Search results for: supervised learning algorithm

Authors: Salina Budin, Nor Liawati Abu Othman, Shaira Ismail

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This study attempts to determine kinesthetic, verbal and visual intelligences among mechanical engineering undergraduate students and explores any probable relation with students’ learning styles and academic performance. The questionnaire used in this study is based on Howard Gardner’s multiple intelligences theory comprising of five elements of learning style; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering. Additional questions on students’ perception of learning styles and their academic performance are included in the questionnaire. The results show that one third of the students are strongly dominant in the kinesthetic intelligent (33%), followed by a combination of kinesthetic and visual intelligences (29%) and 21% are strongly dominant in all three types of intelligences. There is a statistically significant correlation between kinesthetic, verbal and visual intelligences and students learning styles and academic performances. The ANOVA analysis supports that there is a significant relationship between academic performances and level of kinesthetic, verbal and visual intelligences. In addition, it has also proven a remarkable relationship between academic performances and kinesthetic, verbal and visual learning styles amongst the male and female students. Thus, it can be concluded that, academic achievements can be enhanced by understanding as well as capitalizing the students’ types of intelligences and learning styles.

Keywords: kinesthetic intelligent, verbal intelligent, visual intelligent, learning style, academic performances

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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Authors: Danielle Guerra, Marden Silva

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The use of active methodologies in the teaching of English has been widely encouraged recently, due to its potential to create propitious conditions for the learners to develop autonomy and studying skills that tend to keep them motivated throughout the learning process. The constant use of technology by the students makes it possible to implement strategies such as blended learning, which blends regular classes with online instruction and practice. (Horn and Staker, 2015) For that reason, the aim of this study was to implement the blended approach in a High School second-grade English class in Brazil, in order to analyze the impacts of this methodology on the students' autonomy. The teacher's role was that of a mediator, being responsible for selecting the best resources for students to study with, and also for helping them with questions when necessary. The results show that taking learner characteristics and learning experiences into account and allowing the students to follow their learning paths at their own pace was crucial to promoting engagement that led to the desired outcomes. In conclusion, the research shows that blended learning is a helpful strategy to foster autonomy and promote motivation in EFL students.

Keywords: active methodologies, autonomy, blended learning, motivation

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Authors: Mehdi Rostamzadeh

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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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Authors: Jefferson S. Galanza, Jewel An Mischelle R.Camcam, Alyssa Karryl C. Co, Stephanie P. De Guzman, Jet Jet K. Dongui-is, Rodolfo Dane C. Frias, Ovelle C. Jueco, Harvey L. Matbagan, Victoria Luzette T. Rillon, Christelle Romyna H. Saruca, Jeanette Roma M. Villasper

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Background: Amidst numerous studies conducted on learning styles of students from a variety of courses, levels and school, a recent study recommended a great need for research on learning styles of student nurses. Moreover, related literatures have not been found exploring both the learning and teaching style of student nurses. Aims: The study aimed to determine the learning and teaching styles of student nurses and if there is an association between them. It also intended to discover whether student nurses are unimodal or multimodal in their styles and identified which faculty teaching style affords maximum outcome for student’s learning styles. Methods: Quantitative Descriptive-Correlational design was used. Participants were randomly selected 312 student nurses at School of Nursing X, Baguio City, Philippines. The questionnaire utilized a modified version of an adopted tool from Fleming’s VARK learning style version 7.2 (Visual, Auditory, Reader/Writer, Kinaesthetic) and Grasha’s teaching styles (Formal Authority, Demonstrator, Facilitator, Delegator). SPSS 19 was used for statistical treatment of data, where Chi square was used for the correlation of unimodal learning and teaching styles. Results/Finding: Majority of student nurses’ learning style is Kinesthetic and their teaching style is Demonstrator, which was also found to be significantly associated. Moreover, 8 out of 10 students are Unimodal in their learning and teaching modalities. In general, their preferred faculty teaching style is similar to their teaching style, which supports the concept, that teachers teach the way they learn. Conclusion: Study concludes that student nurses’ learning styles and teaching styles are varied, which exemplifies the uniqueness of every learner.This diversity in styles provided more evidence that a variety of mode of teaching and learning should be used by faculty and students to increase learning outcome and academic achievement. Recommendation: Future studies could be carried out in various schools of nursing utilizing faculty as respondents. Conduct assessment of learning style at the onset of classes/clinical placements so that faculty will become aware of the diversity of learners leading them to deliver diverse teaching methods.

