Search results for: repetitive learning method

Authors: Konstantinos Sofianos, Michail Stefanidakis

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Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Jawairia Rasheed

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Modern robots are often used for search and rescue purpose. One of the key areas of interest in such cases is learning complex environments. One of the key methodologies for robots in such cases is reinforcement learning. In reinforcement learning robots learn to move the path to reach the goal while avoiding obstacles. Q-learning, one of the most advancement of reinforcement learning is used for making the robots to learn the path. Robots learn by interacting with the environment to reach the goal. In this paper simulation model of bee-like robots is implemented in NETLOGO. In the start the learning rate was less and it increased with the passage of time. The bees successfully learned to reach the goal while avoiding obstacles through Q-learning technique.

Keywords: reinforlearning of bee like robots for reaching the goalcement learning for randomly placed obstacles, obstacle avoidance through q-learning, q-learning for obstacle avoidance,

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Kamal Heidari

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Covid-19 has borne drastic effects on different areas of society, including the education area, in that it brought virtual education to the center of attention, as an alternative to in-person education. In virtual education, the importance of flipped learning doubles, as students are supposed to take the main responsibility of teaching/learning process; and teachers play merely a facilitative/monitoring role. Given the students’ responsibility in virtual flipped learning, students’ motivation plays a pivotal role in the effectiveness of this learning method. The L2 Motivational Self-System (L2MSS) model is a currently proposed model elaborating on students’ motivation based on three sub-components: ideal L2 self, ought-to L2 self, and L2 learning experience. Drawing on an exploratory sequential mixed-methods research design, this study probed the effect of virtual flipped learning (via SHAD platform) on 112 gifted and non-gifted students’ motivation based on the L2 MSS. This study uncovered that notwithstanding the point that virtual flipped learning improved both gifted and non-gifted students’ motivation, it differentially affected their motivation. In other words, gifted students mostly referred to ideal L2 self, while non-gifted ones referred to ought-to L2 self and L2 learning experience aspects of motivation.

Keywords: virtual flipped learning, giftedness, motivation, L2MSS

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Authors: Henry R. Troy

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Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.

Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning

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Authors: Shahbaz Ahmed

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This study is conducted to demonstrate the knowledge of intentional learning and incidental learning. Hypothesis of this experiment is intentional learning is better than incidental learning, participants were demonstrated and were asked to learn the 10 nonsense syllables in a specific sequence from the colored cards in the end they were asked to recall the background color of each card instead of nonsense syllables. Independent variables of the experiment are the colored cards containing nonsense syllables which are to be memorized by the participants, dependent variables are the number of correct responses made by the participant. The findings of the experiment concluded that intentional learning is better than incidental learning, hence hypothesis is proved.

Keywords: intentional learning, incidental learning, non-sense syllable cards, score sheets

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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

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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: Jian Qu, Akira Shimazu

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OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%.

Keywords: information retrieval, definition retrieval, OOV (out of vocabulary), biomedical information retrieval

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Authors: Jatuphum Ketchatturat

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The objective of this research was to study the learning and innovation skills of undergraduate students after Research-Based Learning had been applied. Eighty research participants were selected from undergraduate students enrolled in Educational Research Program using the Purposive Sampling Method. Research Methodology was Descriptive Research, the research took one semester to complete. The research instruments consisted of (1) Research Skill Assessment Form, (2) Research Quality Assessment Form, (3) Scale of learning and innovation skills 25 items. The quantitative data were analysed using descriptive statistics including, frequency, percentage, average and standard deviation. The qualitative data were analyzed using content analysis. The research results were (1) The students were able to conduct research that focused on educational research, which has a fair to the excellent level of standards of a research learning outcome, research skills, and research quality. The student’s learning and innovation skills have relating to research skills and research quality. (2) The findings found that the students have been developed to be learning and innovation skills such as systematic thinking, analytical thinking, critical thinking, creative problem solving, collaborative, research-creation, communication, and knowledge and experience sharing to friends, community and society.

