Search results for: online and adaptive learning
9584 Efficient Fake News Detection Using Machine Learning and Deep Learning Approaches
Authors: Chaima Babi, Said Gadri
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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification
Procedia PDF Downloads 959583 Estimation of Rare and Clustered Population Mean Using Two Auxiliary Variables in Adaptive Cluster Sampling
Authors: Muhammad Nouman Qureshi, Muhammad Hanif
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Adaptive cluster sampling (ACS) is specifically developed for the estimation of highly clumped populations and applied to a wide range of situations like animals of rare and endangered species, uneven minerals, HIV patients and drug users. In this paper, we proposed a generalized semi-exponential estimator with two auxiliary variables under the framework of ACS design. The expressions of approximate bias and mean square error (MSE) of the proposed estimator are derived. Theoretical comparisons of the proposed estimator have been made with existing estimators. A numerical study is conducted on real and artificial populations to demonstrate and compare the efficiencies of the proposed estimator. The results indicate that the proposed generalized semi-exponential estimator performed considerably better than all the adaptive and non-adaptive estimators considered in this paper.Keywords: auxiliary information, adaptive cluster sampling, clustered populations, Hansen-Hurwitz estimation
Procedia PDF Downloads 2389582 Hate Speech Detection Using Machine Learning: A Survey
Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile
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Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection
Procedia PDF Downloads 1779581 University Short Courses Web Application Using ASP.Net
Authors: Ahmed Hariri
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E-Learning has become a necessity in the advanced education. It is easier for the student and teacher communication also it speed up the process with less time and less effort. With the progress and the enormous development of distance education must keep up with this age of making a website that allows students and teachers to take all the advantages of advanced education. In this regards, we developed University Short courses web application which is specially designed for Faculty of computing and information technology, Rabigh, Kingdom of Saudi Arabia. After an elaborate review of the current state-of-the-art methods of teaching and learning, we found that instructors deliver extra short courses and workshop to students to enhance the knowledge of students. Moreover, this process is completely manual. The prevailing methods of teaching and learning consume a lot of time; therefore in this context, University Short courses web application will help to make process easy and user friendly. The site allows for students can view and register short courses online conducted by instructor also they can see courses starting dates, finishing date and locations. It also allows the instructor to put things on his courses on the site and see the students enrolled in the study material. Finally, student can print the certificate after finished the course online. ASP.NET, SQLSERVER, JavaScript SQL SERVER Database will use to develop the University Short Courses web application.Keywords: e-learning, short courses, ASP.NET, SQL SERVER
Procedia PDF Downloads 1349580 Impact of Grade Sensitivity on Learning Motivation and Academic Performance
Authors: Salwa Aftab, Sehrish Riaz
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The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression
Procedia PDF Downloads 4009579 Role of Feedbacks in Simulation-Based Learning
Authors: Usman Ghani
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Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.Keywords: simulation, feedback, training, hands-on, labs
Procedia PDF Downloads 3779578 The Impact of Artificial Intelligence on E-Learning
Authors: Sameil Hanna Samweil Botros
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The variation of social networking websites inside higher training has garnered enormous hobby in recent years, with numerous researchers thinking about it as a possible shift from the conventional lecture room-based learning paradigm. However, this boom in research and carried out research, but the adaption of SNS-based modules has not proliferated inside universities. This paper commences its contribution with the aid of studying the numerous fashions and theories proposed in the literature and amalgamates together various effective aspects for the inclusion of social technology within e-gaining knowledge. A three-phased framework is similarly proposed, which informs the important concerns for the hit edition of SNS in improving the student's mastering experience. This suggestion outlines the theoretical foundations as a way to be analyzed in sensible implementation across worldwide university campuses.Keywords: eLearning, institutionalization, teaching and learning, transformation vtuber, ray tracing, avatar agriculture, adaptive, e-learning, technology eLearning, higher education, social network sites, student learning
Procedia PDF Downloads 259577 Adaptive Online Object Tracking via Positive and Negative Models Matching
