Search results for: life- long learning

Authors: Wanwadee Neamsakul

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VARK learning style is an effective method of learning that could enhance all skills of the students like visual (V), auditory (A), read/write (R), and kinesthetic (K). This learning style benefits the students in terms of professional competencies, critical thinking and lifelong learning which are the desirable characteristics of the nursing students. This study aimed to develop a model of teaching and learning clinical practicum at postpartum ward for nursing students by using VARK learning styles, and evaluate the nursing students’ opinions about the developmental model. A methodology used for this study was research and development (R&D). The model was developed by focus group discussion with five obstetric nursing instructors who have experiences teaching Maternal Newborn and Midwifery I subject. The activities related to practices in the postpartum (PP) ward including all skills of VARK were assigned into the matrix table. The researcher asked the experts to supervise the model and adjusted the model following the supervision. Subsequently, it was brought to be tried out with the nursing students who practiced on the PP ward. Thirty third year nursing students from one of the northern Nursing Colleges, Academic year 2015 were purposive sampling. The opinions about the satisfaction of the model were collected using a questionnaire which was tested for its validity and reliability. Data were analyzed using descriptive statistics. The developed model composed of 27 activities. Seven activities were developed as enhancement of visual skills for the nursing students (25.93%), five activities as auditory skills (18.52%), six activities as read and write skills (22.22%), and nine activities as kinesthetic skills (33.33%). Overall opinions about the model were reported at the highest level of average satisfaction (mean=4.63, S.D=0.45). In the aspects of visual skill (mean=4.80, S.D=0.45) was reported at the highest level of average satisfaction followed by auditory skill (mean=4.62, S.D=0.43), read and write skill (mean=4.57, S.D=0.46), and kinesthetic skill (mean=4.53, S.D=0.45) which were reported at the highest level of average satisfaction, respectively. The nursing students reported that the model could help them employ all of their skills during practicing and taking care of the postpartum women and newborn babies. They could establish self-confidence while providing care and felt proud of themselves by the benefits of the model. It can be said that using VARK learning style to develop the model could enhance both nursing students’ competencies and positive attitude towards the nursing profession. Consequently, they could provide quality care for postpartum women and newborn babies effectively in the long run.

Keywords: model, nursing students, postpartum ward, teaching and learning clinical practicum

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Authors: Prasita Sooksamran, Wareerat Kaewurai

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STEM is an integrated teaching approach promoted by the Ministry of Education in Thailand. STEM Education is an integrated approach to teaching Science, Technology, Engineering, and Mathematics. It has been questioned by Thai teachers on the grounds of how to integrate STEM into the classroom. Therefore, the main objective of this study is to develop a science instructional model based on the STEM approach to enhance scientific mind and problem-solving skills for primary students. This study is participatory action research, and follows the following steps: 1) develop a model 2) seek the advice of experts regarding the teaching model. Developing the instructional model began with the collection and synthesis of information from relevant documents, related research and other sources in order to create prototype instructional model. 2) The examination of the validity and relevance of instructional model by a panel of nine experts. The findings were as follows: 1. The developed instructional model comprised of principles, objective, content, operational procedures and learning evaluation. There were 4 principles: 1) Learning based on the natural curiosity of primary school level children leading to knowledge inquiry, understanding and knowledge construction, 2) Learning based on the interrelation between people and environment, 3) Learning that is based on concrete learning experiences, exploration and the seeking of knowledge, 4) Learning based on the self-construction of knowledge, creativity, innovation and 5) relating their findings to real life and the solving of real-life problems. The objective of this construction model is to enhance scientific mind and problem-solving skills. Children will be evaluated according to their achievements. Lesson content is based on science as a core subject which is integrated with technology and mathematics at grade 6 level according to The Basic Education Core Curriculum 2008 guidelines. The operational procedures consisted of 6 steps: 1) Curiosity 2) Collection of data 3) Collaborative planning 4) Creativity and Innovation 5) Criticism and 6) Communication and Service. The learning evaluation is an authentic assessment based on continuous evaluation of all the material taught. 2. The experts agreed that the Science Instructional Model based on the STEM Education Approach had an excellent level of validity and relevance (4.67 S.D. 0.50).

