Search results for: online learning environments
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10250

Search results for: online learning environments

8750 Formation of Academia-Industry Collaborative Model to Improve the Quality of Teaching-Learning Process

Authors: M. Dakshayini, P. Jayarekha

Abstract:

In traditional output-based education system, class room lecture and laboratory are the traditional delivery methods used during the course. Written examination and lab examination have been used as a conventional tool for evaluating student’s performance. Hence, there are certain apprehensions that the traditional education system may not efficiently prepare the students for competent professional life. This has led for the change from Traditional output-based education to Outcome-Based Education (OBE). OBE first sets the ideal programme learning outcome consecutively on increasing degree of complexity that students are expected to master. The core curriculum, teaching methodologies and assessment tools are then designed to achieve the proposed outcomes mainly focusing on what students can actually attain after they are taught. In this paper, we discuss a promising applications based learning and evaluation component involving industry collaboration to improve the quality of teaching and student learning process. Incorporation of this component definitely improves the quality of student learning in engineering education and helps the student to attain the competency as per the graduate attributes. This may also reduce the Industry-academia gap.

Keywords: outcome-based education, programme learning outcome, teaching-learning process, evaluation, industry collaboration

Procedia PDF Downloads 431
8749 English Language Teaching and Learning Analysis in Iran

Authors: F. Zarrabi, J. R. Brown

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Although English is not a second language in Iran, it has become an inseparable part of many Iranian people’s lives and is becoming more and more widespread. This high demand has caused a significant increase in the number of private English language institutes in Iran. Although English is a compulsory course in schools and universities, the majority of Iranian people are unable to communicate easily in English. This paper reviews the current state of teaching and learning English as an international language in Iran. Attitudes and motivations about learning English are reviewed. Five different aspects of using English within the country are analysed, including: English in public domain, English in Media, English in organizations/businesses, English in education, and English in private language institutes. Despite the time and money spent on English language courses in private language institutes, the majority of learners seem to forget what has been learned within months of completing their course. That is, when they are students with the support of the teacher and formal classes, they appear to make progress and use English more or less fluently. When this support is removed, their language skills either stagnant or regress. The findings of this study suggest that a dependant approach to learning is potentially one of the main reasons for English language learning problems and this is encouraged by English course books and approaches to teaching.

Keywords: English in Iran, English language learning, English language teaching, evaluation

Procedia PDF Downloads 394
8748 Resilience of Infrastructure Networks: Maintenance of Bridges in Mountainous Environments

Authors: Lorenza Abbracciavento, Valerio De Biagi

Abstract:

Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.

Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance

Procedia PDF Downloads 53
8747 Maker Education as Means for Early Entrepreneurial Education: Evaluation Results from a European Pilot Action

Authors: Elisabeth Unterfrauner, Christian Voigt

Abstract:

Since the foundation of the first Fab Lab by the Massachusetts Institute of Technology about 17 years ago, the Maker movement has spread globally with the foundation of maker spaces and Fab Labs worldwide. In these workshops, citizens have access to digital fabrication technologies such as 3D printers and laser cutters to develop and test their own ideas and prototypes, which makes it an attractive place for start-up companies. Know-How is shared not only in the physical space but also online in diverse communities. According to the Horizon report, the Maker movement, however, will also have an impact on educational settings in the following years. The European project ‘DOIT - Entrepreneurial skills for young social innovators in an open digital world’ has incorporated key elements of making to develop an early entrepreneurial education program for children between the age of six and 16. The Maker pedagogy builds on constructive learning approaches, learning by doing principles, learning in collaborative and interdisciplinary teams and learning through trial and error where mistakes are acknowledged as learning opportunities. The DOIT program consists of seven consecutive elements. It starts with a motivation phase where students get motivated by envisioning the scope of their possibilities. The second step is about Co-design: Students are asked to collect and select potential ideas for innovations. In the Co-creation phase students gather in teams and develop first prototypes of their ideas. In the iteration phase, the prototype is continuously improved and in the next step, in the reflection phase, feedback on the prototypes is exchanged between the teams. In the last two steps, scaling and reaching out, the robustness of the prototype is tested with a bigger group of users outside of the educational setting and finally students will share their projects with a wider public. The DOIT program involves 1,000 children in two pilot phases at 11 pilot sites in ten different European countries. The comprehensive evaluation design is based on a mixed method approach with a theoretical backbone on Lackeus’ model of entrepreneurship education, which distinguishes between entrepreneurial attitudes, entrepreneurial skills and entrepreneurial knowledge. A pre-post-test with quantitative measures as well as qualitative data from interviews with facilitators, students and workshop protocols will reveal the effectiveness of the program. The evaluation results will be presented at the conference.

