unspoken ideas. For international recruitment, the story of market development and change must be captured if MBAs are to remain fit for purpose. If used effectively, story acts as a form of critical reflection that can inform the learning journeys of individuals, emerging identities as well as the ongoing design and development of programmes. The landscape of management education is shifting; the MBA begins to attract a different kind of candidate, some are younger than before, others are seeking validation for their existing work practices, yet more are entrepreneurial and wish to capitalise on an institutional experience to further their career. There is a shift in context, creating uncertainty and ambiguity for programme managers and recruiters, thus requiring institutions to create a new MBA narrative. This study utilises Lego SeriousPlay as the means to engaging programme participants and international agents in telling the story of their MBA. We asked MBA participants to tell the story of their leadership and management aspirations and compare these to stories of their development journeys, allowing for critical reflection of their respective development gaps. We asked international recruiters, who act as university agents and promote courses in the student’s country of origin, to explore their mental models of MBA candidates and their learning agenda. The purpose of this process was to explore the agent’s perception of the MBA programme and to articulate the student journey from a recruitment perspective. The paper’s unique contribution is in combining these stories in order to explore the assumptions that determine programme design. Data drawn from reflective statements together with images of Lego ‘builds’ created the opportunity for reflection between the mental models of these groups. Findings will inform the design of the MBA journey and experience; we review the extent to which the changing identities of learners are congruent with programme design. Data from international recruiters also determines the extent to which marketing and recruitment strategies identify with would be candidates.Keywords: critical reflection, programme management, recruitment, storytelling
Procedia PDF Downloads 22620791 A Study of Permission-Based Malware Detection Using Machine Learning
Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud
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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.Keywords: android malware detection, machine learning, malware, malware analysis
Procedia PDF Downloads 16920790 Towards a Measuring Tool to Encourage Knowledge Sharing in Emerging Knowledge Organizations: The Who, the What and the How
Authors: Rachel Barker
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The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.Keywords: innovation, intellectual capital, knowledge sharing, performance measures
Procedia PDF Downloads 19520789 Importance of an E-Learning Program in Stress Field for Postgraduate Courses of Doctors
Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau
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Background: Preparing in the stress field (SF) is, increasingly, a concern for doctors of different specialties. Aims: The aim was to evaluate the importance of an e-learning program for doctors postgraduate courses, in SF. Methods: Doctors (n= 40 male, 40 female) of different specialties and ages (31-71 years), who attended postgraduate courses in SF, voluntarily responded to a questionnaire that included the following themes: Importance of SF courses for specialty practiced by each respondent doctor (using visual analogue scale, VAS); What SF themes would be indicated as e-learning (EL); Preferred form of SF information assimilation: Classical lectures (CL), EL or a combination of these methods (CL+EL); Which information on the SF course are facilitated by EL model versus CL; In their view which are the first four advantages and the first four disadvantages of EL compared to CL, for SF. Results: To most respondents, the SF courses are important for the specialty they practiced (VAS by an average of 4). The SF themes suggested to be done as EL were: Stress mechanisms; stress factor models for different medical specialties; stress assessment methods; primary stress management methods for different specialties. Preferred form of information assimilation was CL+EL. Aspects of the course facilitated by EL versus CL model: Active reading of theoretical information, with fast access to keywords details; watching documentaries in everyone's favorite order; practice through tests and the rapid control of results. The first four EL advantages, mentioned for SF were: Autonomy in managing the time allocated to the study; saving time for traveling to the venue; the ability to read information in various contexts of time and space; communication with colleagues, in good times for everyone. The first three EL disadvantages, mentioned for SF were: It decreases capabilities for group discussion and mobilization for active participation; EL information accession may depend on electrical source or/and Internet; learning slowdown can appear, by temptation of postponing the implementation. Answering questions was partially influenced by the respondent's age and genre. Conclusions: 1) Post-graduate courses in SF are of interest to doctors of different specialties. 2) The majority of participating doctors preferred EL, but combined with CL (CL+EL). 3) Preference for EL was manifested mainly by young or middle age men doctors. 4) It is important to balance the proper formula for chosen EL, to be the most efficient, interesting, useful and agreeable.Keywords: stress field, doctors’ postgraduate courses, classical lectures, e-learning lecture
Procedia PDF Downloads 23820788 A Relational Data Base for Radiation Therapy
Authors: Raffaele Danilo Esposito, Domingo Planes Meseguer, Maria Del Pilar Dorado Rodriguez