Authors: Shaomei Li, Yawen Wang, Chao Gao
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To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as a binary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm cannot only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.Keywords: object tracking, tracking drift, partial least squares analysis, positive and negative models matching
Procedia PDF Downloads 5299576 E–Learning System in Virtual Learning Environment to Develop Problem Solving Ability and Team Learning for Learners in Higher Education
Authors: Noawanit Songkram
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This paper is a report on the findings of a study conducted on e–learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education. The methodology of this study was R&D research. The subjects were 18 undergraduate students in Faculty of Education, Chulalongkorn University in the academic year of 2013. The research instruments were a problem solving ability assessment, a team learning evaluation form, and an attitude questionnaire. The data was statistically analyzed using mean, standard deviation, one way repeated measure ANOVA and t–test. The research findings discovered the e –learning system in virtual learning environment to develop problem solving ability and team learning for learners in higher education consisted of five components:(1) online collaborative tools, (2) active learning activities, (3) creative thinking, (4) knowledge sharing process, (5) evaluation and nine processes which were (1) preparing in group working, (2) identifying interested topic, (3) analysing interested topic, (4) collecting data, (5) concluding idea (6) proposing idea, (7) creating workings, (8) workings evaluation, (9) sharing knowledge from empirical experience.Keywords: e-learning system, problem solving ability, team leaning, virtual learning environment
Procedia PDF Downloads 4389575 Challenges and Success Factors in Introducing Information Systems for Students' Online Registration
Authors: Stanley Fore, Sharon Chipeperekwa
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The start of the 2011 academic year in South Africa saw a number of Institutions of Higher Learning introducing online registration for their students. The efficiency and effectiveness of Information Systems are increasingly becoming a necessity and not an option for many organizations. An information system should be able to allow end users to access information easily and navigate with ease. The selected University of Technology (UoT) in this research is one of the largest public institution of higher learning in the Western Cape Province and boasts of an enrolment of more than 30000 students per academic year. An observation was made that, during registration students’ stand in long queues waiting to register or for assistance to register. The system tends to ‘freeze’ whilst students are registering and students are in most cases unfamiliar with the system interface. They constantly have to enquire what to do next when going through online registration process. A mixed method approach will be adopted which comprises of quantitative and qualitative approaches. The study uses constructs of the updated DeLone and McLean IS success model (2003) to analyse and explain the student’s perceptions of the online registration system. The research was undertaken to establish the student’s perceptions of the online registration system. This research seeks to identify and analyse the challenges and success factors of introducing an online registration system whilst highlighting the extent to which this system has been able to solve the numerous problems associated with the manual era. The study will assist management and those responsible for managing the current system to determine how well the system is working or not working to achieve user satisfaction. It will also assist them going forward on what to consider before, during and after implementation of an information system. Respondents will be informed of the objectives of the research, and their consent to participate will be sought. Ethical considerations that will be applied to this study include; informed consent and protection from harm, right to privacy and involvement of the research.Keywords: online registration, information systems, University of Technology, end-users
Procedia PDF Downloads 2589574 Comparison Analysis of Multi-Channel Echo Cancellation Using Adaptive Filters
Authors: Sahar Mobeen, Anam Rafique, Irum Baig
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Acoustic echo cancellation in multichannel is a system identification application. In real time environment, signal changes very rapidly which required adaptive algorithms such as Least Mean Square (LMS), Leaky Least Mean Square (LLMS), Normalized Least Mean square (NLMS) and average (AFA) having high convergence rate and stable. LMS and NLMS are widely used adaptive algorithm due to less computational complexity and AFA used of its high convergence rate. This research is based on comparison of acoustic echo (generated in a room) cancellation thorough LMS, LLMS, NLMS, AFA and newly proposed average normalized leaky least mean square (ANLLMS) adaptive filters.Keywords: LMS, LLMS, NLMS, AFA, ANLLMS
Procedia PDF Downloads 5669573 Students' Statistical Reasoning and Attitudes towards Statistics in Blended Learning, E-Learning and On-Campus Learning