Keywords: early entrepreneurial education, Fab Lab, maker education, Maker movement

Procedia PDF Downloads 111
8746 Domain-Specific Deep Neural Network Model for Classification of Abnormalities on Chest Radiographs

Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

Abstract:

This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

Procedia PDF Downloads 97
8745 Introducing Transport Engineering through Blended Learning Initiatives

Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

Abstract:

Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

Procedia PDF Downloads 136
8744 Exploring Smartphone Applications for Enhancing Second Language Vocabulary Learning

Authors: Abdulmajeed Almansour

Abstract:

Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

Procedia PDF Downloads 144
8743 Analytical Study: An M-Learning App Reflecting the Factors Affecting Student’s Adoption of M-Learning

Authors: Ahmad Khachan, Ahmet Ozmen

Abstract:

This study aims to introduce a mobile bite-sized learning concept, a mobile application with social networks motivation factors that will encourage students to practice critical thinking, improve analytical skills and learn knowledge sharing. We do not aim to propose another e-learning or distance learning based tool like Moodle and Edmodo; instead, we introduce a mobile learning tool called Interactive M-learning Application. The tool reconstructs and strengthens the bonds between educators and learners and provides a foundation for integrating mobile devices in education. The application allows learners to stay connected all the time, share ideas, ask questions and learn from each other. It is built on Android since the Android has the largest platform share in the world and is dominating the market with 74.45% share in 2018. We have chosen Google-Firebase server for hosting because of flexibility, ease of hosting and real time update capabilities. The proposed m-learning tool was offered to four groups of university students in different majors. An improvement in the relation between the students, the teachers and the academic institution was obvious. Student’s performance got much better added to better analytical and critical skills advancement and moreover a willingness to adopt mobile learning in class. We have also compared our app with another tool in the same class for clarity and reliability of the results. The student’s mobile devices were used in this experimental study for diversity of devices and platform versions.

Keywords: education, engineering, interactive software, undergraduate education

Procedia PDF Downloads 133
8742 Intelligent Adaptive Learning in a Changing Environment

Authors: G. Valentis, Q. Berthelot

Abstract:

Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

Procedia PDF Downloads 408
8741 An Experimental Study for Assessing Email Classification Attributes Using Feature Selection Methods

Authors: Issa Qabaja, Fadi Thabtah

Abstract:

Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

Procedia PDF Downloads 412
8740 An Application of E-Learning Technology for Students with Deafness and Hearing Impairment

Authors: Eyup Bayram Guzel

Abstract:

There have been growing awareness that technology offers unique and promising advantages by offering up-to-data educational materials in promoting teaching and learning materials, new strategies for building enhanced communication environment for people with disabilities and specifically for this study concentrated on the students with deafness and hearing impairments. Creating e-learning environment where teachers and students work in collaboration to develop better educational outcomes is the foremost reason of conducting this research. This study examined the perspectives of special education teachers’ regarding an application of e-learning software called Multimedia Builder on the students with deafness and hearing impairments. Initial and follow up interviews were conducted with 15 special education teachers around the scope of qualitative case study. Grounded approach has been used to analyse and interpret the data. The research results revealed that application of Multimedia Builder software were influential on reading, sign language, vocabulary improvements, computer and ICT usage developments and on audio-visual learning achievements for the advantages of students with deafness and hearing impairments. The implications of the study encouraged the ways of using e-learning tools and strategies to promote unique and comprehensive learning experiences for the targeted students and their teachers.

