Search results for: application based learning

Authors: Jinil Patel, Sarthak Patel, Sarthak Thakkar, Deepti Saraswat

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Recently, the COVID-19 outbreak has spread across the world, leading the World Health Organization to classify it as a global pandemic. To save the patient’s life, the COVID-19 symptoms have to be identified. But using an AI (Artificial Intelligence) model to identify COVID-19 symptoms within the allotted time was challenging. The RT-PCR test was found to be inadequate in determining the COVID status of a patient. To determine if the patient has COVID-19 or not, a Computed Tomography Scan (CT scan) of patient is a better alternative. It will be challenging to compile and store all the data from various hospitals on the server, though. Federated learning, therefore, aids in resolving this problem. Certain deep learning models help to classify Covid-19. This paper will have detailed work of certain deep learning models like VGG19, ResNet50, MobileNEtv2, and Deep Learning Aggregation (DLA) along with maintaining privacy with encryption.

Keywords: federated learning, COVID-19, CT-scan, homomorphic encryption, ResNet50, VGG-19, MobileNetv2, DLA

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Authors: Aliakbar Alijarahi, Ali Khaleghi, Azadehe Afrasiyabi

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One of the emerging technologies in the field of education that can be effectively profitable, called augmented reality, where the combination of real world and virtual images in real time produces new concepts that can facilitate learning. The paper, providing an introduction to the general concept of augmented reality, aims at surveying its capabitities in different areas, with an emphasis on Education, It seems quite necessary to have comparative study on virtual/e-learning and augmented reality and conclude their differences in education methods. As an review article, the paper is composed, instead of producing new concepts, to sum-up and analayze accomplished works related to the subject.

Keywords: augmented reality, education, virtual learning, e-learning

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Authors: Anjum Afrooze

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The curriculum at General Sciences department in Prince Sultan University includes ‘Physical science’ for Computer Science, Information Technology and Business courses. Students are apathetic towards Physical Science and question, as to, ‘How this course is related to their majors?’ English is not a native language for the students and also for many instructors. More than sixty percent of the students come from institutions where English is not the medium of instruction, which makes student learning and academic achievement challenging. After observing the less enthusiastic student cohort for two consecutive semesters, the instructor was keen to find effective strategies to enhance learning and further encourage deep learning by engaging students in different tasks to empower them with necessary skills and motivate them. This study is participatory action research, in which instructor designs effective tasks to engage students in their learning. The study is conducted through two semesters with a total of 200 students. The effectiveness of this approach is studied using questionnaire at the end of each semester and teacher observation. Major outcomes of this study were overall improvement in students attitude towards science learning, enhancement of multiple skills like note taking, problem solving, language proficiency and also fortifying confidence. This process transformed instructor into engaging and reflecting practitioner. Also, these strategies were implemented by other instructors teaching the course and proved effective in opening a path to changes in related areas of the course curriculum. However, refinement in the strategies could be done based on student evaluation and instructors observation.

Keywords: group activity, language proficiency, reasoning skills, science learning

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: blended learning, higher education, WhatsApp, programming, novices, lecturers

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Authors: Faiza Abdul Latip

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One of the ultimate goals of any nation is to produce competitive manpower and this includes Philippines. Inclination in the field of Mathematics has a significant role in achieving this goal. However, Mathematics, as considered by most people, is the most difficult subject matter along with its topics to learn. This could be manifested from the low performance of students in national and international assessments. Educators have been widely using learning style models in identifying the way students learn. Moreover, it could be the frontline in knowing the difficulties held by each learner in a particular topic specifically concepts pertaining to fractions. However, as what many educators observed, students show difficulties in doing mathematical tasks and in great degree in dealing with fractions most specifically in the district of Datu Odin Sinsuat, Maguindanao. This study focused on the Datu Odin Sinsuat district grade six pupils’ learning styles along with their achievements and difficulties in learning concepts on fractions. Five hundred thirty-two pupils from ten different public elementary schools of the Datu Odin Sinsuat districts were purposively used as the respondents of the study. A descriptive research using the survey method was employed in this study. Quantitative analysis on the pupils’ learning styles on the Kolb’s Learning Style Inventory (KLSI) and scores on the mathematics diagnostic test on fraction concepts were made using this method. The simple frequency and percentage counts were used to analyze the pupils’ learning styles and their achievements on fractions. To determine the pupils’ difficulties in fractions, the index of difficulty on every item was determined. Lastly, the Kruskal-Wallis Test was used in determining the significant difference in the pupils’ achievements on fractions classified by their learning styles. This test was set at 0.05 level of significance. The minimum H-Value of 7.82 was used to determine the significance of the test. The results revealed that the pupils of Datu Odin Sinsuat districts learn fractions in varied ways as they are of different learning styles. However, their achievements in fractions are low regardless of their learning styles. Difficulties in learning fractions were found most in the area of Estimation, Comparing/Ordering, and Division Interpretation of Fractions. Most of the pupils find it very difficult to use fraction as a measure, compare or arrange series of fractions and use the concept of fraction as a quotient.