Keywords: learning and innovation skills, research based learning, research skills, undergraduate students

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Authors: Ya-Hui Lee, Ching-Yi Lu

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Taiwan will become an aging society in 2018. The method to face the challenges related to the aging population has become an important topic. Purpose: This study aims to understand the future preparation of middle-age and older adults, and how they prepared themselves to face the problems of aging, and how they took actions to plan and cope with their future life. Moreover, how did they generate the process of learning action, so that they would be able to live a more active and meaningful life when they entered into their older age? Method: We conducted semi-structure interviews with 10 middle-aged and older adults who had taken actions to prepare for their future. We examined the interviewees’ consciousness and learning actions in their future preparation. Preliminary Results: 1. The triggering factors of the interviewees’ consciousness to prepare for the future included: family events, the desire to maintain active social lives after retirement, the continuation of the interviewees’ professional careers after retirement, and the aspiration for participation in volunteer services. 2. 'Health problems' and 'economic security' were issued of the utmost concern for the interviewees’ future. However, they would transform these worries to learning actions, comprising of active participation in learning, finding relevant information through learning; thus, accumulating more resources to cope with their future needs.

Keywords: middle-age and older adults, preparing for future, older adult learning

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Authors: Leidy M. Aldana, Jorge E. Camargo

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Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

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Authors: Shimaa Nagro, Russell Campion

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Mobile devices are becoming ever more widely available, with growing functionality, and are increasingly used as an enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material user interfaces for mobile devices is beset by many unresolved research issues such as those arising from emphasising the information concepts then mapping this information to appropriate media (modelling information then mapping media effectively). This report describes a multimedia user interface design method for mobile learning. The method covers specification of user requirements and information architecture, media selection to represent the information content, design for directing attention to important information, and interaction design to enhance user engagement based on Human-Computer Interaction design strategies (HCI). The method will be evaluated by three different case studies to prove the method is suitable for application to different areas / applications, these are; an application to teach about major computer networking concepts, an application to deliver a history-based topic; (after these case studies have been completed, the method will be revised to remove deficiencies and then used to develop a third case study), an application to teach mathematical principles. At this point, the method will again be revised into its final format. A usability evaluation will be carried out to measure the usefulness and effectiveness of the method. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the MDMLM method. The researcher has successfully produced the method at this point which is now under validation and testing procedures. From this point forward in the report, the researcher will refer to the method using the MDMLM abbreviation which means Multimedia Design Mobile Learning Method.

Keywords: human-computer interaction, interface design, mobile learning, education

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Authors: Dingyang Hu, Dan Liu

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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: Z. Karakus, Z. Ozer

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Nurses are responsible for the care and treatment of individuals, as well as health maintenance and education. Medication administration is an important part of health promotion. The administration of a medicine is a common but important clinical procedure for nurses because of its complex structure. Therefore, medication errors are inevitable for nurses or nursing students. Medication errors can cause ineffective treatment, patient’s prolonged hospital stay, disablement, or death. Additionally, medication errors affect the global economy adversely by increasing health costs. Hence, preventing or decreasing of medication errors is a critical and essential issue in nursing. Nurse educators are in pursuit of new teaching methods to teach students significance of medication application. In the light of technological developments of this age, e-learning has started to be accepted as an important teaching method. E-learning is the use of electronic media and information and communication technologies in education. It has advantages such as flexibility of time and place, lower costs, faster delivery, and lower environmental impact. Students can make their own schedule and decide the learning method. This study is conducted to determine the impact of e-learning on medication administration of nursing students.