Keywords: instructional model, STEM education, scientific mind, problem solving

Procedia PDF Downloads 192

Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

Procedia PDF Downloads 48

Authors: W.Appamana, S. Jantasee, P. Siwarasak, T. Mueansichai, C. Kaewbuddee

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Heat transfer is important in chemical engineering field. We have to know how to predict rates of heat transfer in a variety of process situations. Therefore, heat transfer learning is one of the greatest challenges for undergraduate students in chemical engineering. To enhance student learning in classroom, active-learning method was proposed in a single classroom, using problems based on videos and creating video, think-pair-share and jigsaw technique. The result shows that active learning method can prevent copying of the solutions manual for students and improve average examination scores about 5% when comparing with students in traditional section. Overall, this project represents an effective type of class that motivates student-centric learning while enhancing self-motivation, creative thinking and critical analysis among students.

Keywords: active learning, student-created video, self-motivation, creative thinking

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Authors: Okoh Charity N.

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This study investigated the predictive power of preschoolers’ involvement in indoor and outdoor learning activities on their social learning skills in Niger state, Nigeria. Two research questions and two null hypotheses guided the study. Correlational research design was employed in the study. The population of the study consisted of 8,568 Nursery III preschoolers across the 549 preschools in the five Local Education Authorities in Niger State. A sample of 390 preschoolers drawn through multistage sampling procedure. Two instruments; Preschoolers’ Learning Activities Rating Scale (PLARS) and Preschoolers’ Social Learning Skills Rating Scale (PSLSRS) developed by the researcher were used for data collection. The reliability coefficients obtained for the PLARS and PSLSRS were 0.83 and 0.82, respectively. Data collected were analyzed using simple linear regression. Results showed that 37% of preschoolers’ social learning skills are predicted by their involvement in indoor learning activities, which is statistically significant (p < 0.05). It also shows that 11% of preschoolers’ social learning skills are predicted by their involvement in outdoor learning activities, which is statistically significant (p < 0.05). Therefore, it was recommended among others, that government and school administrators should employ qualified teachers who will stand as role models for preschoolers’ social skills development and provide indoor and outdoor activities and materials for preschoolers in schools.

Keywords: preschooler, social learning, indoor activities, outdoor activities

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Authors: Lin Li, Farshad Amini

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The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

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Authors: Elleuch Imen

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In this paper, it propose a new approach for learning Arabic as a foreign language via audio-visual translation, particularly subtitling. The approach consists of developing video sequences appropriate to different levels of learning (from A1 to C2) containing conversations, quizzes, games and others. Each video aims to achieve a specific objective, such as the correct pronunciation of Arabic words, the correct syntactic structuring of Arabic sentences, the recognition of the morphological characteristics of terms and the semantic understanding of statements. The subtitled videos obtained can be incorporated into different Arabic second language learning tools such as Moocs, websites, platforms, etc.

Keywords: arabic foreign language, learning, audio-visuel translation, subtitled videos

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Authors: Suratno

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Metacognition thinking skills should be developed early on in learning. The aim of research builds metacognition thinking skills through collaborative learning with self-evaluation. Approach to action research study involving 32 middle school students in Jember Indonesia. Indicators metacognition skills consist of planning, information management strategies, comprehension monitoring, and debugging strategies. Data were analyzed by t test and analysis of instructional videos. Results of the study here were significant differences in metacognition skills before and after the implementation of collaborative learning with self-evaluation. Analysis instructional video showing the difference artifacts of student learning activities to learning before and after implementation of collaborative learning with self-evaluation. Self-evaluation makes students familiar practice thinking skills metacognition.