Keywords: e-learning, special education, deafness and hearing impairment, computer-ICT usage.

Procedia PDF Downloads 421
8739 The Impact of Information and Communication Technology on Learning Quality and Conceptual Change in Moroccan High School Students

Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

Abstract:

Teaching and learning occupy a significant position globally, as the sustainable development of all sectors is intrinsically linked to the improvement of the educational system. The COVID-19 pandemic demonstrated that the integration of Information and Communication Technology (ICT) in the learning process is not optional but essential, and that proficiency in computer tools is an asset that will enhance pedagogy and ensure the continuity of learning under any circumstances. The objective of our study is to evaluate the impact of introducing computer tools on the quality of learning and the realization of conceptual change in learners. To this end, a learning situation was meticulously prepared, targeting first-year baccalaureate students in experimental sciences at a public high school, "Khadija Oum Almouminin," focusing on the chapter on glycemia regulation in the Moroccan Life and Earth Sciences (LES) curriculum. The learning situation was implemented with a pilot group that utilized computer tools and a control group that studied the same chapter without using ICT. The analysis and comparison of the results allowed us to verify the research question posed and to propose perspectives to ensure conceptual change in learners.

Keywords: information and communication technology, conceptual change, continuity of learning, life and earth sciences, glycemia regulation

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8738 Application of Supervised Deep Learning-based Machine Learning to Manage Smart Homes

Authors: Ahmed Al-Adaileh

Abstract:

Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

Procedia PDF Downloads 176
8737 Coevaluations Software among Students in Active Learning Methodology

Authors: Adriano Pinargote, Josue Mosquera, Eduardo Montero, Dalton Noboa, Jenny Venegas, Genesis Vasquez Escuela

Abstract:

In the framework of Pre University learning of the Polytechnic School of the Litoral, Guayaquil, Ecuador, the methodology of Active Learning (Flipped Classroom) has been implemented for applicants who wish to obtain a quota within the university. To complement the Active Learning cycle, it has been proposed that the respective students influence the qualification of their work groups, for which a web platform has been created that allows them to evaluate the performance of their peers through a digital coevaluation that measures through statistical methods, the group and individual performance score that can reflect in numbers a weighting score corresponding to the grade of each student. Their feedback provided by the group help to improve the performance of the activities carried out in classes because the note reflects the commitment with their classmates shown in the class, within this analysis we will determine if this implementation directly influences the performance of the grades obtained by the student.

Keywords: active learning, coevaluation, flipped classroom, pre university

Procedia PDF Downloads 121
8736 Enhanced Weighted Centroid Localization Algorithm for Indoor Environments

Authors: I. Nižetić Kosović, T. Jagušt

Abstract:

Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.

Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization

Procedia PDF Downloads 217
8735 Droning the Pedagogy: Future Prospect of Teaching and Learning

Authors: Farha Sattar, Laurence Tamatea, Muhammad Nawaz

Abstract:

Drones, the Unmanned Aerial Vehicles are playing an important role in real-world problem-solving. With the new advancements in technology, drones are becoming available, affordable and user- friendly. Use of drones in education is opening new trends in teaching and learning practices in an innovative and engaging way. Drones vary in types and sizes and possess various characteristics and capabilities which enhance their potential to be used in education from basic to advanced and challenging learning activities which are suitable for primary, middle and high school level. This research aims to provide an insight to explore different types of drones and their compatibility to be used in teaching different subjects at various levels. Research focuses on integrating the drone technology along with Australian curriculum content knowledge to reinforce the understanding of the fundamental concepts and helps to develop the critical thinking and reasoning in the learning process.