Keywords: e-learning, medication administration, nursing, nursing students

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Authors: Abdelghani Boudiaf

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The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Keywords: changing mentalities, continuing training, organizational learning, quality management system, skills development

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Authors: Rachael Olubukola Afolabi

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Immersive technologies known as X Reality or Cross Reality that include virtual reality augmented reality, and mixed reality have pervaded into the education system at different levels from elementary school to adult learning. Instructors, instructional designers, and learning experience specialists continue to find new ways to engage students in the learning process using technology. While the progression of web technologies has enhanced digital learning experiences, analytics on learning outcomes continue to be explored to determine the relevance of these technologies in learning. Digital learning has evolved from web 1.0 (static) to 4.0 (dynamic and interactive), and this evolution of technologies has also advanced teaching methods and approaches. This paper explores how these technologies are being utilized in learning and the results that educators and learners have identified as effective learning opportunities and approaches.

Keywords: immersive technologoes, virtual reality, augmented reality, technology in learning

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Authors: Naoki Okamura

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From a perspective of moral education, this study has examined the experiences of a group of college students who volunteered in disaster areas after the magnitude 9.0 Earthquake, which struck the Northeastern region of Japan in March, 2011. The research, utilizing the method of grounded theory, has uncovered that most of the students have gone through positive changes in their development of moral and social characters, such as attaining deeper sense of empathy and caring personalities. The study expresses, in identifying the nature of those transformations, that the importance of volunteer work should strongly be recognized by the colleges and universities in Japan, in fulfilling their public responsibility of creating and building learning communities that are responsible and caring.

Keywords: moral development, moral education, service learning, volunteer 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: Thanawit Tongmai, Chatchawan Saewor

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Learning management is very important for students’ development. To promote students’ potential, the teacher should design appropriate learning activity that brings their students potential out. Problem based learning has been using worldwide and it has presented numerous of success. This research aims to study third year students’ attitude and their achievement in scientific research course. To find the results, mix method was used to design research conduction. The researcher used PBL and reflection activity in the class. The students had to choose a topic, reviewed information, designed experimental, wrote academic report and presented their research by themselves. The researcher was only a facilitator. Reflection activity was used to progressing and consulting their research. The data was collected along with research conduction by questionnaire and test, including attitude, opinion and their achievement. The result of this study showed that 74.71% from all of students (n = 87) benefited from PBL and reflection activity, while 25.19% were just satisfied. 100% of students had a positive reflection toward PBL activity and they believed that PBL was the best pedagogy method for scientific research course. The achievements of these students were higher than the previous study (P < 0.05). The student’s learning achievement, A, B+ and B, was 48.28, 28.74 and 22.98% respectively. Therefore, it can conclude that PBL activity is appropriate for scientific research course and it can also promote student’s achievement.

Keywords: reflection, attitude, learning, achievement, PBL

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Authors: Yessica A. Aguilera

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English is currently the only foreign language included in the national educational curriculum in Chile. The English curriculum establishes that once completed secondary education, students are expected to reach B1 level according to the Common European Reference Framework (CEFR) scale. However, the objective has not been achieved, and to the author’s best knowledge, there is still a severe lack of English language skills among students who have completed their secondary education studies. In order to deal with the fact that students do not manage English as expected, team-based learning (TBL) was introduced in English language lessons at the Universidad Federico Santa María (USM). TBL is a collaborative teaching-learning method which enhances active learning by combining individual and team work. This approach seeks to help students achieve course objectives while learning how to function in teams. The purpose of the research was to assess the implementation and effectiveness of TBL in English language classes at USM technical training education. Quantitative and qualitative data were collected from teachers and students about their experience through TBL. Research findings show that both teachers and students are satisfied with the method and that students’ engagement and participation in class is higher. Additionally, students score higher on examinations improving academic outcomes. The findings of the research have the potential to guide how TBL could be included in future English language courses.

Keywords: collaborative learning, college education, English language learning, team-based learning

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Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

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Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees skill efficiently. This study focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increased. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, job satisfaction, learning and growth, Bangkok

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Authors: Kazumoto Tanaka

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It is well known that sport skill learning is facilitated by video observation of players’ actions in sports. The optimal viewpoint for the observation of actions depends on sport scenes. On the other hand, it is impossible to change viewpoint for the observation in general, because most videos are filmed from fixed points. The study has tackled the problem and focused on karate match as a first step. The study developed a method for observing karate player’s actions from any point of view by using 3D-CG model (i.e. virtual player) obtained from video images, and verified the effectiveness of the method on karate match.