Keywords: metacognition, collaborative, evaluation, thinking skills

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

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Authors: Maimuna Nontji

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The life cycle of rice plant has three phases of growth; they are the vegetative, reproductive and maturation phase. They greatly affect the life of dynamics metanotrof bacterial as reducer methane emissions in the rice field, both of population and on the rate of growth. The aim of this study was to analyze the population and growth rate of methanotrof isolates which has been isolated in previous studies. Isolates were taken at all the life cycle of rice plant. Population of analysis was conducted by standard plate count method and growth rate was analysed by logarithmic calculation. The results showed that each isolate varied in population and growth rate. The highest population was obtained in the isolates Gowa Methanotrof Reproductive (GMR 8) about 7.06 x 10 11 cfu / ml on 3 days of incubation and the lowest population was obtained in the Gowa Methanotrof Maturation (GMP 5) about 0.27 x 10 11 cfu / ml on 7 day of incubation. Some isolate were demonstrated in long growth rate about 5 days of incubation and another are 3 days.

Keywords: emission, methanotrof, methane, population

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Stephanie K. Douglas, Gordon R. Haley

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Organizations face increasing disruptions, changes, and uncertainties through the rapid shifts in the economy and business environment. A capacity for resilience is necessary for organizations to survive and thrive in such adverse conditions. Learning is an essential component of an organization's capability for building resilience. Strategic human resource management is a principal component of learning and organizational resilience. To achieve organizational resilience, human resource management strategies must support individual knowledge, skills, and ability development through organizational learning. This study aimed to contribute to the comprehensive knowledge of the relationship between strategic human resource management and organizational learning to build organizational resilience. The organizational learning dimensions of knowledge acquisition, knowledge distribution, knowledge interpretation, and organizational memory can be fostered through human resource management strategies and then aggregated to the organizational level to build resilience.

Keywords: human resource development, human resource management, organizational learning, organizational resilience

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Authors: Prajakta Bhadgaonkar

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Forgiveness is taught since birth in Indian tradition. However, delivering a disabled child is a trauma for the parents. They keep on blaming themselves for the fault, which they are not responsible. Hence, due to lack of forgiving oneself the quality of life of both parent and child gets affected. In forgiveness, person tries to relieve oneself from the feeling of hatred towards oneself or other person. Forgiveness helps move ahead in the life. Hence, one can handle problem more efficiently resulting into better quality of life. In this study, the 30 parents of children with intellectual disability were contacted to find out quality of life. They were administered standardized measure of quality of life (QOL). The children were between 6 to 8 years of age. Out of these 30 parents, 12 parents (7 females and 5 males) were given forgiveness therapy for three months span. After every one month, the QOL scale was administered. At the end of three months, the significant difference was observed in quality of life of parents of children with intellectual disability. Genderwise there was no significant difference between male and female on quality of life.

Keywords: children with intellectual disability, forgiveness, parents, quality of life

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Authors: Djeffal Asma, Zemmouri Noureddine

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In order for building designer to be able to balance environmental concerns with other performance requirements, they need clear and concise information. For certain decisions during the design process, qualitative guidance, such as design checklists or guidelines information may not be sufficient for evaluating the environmental benefits between different building materials, products and designs. In this case, quantitative information, such as that generated through a life cycle assessment, provides the most value. LCA provides a systematic approach to evaluating the environmental impacts of a product or system over its entire life. In the case of buildings life cycle includes the extraction of raw materials, manufacturing, transporting and installing building components or products, operating and maintaining the building. By integrating LCA into building design process, designers can evaluate the life cycle impacts of building design, materials, components and systems and choose the combinations that reduce the building life cycle environmental impact. This article attempts to give an overview of the integration of LCA methodology in the context of building design, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. A multiple case study was conducted in order to assess the benefits of the LCA as a decision making aid tool during the first stages of the building design under specific climate conditions of the North East region of Algeria. It is clear that the LCA methodology can help to assess and reduce the impact of a building design and components on the environment even if the process implementation is rather long and complicated and lacks of global approach including human factors. It is also demonstrated that using LCA as a multi objective optimization of building process will certainly facilitates the improvement in design and decision making for both new design and retrofit projects.

Keywords: life cycle assessment, buildings, sustainability, elementary schools, environmental impacts

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

Procedia PDF Downloads 271

Authors: Horng-Jyh Chen, Yi-Fang Chen, Chien-Liang Lin

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In this paper, the authors try to investigate the determinants of behavioral intention of the blended e-learning course for senior students at the Active Ageing University in Taiwan. Due to lower proficiency in the use of computers and less experience on learning styles of the blended e-learning course for senior students will be expected quite different from those for most young students. After more than five weeks course for two years the questionnaire survey is executed to collect data for statistical analysis in order to understand the determinants of the behavioral intention for senior students. The object of this study is at one of the Active Ageing University in Taiwan total of 84 senior students in the blended e-learning for the ceramics teaching course. The research results show that only the perceived usefulness of the blended e-learning course has significant positive relationship with the behavioral intention.