Keywords: critical thinking, drone technology, drone types, innovative learning

Procedia PDF Downloads 291
8734 Other-Generated Disclosure: A Challenge to Privacy on Social Network Sites

Authors: Tharntip Tawnie Chutikulrungsee, Oliver Kisalay Burmeister, Maumita Bhattacharya, Dragana Calic

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Sharing on social network sites (SNSs) has rapidly emerged as a new social norm and has become a global phenomenon. Billions of users reveal not only their own information (self disclosure) but also information about others (other-generated disclosure), resulting in a risk and a serious threat to either personal or informational privacy. Self-disclosure (SD) has been extensively researched in the literature, particularly regarding control of individual and existing privacy management. However, far too little attention has been paid to other-generated disclosure (OGD), especially by insiders. OGD has a strong influence on self-presentation, self-image, and electronic word of mouth (eWOM). Moreover, OGD is more credible and less likely manipulated than SD, but lacks privacy control and legal protection to some extent. This article examines OGD in depth, ranging from motivation to both online and offline impacts, based upon lived experiences from both ‘the disclosed’ and ‘the discloser’. Using purposive sampling, this phenomenological study involves an online survey and in-depth interviews. The findings report the influence of peer disclosure as well as users’ strategies to mitigate privacy issues. This article also calls attention to the challenge of OGD privacy and inadequacies in the law related to privacy protection in the digital domain.

Keywords: facebook, online privacy, other-generated disclosure, social networks sites (SNSs)

Procedia PDF Downloads 231
8733 An Adaptive CFAR Algorithm Based on Automatic Censoring in Heterogeneous Environments

Authors: Naime Boudemagh

Abstract:

In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

Procedia PDF Downloads 581
8732 Recommendations Using Online Water Quality Sensors for Chlorinated Drinking Water Monitoring at Drinking Water Distribution Systems Exposed to Glyphosate

Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

Procedia PDF Downloads 104
8731 Collaborative Reflexive/Reflective Teaching and Action Research in TESL

Authors: O. F. Elkommos

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Teaching English as a Second Language (TESL) has become a very rich area of research. Practitioners or teachers of English as a foreign or a second language are now promoting both collaborative learning and collaborative teaching. Students learning a language collaboratively and cooperatively are learning in a better environment of team work where they learn from each other. Further, teaching English collaboratively also creates an enriching environment that is also very enriching to students’ and teachers’ experiences of learning and teaching. Moreover, action research stems from actual teacher concerns and students’ needs. Reflection in turn, on the experience of the material taught and the delivery of material is becoming an integral part of the teaching and learning experience self- evaluation and self-development. In this case, the concern of the research field in the area of TESL will be the development of teaching delivery, material and quality of learning. In the present research, the TESL module taught to year two students in the Faculty of Arts and Humanities, British University in Egypt (BUE) will be evaluated reflexively by the students and teachers. The module was taught to students in two different specialisms. It was taught and delivered through collaborative teaching and was evaluated by both teachers and students as very successful and enjoyable. The reflections of both teachers and students as well as student results confirm that it was a success.

Keywords: action research, addressing differentiation, collaborative teaching, reflective teaching and learning, reflexive learning, reflexive teaching, self-development, self-evaluation, TESL

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8730 A Comparative Study of Language Learning Strategy Use of Iranian Kurdish Bilingual and Persian Monolingual in EFL Context

Authors: Reza Khani, Ziba Hosseini

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This study was an attempt to investigate the difference between learners of Iranian Kurdish–Persian bilingual language and Persian monolinguals, regarding language strategy use (LLS). The participants of the study were 120 monolingual Persian and 120 bilingual Kurdish studying English as a foreign language (EFL). Data were collected using strategy inventory for language learning SILL. The results show bilingual reported higher use of language learning strategies in all categories of SILL except memory strategies.