Keywords: difficulties in fraction, fraction, Kolb's model, learning styles

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Rungrot Trongsakul

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This paper was aimed to study the strategic cooperation development of Thailand in accordance with the door open policy of Myanmar, by use of DIMES Model: Diplomacy, Information, Military and Economics, Socio-Culture. This research employed qualitative method, aiming to study, analyze and synthesize the content of laws, policies, relevant research papers and documents, and relevant theories, and to study external environment and national power based on DIMES Model. The five steps of strategic development utilized in this study included (1) conceptual framework and definition; (2) environmental scanning; (3) assessing; (4) determining; and (5) drafting strategic plan. The suggested strategies were based on the concept of 'Soft Power'. Therefore, the determination of measures, action plans or projects as strategic means of public and private organizations should be based on sincere participation among people and communities living on the borders shared by both countries. Adoption of education, learning and sharing process is a key to building sustainability of the countries’ strategic cooperation, while an application of 'Soft Power' in all dimensions of the cooperation between the two countries was suggested.

Keywords: education, strategic cooperation, Thailand-Myanmar borders, sustainability

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Authors: S. J. Hachar

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The goal of this paper is to provide educators an overview of international practices supporting young learners, arming us with adequate information to lead effective change. We will report on research and observations of Service Learning Projects conducted by one South Texas University. The intent of the paper is also to provide readers an overview of service learning in the preparation of teacher candidates pursuing a Bachelor of Science in Elementary Education. The objective of noting the efficiency and effectiveness of programs leading to literacy and oral fluency in a native language and second language will be discussed. This paper also highlights experiential learning for academic credit that combines community service with student learning. Six weeks of visits to a variety of community sites, making personal observations with faculty members, conducting extensive interviews with parents and key personnel at all sites will be discussed. The culminating Service Learning Expo will be reported as well.

Keywords: elementary education, junior achievement, service learning

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Authors: T. T. K. Nguyen, T. H. Doan

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The study investigates students’ perceptions and students’ use of vocabulary learning strategies (VLS) among non-English majors at Ho Chi Minh City University of Technology (HUTECH). Three main issues addressed are (1) to determine students’ perception in terms of their awareness and the level of the importance of vocabulary learning strategies; (2) students’ use in terms of frequency and preference; (3) the correlation between students’ perception in terms of the level of the importance of vocabulary learning strategies and their use in terms of frequency. The mixed method is applied in this investigation; additionally, questionnaires focus on social groups, memory groups, cognitive groups, and metacognitive groups with 350 sophomores from four different majors, and 10 sophomores are invited to structured interviews. The results showed that the vocabulary learning strategies of the current study were well aware. All those strategies were perceived as important in learning vocabulary, and four groups of vocabulary were used frequently. Students’ responses in terms of preference also confirmed students’ use in terms of frequency. On the other hand, students’ perception correlated with students’ use in only the cognitive group of vocabulary learning strategies, but not the three others.

Keywords: vocabulary learning strategies, students' perceptions, students' use, mixed methods, non-English majors