Keywords: learning, learning styles, teaching styles, student nurses

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Authors: Rabia Aslam

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Overwhelming evidence from all around the world suggests that high-quality teacher professional development facilitates the improvement of teaching practices which in turn could improve student learning outcomes. The new Continuous Professional Development (CPD) model for primary school teachers in Punjab uses a blended approach in which pedagogical content knowledge is delivered through technology (high-quality instructional videos and lesson plans delivered to school tablets or mobile phones) with face-to-face support by Assistant Education Officers (AEOs). The model also develops Communities of Practice operationalized through formal meetings led by the AEOs and informal interactions through social media groups to provide opportunities for teachers to engage with each other and share their ideas, reflect on learning, and come up with solutions to issues they experience. Using Kirkpatrick’s 4 levels of the learning evaluation model, this paper investigates how school tablets and teacher mobile phones may act as transformational cultural tools to potentially expand perceptions and access to teaching and learning resources and explore some of the affordances of social media (Facebook, WhatsApp groups) in learning in an informal context. The results will be used to inform policy-level decisions on what shape could CPD of all teachers take in the context of a developing country like Pakistan.

Keywords: CPD, teaching & learning, blended learning, learning technologies

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Authors: Hadj Abd El Kader Benghenia, Fethi Bereksi Reguig

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In clinical medicine, blood pressure, raised blood hemodynamic monitoring is rich pathophysiological information of cardiovascular system, of course described through factors such as: blood volume, arterial compliance and peripheral resistance. In this work, we are interested in analyzing these signals to propose a detection algorithm to delineate the different sequences and especially systolic blood pressure (SBP), diastolic blood pressure (DBP), and the wave and dicrotic to do their analysis in order to extract the cardiovascular parameters.

Keywords: blood pressure, SBP, DBP, detection algorithm

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

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Authors: Saeed Poormoaied, Zumbul Atan

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Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

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Authors: Amira Abdulrazzaq

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This paper is studying the opinion of faculty members and students about the future of education (e-learning) at the University of Bahrain. Through quantitative analysis a distribution of two surveys, one targeting students of IT College, and College of Arts and the other targeting Faculty members of both Colleges. Through the above survey, the paper measures the following factors: awareness and acceptance, satisfaction, usability, and usefulness. Results indicate positive reactions of all above factors.

Keywords: e-learning, education, moodle, WebCT

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Authors: Adrian Florin Busu

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The communicative approach, or communicative language teaching, used for enhancing communicative skills in students in automatics is a modern teaching approach based on the concept of learning a language through having to communicate real meaning. In the communicative approach, real communication is both the objective of learning and the means through which it takes place. This approach was initiated during the 1970’s and quickly became prominent, as it proposed an alternative to the previous systems-oriented approaches. In other words, instead of focusing on the acquisition of grammar and vocabulary, the communicative approach aims at developing students’ competence to communicate in the target language with an enhanced focus on real-life situations. To put it in an nutshell, CLT considers using the language to be just as important as actually learning the language.

Keywords: communication, approach, objective, learning

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Authors: Malathi Balakrishnan, Gananathan M. Nadarajah, Saraswathy Vellasamy, Evelyn Gnanam William George

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The purpose of the study is to explore how the fun game-learning approach enhances teacher trainers’ higher order thinking skills. Two-day fun filled fun game learning-approach was introduced to teacher trainers as a Continuous Professional Development Program (CPD). 26 teacher trainers participated in this Transformation of Teaching and Learning Fun Way Program, organized by Institute of Teacher Education Malaysia. Qualitative research technique was adopted as the researchers observed the participants’ higher order thinking skills developed during the program. Data were collected from observational checklist; interview transcriptions of four participants and participants’ reflection notes. All the data were later analyzed with NVivo data analysis process. The finding of this study presented five main themes, which are critical thinking, hands on activities, creating, application and use of technology. The studies showed that the teacher trainers’ higher order thinking skills were enhanced after the two-day CPD program. Therefore, Institute of Teacher Education will have more success using the fun way game-learning approach to develop higher order thinking skills among its teacher trainers who can implement these skills to their trainee teachers in future. This study also added knowledge to Constructivism learning theory, which will further highlight the prominence of the fun way learning approach to enhance higher order thinking skills.