Keywords: language learning, memory, monolingual, comparative study

Procedia PDF Downloads 385
8729 Perceptions of Islamic Education Teachers on the Implementation of 21st Century Learning Practices

Authors: Hafizul Rasdi

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This study was conducted to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning practices in Kuching, Sarawak. This study uses the field method. Eight respondents were selected based on the interviews and focus group discussions conducted among teachers in four primary school in Kuching, Sarawak. This study is focused to find out the perceptions of Islamic Education teachers on the implementation of 21st century learning as well as the importance of 21st century learning in the subject of Islamic Education. Data were collected using library research, semi-structured interview transcripts and focus group discussions. Data analysis methods used was descriptive analysis. The findings of the study have shown that Islamic Education teachers in primary school in Kuching, Sarawak agreed on the implementation of 21st Century Learning Practices in Islamic Education subject. The finding also show that the application of 21st Century Learning Practices in the subject of Islamic Education can help improve students mastery of the subject.

Keywords: perceptions, Islamic education, 21st century learning practices, teachers

Procedia PDF Downloads 55
8728 A Comparative Study of Deep Learning Methods for COVID-19 Detection

Authors: Aishrith Rao

Abstract:

COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.

Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks

Procedia PDF Downloads 139
8727 Application of ICT in the Teaching and Learning of English Language in Nigerian Secondary Schools

Authors: Richard Ayobayowa Foyewa

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This work examined the application of ICT in the teaching and learning of English language in Nigerian secondary schools. The definition of ICT was given briefly before areas in which the ICT could be applied in teaching and learning of English language were observed. Teachers’ attitudes towards the use of the computer and Internet facilities were also observed. The conclusion drawn was that ICT is very relevant in the teaching and learning of English language in Nigerian secondary schools. It was therefore recommended that teachers who are not computer literate should go for the training without further delay; government should always employ English language teachers who are computer literates. Government should make fund available in schools for the training and re-training of English language teachers in various computer programmes and in making internet facilities available in secondary schools.

Keywords: ICT, Nigerian secondary schools, teaching and learning of English

Procedia PDF Downloads 297
8726 Data Augmentation for Automatic Graphical User Interface Generation Based on Generative Adversarial Network

Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

Procedia PDF Downloads 166
8725 Moving from Computer Assisted Learning Language to Mobile Assisted Learning Language Edutainment: A Trend for Teaching and Learning

Authors: Ahmad Almohana

Abstract:

Technology has led to rapid changes in the world, and most importantly to education, particularly in the 21st century. Technology has enhanced teachers’ potential and has resulted in the provision of greater interaction and choices for learners. In addition, technology is helping to improve individuals’ learning experiences and building their capacity to read, listen, speak, search, analyse, memorise and encode languages, as well as bringing learners together and creating a sense of greater involvement. This paper has been organised in the following way: the first section provides a review of the literature related to the implementation of CALL (computer assisted learning language), and it explains CALL and its phases, as well as attempting to highlight and analyse Warschauer’s article. The second section is an attempt to describe the move from CALL to mobilised systems of edutainment, which challenge existing forms of teaching and learning. It also addresses the role of the teacher and the curriculum content, and how this is affected by the computerisation of learning that is taking place. Finally, an empirical study has been conducted to collect data from teachers in Saudi Arabia using quantitive and qualitative method tools. Connections are made between the area of study and the personal experience of the researcher carrying out the study with a methodological reflection on the challenges faced by the teachers of this same system. The major findings were that it is worth spelling out here that despite the circumstances in which students and lecturers are currently working, the participants revealed themselves to be highly intelligent and articulate individuals who were constrained from revealing this criticality and creativity by the system of learning and teaching operant in most schools.