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Authors: Wei Zhao

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The pandemic crisis disrupted normal classroom practices so that the constraints of the traditional practice became apparent. This turns out to be new opportunities for technology-based learning and teaching. However, how the technology supports the preschool teachers go through this sudden crisis and how preschool teachers conceived of the use of technology, appropriate and design technological artifacts as a mediator of knowledge construction in order to suit young children’s literacy level are rarely explored. This study addresses these issues by looking at the influence of a web-supported teacher community on changes/shifts in preschool teachers’ epistemological beliefs and practices. This teachers’ professional development community was formulated before the pandemic time and developed virtually throughout the home-based learning caused by Covid-19. It served as a virtual and asynchronous community for those teachers to collaboratively plan for and conduct online lessons using the knowledge-building approach for the purpose of sustaining children’s learning curiosity and opening up new learning opportunities during the lock-down period. The knowledge-building approach helps to increase teachers’ collective responsibility to collaboratively work on shared educational goals in the teacher community and awareness of noticing new ideas or innovations in their classroom. Based on the data collected across five months during and after the lock-down period and the activity theory, results show a dynamic interplay between the evolution of the community culture, the growth of teacher community and teachers’ identity transformation and professional development. Technology is useful in this regard not only because it transforms the geographical distance and new gathering guidelines after the outbreak of pandemic into new ways of communal communication and collaboration. More importantly, while teachers selected, monitored and adapted the technology, it acts as a catalyst for changes in teachers’ old teaching practices and epistemological dispositions.

Keywords: activity theory, changes in epistemology and practice, knowledge building, web-based teachers’ professional development community

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Authors: Noha Desouky Aly, Maged Makram Habib

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Given the imperative role educational institutions have in the creation of a motivational learning community that develops and engages their students, the influence of evoking the same environment for their teachers needs to be examined. Teachers and their role lie at the core of the efficiency of the learning experience. One exigent aspect in the process of providing professional development to teachers is to involve them in this process, and the best manner would be through creating a learning community in which they are directly engaged and responsible for their own learning. An educational institution that thinks first of its teachers learning and growth would achieve its goals in providing an effective education for its students. The purpose of this research paper is to examine the effect of engaging teachers in a learning community in which they are responsible for their own learning through conducting and providing the material required for the training on their self efficacy, engagement, and perceived autonomy. The sample includes twenty instructors at the German University in Cairo teaching Academic skills at the Department of English and Scientific Methods. The courses taught at the department include Academic skills, writing argumentative essays, critical thinking, communication and presentation skills, and research paper writing. Procedures for the duration of eight weeks will entail pre-post measures to include The Teachers Self Efficacy Scale and an interview. During the weekly departmental meeting, teachers are to share resources and experiences or research and present a topic of their choice that contributes to their professional development. Results are yet to be found.

Keywords: learning community, self- efficacy, teachers, learning experience

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Authors: Aditya Verma

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E-voting using blockchain provides us with a distributed system where data is present on each node present in the network and is reliable and secure too due to its immutability property. This work compares various blockchain consensus algorithms used for e-voting applications in the past, based on performance and node scalability, and chooses the optimal one and improves on one such previous implementation by proposing solutions for the loopholes of the optimally working blockchain consensus algorithm, in our chosen application, e-voting.

Keywords: blockchain, parallel bft, consensus algorithms, performance

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Authors: Shang-Hua Wu, Rong-Chi Chang, Horng–Twu Liaw

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Nowadays, competencies of e-learning project personnel are very important in assisting them in offering courses, serving students in an effective way, leveraging advantages, strengthen their relationships with potential students, etc. among e-learning platforms, MOOCs has recently attracted increasing focuses in distance education since it can be conducted for a large numbers of virtual learners. Nonetheless, since MOOCs is a relatively new e-learning platform, top concerns have been paid to what competencies are important for e-learning personnel to consider. Taking this need, this research aimed to carry out an in-depth exploration of competency requirements of MOOCs (e-learning) project personnel in Taiwan vocational schools. Data were collected through thorough literature reviews and discussions and competency analysis was carried out using Delphi technique questionnaires. The results show that that MOOCs (e-learning) project personnel’ professional competency lie in three main dimensions, among which ‘demand analysis competency’ (i.e., containing 10 major competences and 48 subordinate capabilities) is the most important competency, followed by ‘project management competency’ (i.e., comprising 6 major competences and 31 secondary capabilities), and finally ‘digital content production competency’ (i.e., including 12 major competences and 79 secondary capabilities). As such, in Taiwan context with different organizational scales and market sizes, the e-learning competency items and unique experience/ achievements throughout the promotion process obtained in this research will provide useful references for academic institutions in promoting e-learning.