Keywords: constructivism, game-learning approach, higher order thinking skill, teacher trainer

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Orit Baruth, Anat Cohen

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Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: María-Dolores Afonso-Suárez, Nayra Pumar-Carreras, Juan Ruiz-Alzola

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This research addresses the use of an e-Learning creation methodology for learning objects. Throughout the process, indicators are being gathered, to determine if it responds to the main objectives of an engineering discipline. These parameters will also indicate if it is necessary to review the creation cycle and readjust any phase. Within the project developed for this study, apart from the use of structured methods, there has been a central objective: the establishment of a learning atmosphere. A place where all the professionals involved are able to collaborate, plan, solve problems and determine guides to follow in order to develop creative and innovative solutions. It has been outlined as a blended learning program with an assessment plan that proposes face to face lessons, coaching, collaboration, multimedia and web based learning objects as well as support resources. The project has been drawn as a long term task, the pilot teaching actions designed provide the preliminary results object of study. This methodology is been used in the creation of learning content for the African countries of Senegal, Mauritania and Cape Verde. It has been developed within the framework of the MACbioIDi, an Interreg European project for the International cooperation and development. The educational area of this project is focused in the training and advice of professionals of the medicine as well as engineers in the use of applications of medical imaging technology, specifically the 3DSlicer application and the Open Anatomy Browser.

Keywords: teaching contents engineering, e-learning, blended learning, international cooperation, 3dslicer, open anatomy browser

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Authors: Cristie Ann Jaca-Delfin, Felino Javines Jr.

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Teachers especially those who are teaching elementary and high school students need to upgrade their teaching practices in order to become effective and efficient facilitators of learning. It is in this context that this study is conducted in order to present the perceived teaching-learning activities needs among basic education teachers in the three campuses of the University of San Carlos, Cebu City, the Philippines as expressed during their In-Service Teacher Training. The study employed the quantitative-qualitative research design and used the researcher-made survey questionnaire to look into the ten items under Teaching-Learning Activities to determine which item teachers need to be trained and retrained on. The data were solicited during the teachers’ In-Service Teacher Training period conducted in May 2015. It was found out that designing interesting and meaningful classroom activities, strategies in teaching and assessment procedures were identified as the most needed areas teachers want to be included in their in-service training. As these expressed needs were identified, the teachers’ in-service training must a venue for teachers’ instructional development needs to be addressed so as to maximize the students’ learning outcomes

Keywords: in-service teacher training, perceived needs, teaching-learning activities, teaching practices

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Authors: Mehdi Damaliamiri, Firouzeh Akbari

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Teaching literature to children at an early age is of great importance, and there have been different methods to facilitate learning literature. Based on the law, all children going to school in Iran should learn the Persian language and literature. This has been concomitant with two different levels of learning related to urban or rural bilingualism. For bilingual children living in the villages, learning literature and a new language (Persian) turns into a big challenge as it is done based on the translation the teacher does while in the city, it is easier as the confrontation of children with the Persian language is more. Over recent years, to change the trend of learning Persian by children speaking another language, the TV and radio programs have been considered to be effective, but the scores of the students in Persian language national exams show that these programs have not been so effective for the bilingual students living in the villages. To identify the determinants of weak learning of Persian by bilingual children, two different regions were chosen, Turkish-speaking and Kurdish-speaking communities, to compare their learning of Persian at the first and second levels of elementary school. The criteria of learning was based on the syllabification of Persian words, word order in the sentence, and compound sentences. Students were taught in Persian how to recognize syllabification without letting them translate the words in their own languages and were asked to produce simple sentences in Persian in response to situational questions. Teaching methods, language relatedness with Persian, and exposure to social media programs, especially TV and radio, were the factors that were considered to affect the potential of children in learning Persian.

Keywords: bilingualism, persian, education, Literature

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Authors: Arshad Mehmood Ch, Riaz Ahmad, Imran Ali Ch, Waqas Durrani

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This study deals with the application of Ant Colony Optimization (ACO) approach to solve no-wait flowshop scheduling problem (NW-FSSP). ACO algorithm so developed has been coded on Matlab computer application. The paper covers detailed steps to apply ACO and focuses on judging the strength of ACO in relation to other solution techniques previously applied to solve no-wait flowshop problem. The general purpose approach was able to find reasonably accurate solutions for almost all the problems under consideration and was able to handle a fairly large spectrum of problems with far reduced CPU effort. Careful scrutiny of the results reveals that the algorithm presented results better than other approaches like Genetic algorithm and Tabu Search heuristics etc; earlier applied to solve NW-FSSP data sets.