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As far as we know, it is still unavailable a commercial solution which would allow to manage, openly and configurable up to user needs, the huge amount of data generated in a modern Radiation Oncology Department. Currently, available information management systems are mainly focused on Record & Verify and clinical data, and only to a small extent on physical data. Thus, results in a partial and limited use of the actually available information. In the present work we describe the implementation at our department of a centralized information management system based on a web server. Our system manages both information generated during patient planning and treatment, and information of general interest for the whole department (i.e. treatment protocols, quality assurance protocols etc.). Our objective it to be able to analyze in a simple and efficient way all the available data and thus to obtain quantitative evaluations of our treatments. This would allow us to improve our work flow and protocols. To this end we have implemented a relational data base which would allow us to use in a practical and efficient way all the available information. As always we only use license free software.Keywords: information management system, radiation oncology, medical physics, free software
Procedia PDF Downloads 24220787 Adopting a Systematically Planned Humour Pedagogical Approach to Increase Student Engagement in Higher Education
Authors: Rita Gill Singh, Alex Chun Koon, Cindy Sing Bik Ngai, Joanna Wen Ying Ho, Mei Li Khong, Enoch Chan, Terrence Lau
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Although humour is viewed as a beneficial element in teaching, there has been little attempt to systematize humour in teaching, possibly because it is difficult to teach someone to be humorous. This study integrated planned humour pedagogical approach into teaching and learning activities and examined the effect of systematically planned humour on students’ engagement and learning in different courses. Specifically, appropriate types of humour (i.e. analogy, absurdity and wordplay) and incorporation methods and frequency were systematically integrated into the lessons of courses at some higher education institutions in Hong Kong. The results showed that the planned humour pedagogical approach increased student engagement, as well as enhanced learning and motivation while reducing students’ stress. The pedagogical implications of this study will be useful for researchers, practitioners, and educators.Keywords: higher education, pedagogy, humour, student engagement, learning, motivation
Procedia PDF Downloads 6220786 How Natural Environments Are Being Used by Teachers to Improve Student Learning and Wellbeing in Australia
Authors: Jade Fersterer, Tristan Snell, Mark Rickinson
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This paper is designed to provide a review of the literature concerning the impact of natural environments on student learning and wellbeing in Australia. Specific areas of interest include how child-led and teacher-led pedagogies differ in outdoor learning settings, and the impact of each approach on children’s well-being, behavior, relationships with others as well as educational outcomes. The review will include links to possibilities for future research, including a Ph.D. currently being undertaken in Australia, which aims to fulfill a considerable gap in psychological, educational and outdoor learning research, regarding how natural environments are being used by teachers to improve learning and wellbeing among primary school students. The proposed study aims to understand if children’s experience of learning, 1. in a natural environment, and 2. in a child-led way, can support and strengthen their skills across several areas of development, including those required for positive educational outcomes. Data will be collected from a sample of primary school students and teachers via both quantitative and qualitative methods, including a pre- and post-questionnaire, direct observation, and semi-structured interviews. The study will have valuable implications for the provision of quality education as well as the promotion of good health and wellbeing. The implications of the research will be useful not only for teachers and parents but also for Psychologists working with children and young people in both a school and clinical setting. Understanding the impacts and implications of child-led learning and exposure to natural environments provides the opportunity to build on the current school curriculum. The inclusion of child-led experiences in nature may provide a simple way to build enthusiasm for school and learning, cultivating skills for life and relationships as well as meeting current curriculum requirements and building capacity for ongoing academic pursuits. In addition, understanding the impact of learning in a natural environment on wellbeing will assist in the development and dissemination of an educational model that could help mitigate the negative health outcomes associated with reduced physical activity and decreasing contact with nature among children.Keywords: child-led learning, educational outcomes, natural environments, wellbeing
Procedia PDF Downloads 12520785 The Change in Management Accounting from an Institutional Perspective: A Case Study for a Romania Company
Authors: Gabriel Jinga, Madalina Dumitru
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The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalization of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modeled by the contingencies specific to this company (e.g. environment, industry, strategy).Keywords: management accounting, change, Romania, contingency, institutional theory
Procedia PDF Downloads 51620784 Development of Mechanisms of Value Creation and Risk Management Organization in the Conditions of Transformation of the Economy of Russia
Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Eugenia V. Klicheva
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In modern conditions, scientific judgment of problems in developing mechanisms of value creation and risk management acquires special relevance. Formation of economic knowledge has resulted in the constant analysis of consumer behavior for all players from national and world markets. Effective mechanisms development of the demand analysis, crucial for consumer's characteristics of future production, and the risks connected with the development of this production are the main objectives of control systems in modern conditions. The modern period of economic development is characterized by a high level of globalization of business and rigidity of competition. At the same time, the considerable share of new products and services costs has a non-material intellectual nature. The most successful in Russia is the contemporary development of small innovative firms. Such firms, through their unique technologies and new approaches to process management, which form the basis of their intellectual capital, can show