Keywords: competency analysis, Delphi technique questionnaire, e-learning, massive open online courses

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Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

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Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

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Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: community pharmacy, intervention, prevention, risk assessment, type 2 diabetes

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Hema Vanita Kesevan

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The global spread of Covid-19 virus in early 2020 has led to major changes in many walks of life, including the education system. Traditional face to face lessons that were carried out for years has been replaced by online learning. Although online learning has been used before the pandemic, it has not been the only source of teaching and learning. This drastic change has brought significant impact to the process of teaching and learning in many classrooms around the world. Likewise, in country like Malaysia that that has been promoting online learning but has not utilize it fully due to many restrictions in terms of technology, accessibility, and online literacy, the sudden change to full online platform learning in all educational sector has definitely caused Issues in terms of its adaptation and usage. Although many studies have been conducted to explore the efficiency and impact of online learning during the pandemic, studies focusing on the same are limited in Malaysian classroom context, especially in English language classrooms. Thus, this study seeks to explore on the efficacy and effectiveness of online learning tools in ESL classroom contexts during the pandemic. The aim of this study is to understand the educator's and student's perceptions on the implementation of online learning tools in the teaching and learning process and the types of online learning tools that were used to assist the teaching and learning process during the pandemic. Particularly, this study focused to explore the types of online learning tools used in Malaysian schools and university during the online teaching and learning process and further explores how the various types of tools used impacted the students' participation in the lessons conducted. The participants of this study are secondary school students, teachers, and university students. Data will be collected in terms of survey questionnaire and interviews. The survey data intends to obtain information on the types of online learning used in ESL teaching and learning practices during the pandemic, how the various types of online tools influence students' participation during lessons. The interview data from the teachers serves to provide information about the selection of online learning tools, challenges of using it to conduct online lessons, and other arising issues. A mixed method design will be used to analysed the data obtained. The questionnaire will be analysed quantitatively using descriptive analysis meanwhile, the interview data will be analysed qualitatively.

Keywords: Covid 19, online learning tools, ESL classroom, effectiveness, efficacy

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Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

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Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

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Authors: Sumaira Taj

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Blended learning is emerged as a prerequisite approach for teaching in all schools after the outbreak of the COVID-19 pandemic. However, how much public elementary and secondary schools in Pakistan are ready for adapting this approach and what should be done to prepare schools and students for blended learning are the questions that this paper attempts to answer. Mixed-method research methodology was used to collect data from 40 teachers, 500 students, and 10 mothers. Descriptive statistics was used to analyze quantitative data. As for as readiness is concerned, schools lack resources for blended/ virtual/ online classes from infra-structure to skills, parents’ literacy level hindered students’ learning process and teachers’ skills presented challenges in a smooth and swift shift of the schools from face-to-face learning to blended learning. It is recommended to establish a conducive environment in schools by providing all required resources and skills. Special trainings should be organized for low literacy level parents. Multiple ways should be adopted to benefit all students.

Keywords: blended learning, challenges in online classes, education in covid-19, public schools in pakistan

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Authors: Kanyaporn Sommeechai

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Air cadets who aspire to become military pilots upon graduation undergo rigorous training at military academies. As first-year cadets are akin to civilian freshmen, they encounter numerous challenges within the seniority-based military academy system. Imposed routines, such as mandatory morning runs and restrictions on mobile phone usage for two semesters, have the potential to impact their learning process and motivation to study, including second language (L2) acquisition. This study aims to investigate the motivational dynamics and L2 learning transitions experienced by air cadets. To achieve this, a Retrodictive Qualitative Modelling approach will be employed, coupled with the adaptation of the three-barrier structure encompassing institutional factors, situational factors, and dispositional factors. Semi-structured interviews will be conducted to gather rich qualitative data. By analyzing and interpreting the collected data, this research seeks to shed light on the motivational factors that influence air cadets' L2 learning journey. The three-barrier structure will provide a comprehensive framework to identify and understand the institutional, situational, and dispositional factors that may impede or facilitate their motivation and language learning progress. Moreover, the study will explore how these factors interact and shape cadets' motivation and learning experiences. The outcomes of this research will yield fundamental data that can inform strategies and interventions to enhance the motivation and language learning outcomes of air cadets. By better understanding their motivational dynamics and transitions, educators and institutions can create targeted initiatives, tailored pedagogical approaches, and supportive environments that effectively inspire and engage air cadets as L2 learners.