Keywords: CALL, computer assisted learning language, EFL, English as a foreign language, ELT, English language teaching, ETL, enhanced technology learning, MALL, mobile assisted learning language

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8724 Influencing Factors to Mandatory versus Non-Mandatory E-Government Services Adoption in India: An Empirical Study

Authors: Rajiv Kumar, Amit Sachan, Arindam Mukherjee

Abstract:

Government agencies around the world, including India, are incorporating digital technologies and processes into their day-to-day operations to become more efficient. Despite low internet penetration (around 34.8% of total population) in India, Government of India has made some public services mandatory to access online (e.g. passport, tax filing).This is insisting citizens to access mandatory public services online. However, due to digital divide, all citizens do not have equal access to internet. In light of this, it is an interesting topic to explore how citizens are able to access mandatory online public services. It is important to understand how citizens are adopting these mandatory e-government services and how the adoption behavior of these mandatory e-government services is different or similar to adoption behavior of non-mandatory e-government services. The purpose of this research is to investigate the factors that influence adoption of mandatory and non-mandatory e-government services in India. A quantitative technique is employed in this study. A conceptual model has been proposed by integrating the influencing factors to adopt e-government services from previous studies. The proposed conceptual model highlights a comprehensive set of potential factors influencing the adoption of e-government services. The proposed model has been validated by keeping in view the local context of Indian society. Online and paper based survey was administered, collected data was analyzed and results have been discussed. A total of 463 valid responses were received and further the responses were analyzed. The research reveals that the influencing factors to adopt e-government services are not same for both mandatory and non-mandatory e-government services. There are some factors that influence adoption of both mandatory and non-mandatory e-government services but there are some which are relevant for either of mandatory and non-mandatory e-government services. The research findings may help government or concerned agencies in successfully implementing e-government services.

Keywords: adoption, e-government, India, mandatory, non-mandatory

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8723 Factors Affecting Consumers’ Online Shopping Behavior in Vietnam during the COVID-19 Pandemic: A Case Study of Tiki

Authors: Thi Hai Anh Nguyen, Pantea Aria

Abstract:

Tiki is one of the leading e-commerce companies in Viet Nam. Since the beginning of 2020, COVID-19 has been spreading around the world. Thanks to this pandemic, the Tiki platform has many strengths and has faced many threats. Customer behaviour was forecasted to change during the COVID-19 pandemic. The aim of the investigation is (1) Identifying factors affecting online consumer behaviour of Tiki in Ho Chi Minh City, Vietnam, (2) Measuring the level of impact of these factors, and (3) Recommendations for Tiki to improve its business strategy for the next stage. This research studies eight factors and collected 378 online surveys for analysis. Using SPSS software identified five factors (product, price, reliability, and web design) positively influencing customer behaviour. COVID-19 factor does not impact significantly Tiki’s customer behaviour. This research conducted some qualitative interviews to understand shopping experiences and customers’ expectations. One of these interviews’ main points is that Tiki’s customers have high trust in the Tiki brand and its high-quality products. Based on the results, the Tiki corporation should secure its core value. Tiki’s employees and logistics systems should be well-trained and optimized to improve customer experiences.

Keywords: COVID-19, e-commerce, impact, pandemic, Vietnam

Procedia PDF Downloads 143
8722 Teachers’ and Students’ Reactions to a Guided Reading Program Designed by a Teachers’ Professional Learning Community

Authors: Yea-Mei Leou, Shiu-Hsung Huang, T. C. Shen, Chin-Ya Fang

Abstract:

The purposes of this study were to explore how to establish a professional learning community for English teachers at a junior high school, and to explore how teachers and students think about the guided reading program. The participants were three experienced English teachers and their ESL seventh-grade students from three classes in a junior high school. Leveled picture books and worksheets were used in the program. Questionnaires and interviews were used for gathering information. The findings were as follows: First, most students enjoyed this guided reading program. Second, the teachers thought the guided reading program was helpful to students’ learning and the discussions in the professional learning community refreshed their ideas, but the preparation for the teaching was time-consuming. Suggestions based on the findings were provided.

Keywords: ESL students, guided reading, leveled books, professional learning community

Procedia PDF Downloads 359
8721 A Framework of Product Information Service System Using Mobile Image Retrieval and Text Mining Techniques

Authors: Mei-Yi Wu, Shang-Ming Huang

Abstract:

The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

Procedia PDF Downloads 339