Keywords: Active Aging University, blended e-learning, ceramics teaching course, behavioral intention

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Qingyu Zhang, Mei Cao

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As the environments become increasingly uncertain, firms have attempted to achieve greater supply chain collaboration. Supply chain collaboration can generate significant benefits to its members, e.g., reducing risks and decreasing transaction costs. However, a strong relationship is often related to firm’s culture (e.g., short-term vs. long-term interests). The objective of the study is to explore the effect of long-term oriented culture on product quality in a supply chain. Data was collected through a Web survey of U.S. manufacturing firms. Structural equation modeling (LISREL) was used to analyze the data. The results support the mediating roles of goal congruence and communication in the relationship between long-term orientation and product quality in the supply chain. Goal congruence partially mediates the relationship between long-term orientation and communication; communication completely mediates the relationship between goal congruence and product quality. Without high levels of communication, goal congruence cannot improve product quality in a positive way.

Keywords: communication, long-term orientation, product quality, supply chain

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Authors: Thi Chang Duyen Can

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Althoughthe COVID-19 epidemic is under control, online education technology in Vietnam will still thrive in the learner-centered trend. Most of the Vietnamese students are now ready to familiarize themselves with and access to online learning. Even in some cases, online learning, if combined with new tools, is far more effective and exciting for students than some traditional instruction. However, little research has been conducted to explore Vietnamese teachers’ difficulties in moderating learner-centered E-learning. Therefore, the study employed the mixed method (n=9) to (i) uncover the challenges faced by Vietnamese teachers in English language online classes using learner-centred approach and (ii) propose the recommendations to improve the quality of online training in universities.

Keywords: learner-centered e-learning, english language classes, teachers' challenges, online learning

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Raminder Kaur

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This paper considers the emerging area of integrating Virtual Reality (VR) technologies into the teaching of Visual Anthropology, Research Methods, and the Anthropology of Contemporary India in the University of Sussex. If deployed in a critical and self-reflexive manner, there are several advantages to VR-based immersive learning: (i) Based on data available for British schools, it has been noted that ‘Learning through experience can boost knowledge retention by up to 75%’. (ii) It can tutor students to learn with and from virtual worlds, devising new collaborative methods where suited. (iii) It can foster inclusive learning by aiding students with SEN and disabilities who may not be able to explore such areas in the physical world. (iv) It can inspire and instill confidence in students with anxieties about approaching new subjects, realms, or regions. (v) It augments our provision of ‘smart classrooms’ synchronised to the kinds of emerging immersive learning environments that students come from in schools.

Keywords: virtual reality, anthropology, immersive learning, university

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Authors: Glenn A. Palmer, Lorenzo Bowman, Juanita Johnson-Bailey

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The ubiquitous economic upheaval that has gripped the global environment in the past few years displaced many workers through unemployment or underemployment. Globally, this disruption has caused many adult workers to seek additional education or skills to remain competitive, and acquire the ability and options to find gainful employment. While many learners have availed themselves of some opportunities to be retrained and retooled at locations within their communities, others have explored those options through the online learning environment. This paper examines the empirical research that explores the various strategies that are used in the adult online learning community that could also foster transformative learning.