Keywords: no-wait, flowshop, scheduling, ant colony optimization (ACO), makespan

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Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

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Authors: Mei-Ying Liao, Lee-Ching Wei, Jung-Hsiang Tseng

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The main purpose of this study was to explore the process of planning and execution of the music learning center in preschool. This study was conducted through a collaborative action research method. The research members included a university music professor, a teaching guide, a preschool director, and a preschool teacher, leading a class of 5-6-year-old children to participate in this study. Five teaching cycles were performed with a subject of bird. In the whole process that lasted three months, the research members would maintain the conversation, reflection, and revision repeatedly. A triangular validated method was used to collect data, including archives, interviews, seminars, observations, journals, and learning evaluations to improve research on the validity and reliability. It was found that a successful music learning center required comprehensive planning and execution. It is also important to develop good listening, singing, respect, and homing habits at the beginning of running the music learning center. By timely providing diverse musical instruments, learning materials, and activities according to the teaching goals, children’s desire to learning was highly stimulated. Besides, peer interactions improved their ensemble and problem-solving abilities. The collaborative action research enhanced the preschool teacher’s confidence and promoted professional growth of the research members.

Keywords: collaborative action research, case study, music learning center, music development

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Authors: Pia Kastl

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Potentials of blended learning are the flexibility of learning and the possibility to get in touch with lecturers and fellow students on site. By combining face-to-face sessions with digital self-learning units, the learning process can be optimized, and learning success increased. To examine wether blended learning outperforms online and face-to-face teaching, a theory-based questionnaire survey was conducted. The results show that the interaction and cooperation among students is poorly provided in blended learning, and face-to-face teaching performs better in this respect. The aim of this article is to identify concrete suggestions students have for improving cooperation and interaction in blended learning courses. For this purpose, interviews were conducted with students from various academic disciplines in face-to-face, online, or blended learning courses (N= 60). The questions referred to opinions and suggestions for improvement regarding the course design of the respective learning environment. The analysis was carried out by qualitative content analysis. The results show that students perceive the interaction as beneficial to their learning. They verbalize their knowledge and are exposed to different perspectives. In addition, emotional support is particularly important in exam phases. Interaction and cooperation were primarily enabled in the face-to-face component of the courses studied, while there was very limited contact with fellow students in the asynchronous component. Forums offered were hardly used or not used at all because the barrier to asking a question publicly is too high, and students prefer private channels for communication. This is accompanied by the disadvantage that the interaction occurs only among people who already know each other. Creating contacts is not fostered in the blended learning courses. Students consider optimization possibilities as a task of the lecturers in the face-to-face sessions: Here, interaction and cooperation should be encouraged through get-to-know-you rounds or group work. It is important here to group the participants randomly to establish contact with new people. In addition, sufficient time for interaction is desired in the lecture, e.g., in the context of discussions or partner work. In the digital component, students prefer synchronous exchange at a fixed time, for example, in breakout rooms or an MS Teams channel. The results provide an overview of how interaction and cooperation can be implemented in blended learning courses. Positive design possibilities are partly dependent on subject area and course. Future studies could tie in here with a course-specific analysis.

Keywords: blended learning, higher education, hybrid teaching, qualitative research, student learning

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Authors: Ahmed Amin Mousa, Huda Mazeed, Eman Saad

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The study aims to identify the extent of the effectiveness of the artistic formation program using some types of pastes to reduce the hyperactivity of the kindergarten child. The researcher has discussed the effectiveness of the artistic program using some types of pastes in reducing the hyperactivity of the kindergarten child. The research sample included 120 children of ages between 5 to 6 years old from the five schools for special needs section learning disability, Cairo Province. The study used the empirical like curriculum which depends on designing one group using the before and after application measurement for the group to validate the fidelity of both the hypothesis and the effectiveness of the program. The variables of the study were specified as follows; artistic formation program using paper Mache as an independent variable and its effect on skills of kindergarten child with learning disabilities as a subsequent variable. The researchers depended on applying a group of artistic formation program using pulp melding skills for kindergarten children with learning disabilities. The tools of the study, designed by the researcher, included: recording card used for recording the Effective program using pulp molding skills for kindergarten children with learning disabilities during practicing the artistic formation activity. In additional, there was a program using pulp molding skills for kindergarten children with learning disabilities. The results proved the effectiveness of the program using pulp molding skills for kindergarten children with learning disabilities.

Keywords: artistic program, developing skills, kindergarten, children, learning disabilities

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Authors: Ibraheem Alzahrani

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The Saudi Arabia ministry of higher education has established 24 universities across various cities in the kingdom. The universities have the mandate of sustaining technological progress in both teaching and learning. The present study explores the statues of teaching in Saudi universities, focusing on biology, a critical curriculum. The paper explores biology teachers’ points of view is several Saudi higher education institutions through questionnaires disseminated via emails. According to the findings, the current teaching methods are traditional and the teachers believe that it is critical to change it. This study also, reviews how biology has been taught in the kingdom over the past, as well as how it is undertaken presently. In addition, some aspects of biology teaching are considered, including the biology curriculum and learning objectives in higher education biology.