flexibility and succeed in the market. As a rule, such enterprises should have very variable structure excluding the tough scheme of submission and demanding essentially new incentives for inclusion of personnel in innovative activity. Realization of similar structures, as well as a new approach to management, can be constructed based on value-oriented management which is directed to gradual change of consciousness of personnel and formation from groups of adherents included in the solution of the general innovative tasks. At the same time, valuable changes can gradually capture not only innovative firm staff, but also the structure of its corporate partners. Introduction of new technologies is the significant factor contributing to the development of new valuable imperatives and acceleration of the changing values systems of the organization. It relates to the fact that new technologies change the internal environment of the organization in a way that the old system of values becomes inefficient in new conditions. Introduction of new technologies often demands change in the structure of employee’s interaction and training in their new principles of work. During the introduction of new technologies and the accompanying change in the value system, the structure of the management of the values of the organization is changing. This is due to the need to attract more staff to justify and consolidate the new value system and bring their view into the motivational potential of the new value system of the organization.Keywords: value, risk, creation, problems, organization
Procedia PDF Downloads 28420783 An Algorithm to Compute the State Estimation of a Bilinear Dynamical Systems
Authors: Abdullah Eqal Al Mazrooei
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In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization
Procedia PDF Downloads 48620782 Development and Adaptation of a LGBM Machine Learning Model, with a Suitable Concept Drift Detection and Adaptation Technique, for Barcelona Household Electric Load Forecasting During Covid-19 Pandemic Periods (Pre-Pandemic and Strict Lockdown)
Authors: Eric Pla Erra, Mariana Jimenez Martinez
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While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)
Procedia PDF Downloads 10520781 Voices and Pictures from an Online Course and a Face to Face Course
Authors: Eti Gilad, Shosh Millet
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In light of the technological development and its introduction into the field of education, an online course was designed in parallel to the 'conventional' course for teaching the ''Qualitative Research Methods''. This course aimed to characterize learning-teaching processes in a 'Qualitative Research Methods' course studied in two different frameworks. Moreover its objective was to explore the difference between the culture of a physical learning environment and that of online learning. The research monitored four learner groups, a total of 72 students, for two years, two groups from the two course frameworks each year. The courses were obligatory for M.Ed. students at an academic college of education and were given by one female-lecturer. The research was conducted in the qualitative method as a case study in order to attain insights about occurrences in the actual contexts and sites in which they transpire. The research tools were open-ended questionnaire and reflections in the form of vignettes (meaningful short pictures) to all students as well as an interview with the lecturer. The tools facilitated not only triangulation but also collecting data consisting of voices and pictures of teaching and learning. The most prominent findings are: differences between the two courses in the change features of the learning environment culture for the acquisition of contents and qualitative research tools. They were manifested by teaching methods, illustration aids, lecturer's profile and students' profile.Keywords: face to face course, online course, qualitative research, vignettes
Procedia PDF Downloads 41820780 Graphic Animation: Innovative Language Learning for Autistic Children
Authors: Norfishah Mat Rabi, Rosma Osman, Norziana Mat Rabi
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It is difficult for autistic children to mix with and be around with other people. Language difficulties are a problem that affects their social life. A lack of knowledge and ability in language are factors that greatly influence their behavior, and their ability to communicate and interact. Autistic children need to be assisted to improve their language abilities through the use of suitable learning resources. This study is conducted to identify weather graphic animation resources can help autistic children learn and use transitive verbs more effectively. The study was conducted in a rural secondary school in Penang, Malaysia. The research subject comprised of three autistic students ranging in age from 14 years to 16 years. The 14-year-old student is placed in A Class and two 16-year-old students placed in B Class. The class placement of the subjects is based on the diagnostic test results conducted by the teacher and not based on age. Data collection is done through observation and interviews for the duration of five weeks; with the researcher allocating 30 minutes for every learning activity carried out. The research finding shows that the subjects learn transitive verbs better using graphic animation compared to static pictures. It is hoped that this study will give a new perspective towards the learning processes of autistic children.Keywords: graphic animation, autistic children, language learning, teaching
Procedia PDF Downloads 27620779 Examining Audiology Students: Clinical Reasoning Skills When Using Virtual Audiology Cases Aided With no Collaboration, Live Collaboration, and Virtual Collaboration
Authors: Ramy Shaaban