Keywords: online learning, transformational learning, adult education, economic crisis, unemployment

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Authors: Radovan Cobanovic, Milica Rankov-Sicar

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The fresh cake is in the group of perishable food which cannot be kept a long period of time. The study of sustainability has been done in order to extend the shelf-life of the product which was 10 days. According to the plan of sustainability, it was defined that 5 samples had to be stored for 20 days at max +8°C and analyzed every 5th day from the day of reception until the 20th day. The shelf life of cake has expired during the study of sustainability in the period between 10th and 20th day of analyses. Cake samples were subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analysis (Listeria monocytogenes, Salmonella spp. and Enterobacteriaceae) according to Serbian state regulation. All analysis were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11290-1, Salmonella spp ISO 6579, and Enterobacteriaceae ISO 21258-2. Analyses showed that after ten days of storage at a temperature defined by the manufacturers and within the product's shelf life, the cake did not have any noticeable changes in sensory characteristics. Smell and taste are unaffected there was no presence of strange smell or taste. As far as microbiological analyses are concerned, neither one pathogen was detected and number of Enterobacteriaceae was at level less than 102 cfu/g. After expiry of shelf life in a period of 15th and 20th day of storage, the sensory analysis showed the presence of strange sour-milky smell and rancid taste. Concerning microbiological analyses, there still were not positive results for pathogen microorganisms but the number of Enterobacteriaceae was at level more than 103cfu/g. Reviewing the results of sensory analysis indicates that it is not recommended to extend the shelf-life of the product comparing to the already defined shelf-life because occurred changes may adversely affect the consumer desire for the choice of this product.

Keywords: confectionary product, extension of shelf life, sensory and microbiological analyses, sustainability

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

Abstract:

Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

Procedia PDF Downloads 96

Authors: Min Bao

Abstract:

The teacher is at the core of the three fundamental factors in international Chinese language teaching, the other two being the textbook and the method. Professional development of the teacher comprises a self-renewing process that is characterized by knowledge impartment and self-reflection, in which individual agency plays a significant role. Agency makes a positive contribution to teachers’ teaching practice and their life-long learning. This study, taking Chinese teaching and learning in Minsk State Linguistic University of Belarus as an example, attempts to understand agency by investigating the teacher’s strategic adaptation of textbooks to meet local needs. Firstly, through in-depth interviews, teachers’ comments on textbooks are collected and analyzed to disclose their strategies of adapting and localizing textbooks. Then, drawing on the theory of 'The chordal triad of agency', the paper reveals the process in which teacher agency is exercised as well as its rationale. The results verify the theory, that is, given its temporal relationality, teacher agency is constructed through a combination of experiences, purposes and aims, and context, i.e., projectivity, iteration and practice-evaluation as mentioned in the theory. Evidence also suggests that the three dimensions effect differently; It is usually one or two dimensions that are of greater effects on the construction of teacher agency. Finally, the paper provides four specific insights to teacher development in international Chinese language teaching: 1) when recruiting teachers, priority be given on candidates majoring in Chinese language or international Chinese language teaching; 2) measures be taken to assure educational quality of the two said majors at various levels; 3) pre-service teacher training program be tailored for improved quality, and 4) management of overseas Confucius Institutions be enhanced.

Keywords: international Chinese language teaching, teacher agency, textbooks, localization

Procedia PDF Downloads 156

Authors: Anna-Maria Saarela

Abstract:

At the Savonia University of Applied Sciences (UAS), curriculum and studies have been improved by applying an Open Innovation Space approach (OIS). It is based on multidisciplinary action learning. The key elements of OIS-ideology are work-life orientation, and student-centric communal learning. In this approach, every participant can learn from each other and innovations will be created. In this social innovation educational approach, all practices are carried out in close collaboration with enterprises in real-life settings, not in classrooms. As an example, in this paper, Savonia UAS’s Future Food RDI hub (FF) shows how OIS practices are implemented by providing food product development and consumer research services for enterprises in close collaboration with academicians, students and consumers. In particular one example of OIS experimentation in the field is provided by a consumer research carried out utilizing verbal analysis protocol combined with audio-visual observation (VAP-WAVO). In this case, all co-learners were acting together in supermarket settings to collect the relevant data for a product development and the marketing department of a company. The company benefitted from the results obtained, students were more satisfied with their studies, educators and academicians were able to obtain good evidence for further collaboration as well as renewing curriculum contents based on the requirements of working life. In addition, society will benefit over time as young university adults find careers more easily through their OIS related food science studies. Also this knowledge interaction model re-news education practices and brings working-life closer to educational research institutes.

Keywords: collaboration, education, food science, industry, knowledge transfer, RDI, student

Procedia PDF Downloads 373