Keywords: higher education, teaching style, traditional learning, electronic learning, web 2.0 applications, blended learning

Procedia PDF Downloads 371

Authors: Deonie Botha

Abstract:

Digital transformation and the digitization of occupational health and safety training have grown exponentially due to a variety of contributing factors. The literature suggests that digitalization has numerous benefits but also has associated challenges. The aim of the paper is to develop an understanding of both the perceived benefits and challenges of digitalization in an occupational health and safety context in an effort to design and develop e-learning interventions that will optimize the benefits of digitalization and address the associated challenges. The paper proposes, deliberate and tests the design principles of an e-learning intervention to ensure alignment with the requirements of a digitally transformed environment. The results of the research are based on a literature review regarding the requirements and effect of the Fourth Industrial Revolution on learning and e-learning in particular. The findings of the literature review are enhanced with empirical research in the form of a case study conducted in an organization that designs and develops e-learning content in the occupational health and safety industry. The primary findings of the research indicated that: (i) The requirements of learners and organizations in respect of e-learning are different than previously (i.e., a pre-Fourth Industrial Revolution related work setting). (ii) The design principles of an e-learning intervention need to be aligned with the entire value chain of the organization. (iii) Digital twins support and enhance the design and development of e-learning. (iv)Learning should incorporate a multitude of sensory experiences and should not only be based on visual stimulation. (v) Data that are generated as a result of e-learning interventions should be incorporated into big data streams to be analyzed and to become actionable. It is therefore concluded that there is general consensus on the requirements that e-learning interventions need to adhere to in a digitally transformed occupational health and safety work environment. The challenge remains for organizations to incorporate data generated as a result of e-learning interventions into the digital ecosystem of the organization.

Keywords: digitalization, training, fourth industrial revolution, big data

Procedia PDF Downloads 145

Authors: Takwa Jahan

Abstract:

Music can be used in ESL classroom to create a learning environment. As literature abounds with positive statements, music can be used as a vehicle for second language acquisition. Music can be applied as an instrument to help second language learners to acquire vocabulary, grammar, spelling and other four skills and to expand cultural knowledge. Vocabulary learning is perceived boring by learners. As listening to music and singing songs are enjoyable to students, it can be used effectively to acquire vocabulary in second language. This paper reports a study to find out how music exhilarates vocabulary acquisition as the learners stay relaxed and thus learning becomes more enjoyable. For conducting my research two groups of fifty students- music and non-music group were formed. Data were collected through class observation, test, questionnaires, and interview. The finding shows that music group acquired much amount of vocabulary than the non-music group. They enjoyed vocabulary learning activities based on listening songs.

Keywords: effective instrument, ESL classroom, music, relax environment, vocabulary learning

Procedia PDF Downloads 358

Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

Abstract:

Many people know ‘Mathematics needs practice!’ statement or similar ones from their mathematics lessons. It seems important to practice when learning mathematics. At the same time, it also seems important to practice how to learn mathematics. This paper places neuroscientific-radiological findings on “practicing” while learning mathematics in a context of mathematics education. To accomplish this, we use a literature-based discussion of our case study on practice. We want to describe neuroscientific-radiological findings in the context of mathematics education and point out stimulating connections between both perspectives. From a connective perspective we expect incentives that lead discussions in future research in the field of mathematics education.

Keywords: functional magnetic resonance imaging, fMRI, education, mathematics learning, practicing

Procedia PDF Downloads 324

Authors: Kunihiro Kamataki

Abstract:

In this study, active learning based on simple science experiments was developed in a university class of the freshman, in order to improve their scientific literacy. Through the active learning based on simple experiments of generation of cloud in a plastic bottle, students increased the interest in the global atmospheric problem and were able to discuss and find solutions about this problem positively from various viewpoints of the science technology, the politics, the economy, the diplomacy and the relations among nations. The results of their questionnaires and free descriptions of this class indicate that they improve the scientific literacy and motivations of other classroom lectures to acquire knowledge. It is thus suggested that the science experiment is strong tool to improve their intellectual curiosity rapidly and the connections that link the impression of science experiment and their interest of the social problem is very important to enhance their learning effect in this education.

Keywords: active learning, scientific literacy, simple scientific experiment, university education

Procedia PDF Downloads 250