Keywords: computer graphics, karate training, learning by observation, motion capture, virtual player

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Authors: Farouk Lawan Gambo, Hamada Mohammad

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Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

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Authors: Maryam Ghavam Sadri, Kimia Moiniafshari

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Objectives: The prevalence of Autism in the world has taken on a growing trend. Autism is a neuro-developmental disorder that is identified at the age of three. Studies have been shown that nutritional management can control nutritional deficiencies in Autism. This review study aimed to assess the role of nutritional management strategies for Autism in children has been made. Methods: This review study was accomplished by using the keywords related to the topic, 68 articles were found (2000-2015) and finally 15 articles with criteria such as including dietary pattern, nutritional deficiencies and Autism controlling were selected. Results: The studies showed that intake of vitamins D, E, and calcium because of restricted diet (casein and gluten free) in autistic children is less than typically developing children (TYP) (p value ≤ 0.001) and as a result of restrictions on the consumption of fresh fruits and vegetables, vitamin C and magnesium intake is less than TYP children (p value ≤ 0.001). Autistic children also get omega-3 less than TYP children. Studies have shown that food sources rich in omega-3 can improve behavioral indicators, especially in reducing hyperactivity (95% CI = -2.2 - 5.2). Zinc deficiency in these children leads to a high serum level of mercury, lead and cadmium. As a result of the repetitive dietary pattern, Sodium intake in autistic children is more than TYP children (p value < 0.001).Because of low food variety in autistic children, healthy eating index (HEI) is less than TYP children (p value = 0.008).Food selectivity in Autism due to repetitive and restricted dietary pattern and nutritional deficiencies. Conclusion: Because of restricted (casein and gluten free) and repetitive dietary pattern, the intake of some micronutrients are denied in autistic children. The nutritional strategy programs appear to help controlling of Autism.

Keywords: autism, food selectivity, nutrient intake, nutritional strategies

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Authors: Martina Holenko Dlab, Natasa Hoic-Bozic, Ivica Boticki

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This paper presents technologically innovative and scalable mobile learning solution within the SCOLLAm project (“Opening up education through Seamless and COLLAborative mobile learning on tablet computers”). The main research method applied during the development of the SCOLLAm mobile learning system is design-based research. It assumes iterative refinement of the system guided by collaboration between researches and practitioners. Following the identification of requirements, a multiplatform mobile learning system SCOLLAm [in]Form was developed. Several experiments were designed and conducted in the first and second grade of elementary school. SCOLLAm [in]Form system was used to design learning activities for math classes during which students practice calculation. System refinements were based on experience and interaction data gathered during class observations. In addition to implemented improvements, the data were used to outline possible improvements and deficiencies of the system that should be addressed in the next phase of the SCOLLAm [in]Form development.

Keywords: adaptation, collaborative learning, educational technology, mobile learning, tablet computers

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Linhan Sun

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With the gradual strengthening of China's economic development, more and more people around the world are learning Chinese due to economic and trade needs, which has also promoted the research related to Chinese language education for foreigners. Because the Chinese language system is different from the Western language system, learning Chinese is not easy for many learners. In addition, language learning cannot be separated from the learning and understanding of culture. How to integrate cultural learning into the curriculum of Chinese language education for foreigners is the focus of this study. Through a semi-structured in-depth interview method, 15 foreigners who have studied or are studying Chinese participated in this study. This study found that cultural learning and Chinese as a foreign language are relatively disconnected. In other words, learners were able to acquire a certain degree of knowledge of the Chinese language through textbooks or courses but did not gain a deeper understanding of Chinese culture.

Keywords: Chinese language education, Chinese culture, qualitative methods, intercultural communication

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