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The purpose of this study was to examine the difference in clinical reasoning skills of students when using virtual audiology cases with and without collaborative assistance from major learning approaches important to clinical reasoning skills and computer-based learning models: Situated Learning Theory, Social Development Theory, Scaffolding, and Collaborative Learning. A quasi-experimental design was conducted at two United States universities to examine whether there is a significant difference in clinical reasoning skills between three treatment groups using IUP Audiosim software. Two computer-based audiology case simulations were developed, and participants were randomly placed into the three groups: no collaboration, virtual collaboration, and live collaboration. The clinical reasoning data were analyzed using One-Way ANOVA and Tukey posthoc analyses. The results show that there was a significant difference in clinical reasoning skills between the three treatment groups. The score obtained by the no collaboration group was significantly less than the scores obtained by the virtual and live collaboration groups. Collaboration, whether virtual or in person, has a positive effect on students’ clinical reasoning. These results with audiology students indicate that combining collaboration models with scaffolding and embedding situated learning and social development theories into the design of future virtual patients has the potential to improve students’ clinical reasoning skills.Keywords: clinical reasoning, virtual patients, collaborative learning, scaffolding
Procedia PDF Downloads 21420778 Identifying the Level of Awareness on Value Management Practice amongst Construction Practitioners in Nigeria
Authors: Alhassan Dahiru
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Value management is widely accepted technique of eliminating unnecessary cost at different stages of project development that maximizes the functional value of a project by managing its evolution and development from concept to completion. Many construction industry practitioners are not aware of Value Management practice, and its use is less widespread in Nigeria. The aim of this research is to identify the level of awareness on value management practice amongst construction practitioners with a view to contribute to the improvement of the implementation of value management practice in the Nigerian construction industry. In this study, construction practitioners have been chosen as respondents from the 6 geopolitical zones of the federation including FCT Abuja. Through the survey, a total number of 360 semi-structured questionnaires were administered and 284 were returned and remained good for the analysis. The results indicate that most of the respondents were aware of the value management concept and issues surrounding construction industry in Nigeria, while about 32% of the respondents were not aware of its potential benefits. Therefore, organisations should review their techniques and processes from time to time for improvement on effective service delivery. Additionally, a change management strategy should also be part of every organization to ease the introduction of new techniques such as value management. There is also the need for more value management training workshops and seminars in order to enlighten the participants of the construction industry on the principles, concept, and techniques involved in the value management process.Keywords: sustainability, value management, construction practitioners, Nigeria
Procedia PDF Downloads 23120777 A Comparison between Virtual Case-Based Learning and Traditional Learning: The Effect on Undergraduate Nursing Students’ Performance during Covid-19: A Pilot Study
Authors: Aya M. Aboudesouky
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Covid-19 has changed and affected the whole world dramatically in a new way that the entire world, even scientists, have not imagined before. The educational institutions around the world have been fighting since Covid-19 hit the world last December to keep the educational process unchanged for all students. E-learning was a must for almost all US universities during the pandemic. It was specifically more challenging to use online case-based learning instead of regular classes among nursing students who take practical education. This study aims to examine the difference in performance and satisfaction between nursing students taking traditional education and those who take virtual case-based education during their practical study. This study enrolls 40 last-year nursing undergraduates from a mid-sized university in Western Pennsylvania. The study uses a convenient sample. Students will be divided into two groups; a control group that is exposed to traditional teaching strategy and a treatment group that is exposed to a case-based teaching strategy. The module designed for this study is a total parenteral nutrition (TPN) module that will be taught for one month. The treatment group (n=20) utilizes the virtual simulation of the CBL method, while the control group (n=20) uses the traditional lecture-based teaching method. Student evaluations are collected after a month by using the survey to attain the students’ learning satisfaction and self-evaluation of the course. The post-test is used to assess the end of the course performance.Keywords: virtual case-based learning, traditional education, nursing education, Covid-19 crisis, online practical education
Procedia PDF Downloads 12820776 Latitudinal Patterns of Pre-industrial Human Cultural Diversity and Societal Complexity
Authors: Xin Chen
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Pre-industrial old-world human cultural diversity and societal complexity exhibits remarkable geographic regularities. Along the latitudinal axis from the equator to the arctic, a descending trend of human ethno-cultural diversity is found to be in coincidence with a descending trend of biological diversity. Along the same latitudinal axis, the pre-industrial human societal complexity shows to peak at the intermediate latitude. It is postulated that human cultural diversity and societal complexity are strongly influenced by collective learning, and that collective learning is positively related to human population size, social interactions, and environmental challenges. Under such postulations the relationship between collective learning and important geographical-environmental factors, including climate and biodiversity/bio-productivity is examined. A hypothesis of intermediate bio-productivity is formulated to account for those latitudinal patterns of pre-industrial human societal complexity.Keywords: cultural diversity, soetal complexity, latitudinal patterns, biodiversity, bio-productivity, collective learning
Procedia PDF Downloads 7920775 Machine Learning-Enabled Classification of Climbing Using Small Data
Authors: Nicholas Milburn, Yu Liang, Dalei Wu
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Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence
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