Keywords: second language, education, motivational dynamics, learning transitions

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Authors: P. L. Cheng, I. N. Umar

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Online discussion forum is a popular e-learning technique that allows participants to interact and construct knowledge. This study aims to examine the levels of participation, categories of participants and the structure of their interactions in a forum. A convenience sampling of one course coordinator and 23 graduate students was selected in this study. The forums’ log file and the Social Network Analysis software were used in this study. The analysis reveals 610 activities (including viewing forum’s topic, viewing discussion thread, posting a new thread, replying to other participants’ post, updating an existing thread and deleting a post) performed by them in this forum, with an average of 3.83 threads posted. Also, this forum consists of five at-risk participants, six bridging participants, four isolated participants and five leaders of information. In addition, the network density value is 0.15 and there exist five reciprocal interactions in this forum. The closeness value varied between 28 and 68 while the eigen vector centrality value varied between 0.008 and 0.39. The finding indicates that the participants tend to listen more rather than express their opinions in the forum. It was also revealed that those who actively provide supports in the discussion forum were not the same people who received the most responses from their peers. This study found that cliques do not exist in the forum and the participants are not selective to whom they response to, rather, it was based on the content of the posts made by their peers. Based upon the findings, further analysis with different method and population, larger sample size and a longer time frame are recommended.

Keywords: e-learning, learning management system, online forum, social network analysis

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Asim Qayyum, David Smith

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The use of information tools is a common activity for students of any educational stage when they encounter online learning activities. Finding the relevant information for particular learning tasks is the topic of this paper as it investigates the use of information tools for a group of student participants. The paper describes and discusses the results with particular implications for use in higher education, and the findings suggest that improvement in assessment design and subsequent student learning may be achieved by structuring the purposefulness of information tools usage and online reading behaviors of university students.

Keywords: information tools, assessment, online learning, student assessment experience

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Authors: M. Van Zyl, M. H. A. Combrinck, E. J. Spamer

Abstract:

Due to the need for higher education in South Africa, the country experiences a rapid growth in open distance learning, especially in rural areas. It is difficult for people to enrol fulltime at contact universities, owing to work and financial constraints. The Unit for Open Distance Learning (UODL) at the North-West University (NWU), Potchefstroom campus, South Africa was established in 2013 with its main function to deliver open distance learning programmes to 30 000 students from the Faculties of Education Sciences, Theology and Health Sciences. With the use of interactive whiteboards (IWBs), the NWU and UODL are now able to deliver lectures to students concurrently at 60 regional open learning centres across Southern Africa as well as to an unlimited number of individuals with Internet access worldwide. Although IWBs are not new, our initiative is to use them more extensively in order to create more contact between lecturers and students. To be able to ensure and enhance quality education it is vital to determine students’ perceptions on the delivery of programmes by means of IWBs. Therefore, the aim of the study is to explore students’ perceptions for the use of IWBs in the delivery of programmes in terms of Moore’s Theory of Transactional Distance.

Keywords: interactive white board, open distance learning, technology, transactional learning

Procedia PDF Downloads 452

Authors: M. Zezou

Abstract:

This paper focuses on the design of a Massive Open Online Course (MOOC) about Content Language Integrated Learning (CLIL) and more specifically about how teachers can use CLIL as an educational approach incorporating technology in their teaching as well. All the four weeks of the MOOC will be presented and a step-by-step analysis of each lesson will be offered. Additionally, the paper includes detailed lesson plans about CLIL lessons with proposed CLIL activities and games in which technology plays a central part. The MOOC is structured based on certain criteria, in order to ensure success, as well as a positive experience that the learners need to have after completing this MOOC. It addresses to all language teachers who would like to implement CLIL into their teaching. In other words, it presents the methodology that needs to be followed so as to successfully carry out a CLIL lesson and achieve the learning objectives set at the beginning of the course. Firstly, in this paper, it is very important to give the definitions of MOOCs and LMOOCs, as well as to explore the difference between a structure-based MOOC (xMOOC) and a connectivist MOOC (cMOOC) and present the criteria of a successful MOOC. Moreover, the notion of CLIL will be explored, as it is necessary to fully understand this concept before moving on to the design of the MOOC. Onwards, the four weeks of the MOOC will be introduced as well as lesson plans will be presented: The type of the activities, the aims of each activity and the methodology that teachers have to follow. Emphasis will be placed on the role of technology in foreign language learning and on the ways in which we can involve technology in teaching a foreign language. Final remarks will be made and a summary of the main points will be offered at the end.

Keywords: CLIL, cMOOC, lesson plan, LMOOC, MOOC criteria, MOOC, technology, xMOOC

Procedia PDF Downloads 186

Authors: Xhevrie Mamaqi

Abstract:

Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

Procedia PDF Downloads 296