Authors: Petros Roussos
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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning
Procedia PDF Downloads 3109572 Building Community through Discussion Forums in an Online Accelerated MLIS Program: Perspectives of Instructors and Students
Authors: Mary H Moen, Lauren H. Mandel
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Creating a sense of community in online learning is important for student engagement and success. The integration of discussion forums within online learning environments presents an opportunity to explore how this computer mediated communications format can cultivate a sense of community among students in accelerated master’s degree programs. This research has two aims, to delve into the ways instructors utilize this communications technology to create community and to understand the feelings and experiences of graduate students participating in these forums in regard to its effectiveness in community building. This study is a two-phase approach encompassing qualitative and quantitative methodologies. The data will be collected at an online accelerated Master of Library and Information Studies program at a public university in the northeast of the United States. Phase 1 is a content analysis of the syllabi from all courses taught in the 2023 calendar year, which explores the format and rules governing discussion forum assignments. Four to six individual interviews of department faculty and part time faculty will also be conducted to illuminate their perceptions of the successes and challenges of their discussion forum activities. Phase 2 will be an online survey administered to students in the program during the 2023 calendar year. Quantitative data will be collected for statistical analysis, and short answer responses will be analyzed for themes. The survey is adapted from the Classroom Community Scale Short-Form (CSS-SF), which measures students' self-reported responses on their feelings of connectedness and learning. The prompts will contextualize the items from their experience in discussion forums during the program. Short answer responses on the challenges and successes of using discussion forums will be analyzed to gauge student perceptions and experiences using this type of communication technology in education. This research study is in progress. The authors anticipate that the findings will provide a comprehensive understanding of the varied approaches instructors use in discussion forums for community-building purposes in an accelerated MLIS program. They predict that the more varied, flexible, and consistent student uses of discussion forums are, the greater the sense of community students will report. Additionally, students’ and instructors’ perceptions and experiences within these forums will shed light on the successes and challenges faced, thereby offering valuable recommendations for enhancing online learning environments. The findings are significant because they can contribute actionable insights for instructors, educational institutions, and curriculum designers aiming to optimize the use of discussion forums in online accelerated graduate programs, ultimately fostering a richer and more engaging learning experience for students.Keywords: accelerated online learning, discussion forums, LIS programs, sense of community, g
Procedia PDF Downloads 839571 Beyond Personal Evidence: Using Learning Analytics and Student Feedback to Improve Learning Experiences
Authors: Shawndra Bowers, Allie Brandriet, Betsy Gilbertson
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This paper will highlight how Auburn Online’s instructional designers leveraged student and faculty data to update and improve online course design and instructional materials. When designing and revising online courses, it can be difficult for faculty to know what strategies are most likely to engage learners and improve educational outcomes in a specific discipline. It can also be difficult to identify which metrics are most useful for understanding and improving teaching, learning, and course design. At Auburn Online, the instructional designers use a suite of data based student’s performance, participation, satisfaction, and engagement, as well as faculty perceptions, to inform sound learning and design principles that guide growth-mindset consultations with faculty. The consultations allow the instructional designer, along with the faculty member, to co-create an actionable course improvement plan. Auburn Online gathers learning analytics from a variety of sources that any instructor or instructional design team may have access to at their own institutions. Participation and performance data, such as page: views, assignment submissions, and aggregate grade distributions, are collected from the learning management system. Engagement data is pulled from the video hosting platform, which includes unique viewers, views and downloads, the minutes delivered, and the average duration each video is viewed. Student satisfaction is also obtained through a short survey that is embedded at the end of each instructional module. This survey is included in each course every time it is taught. The survey data is then analyzed by an instructional designer for trends and pain points in order to identify areas that can be modified, such as course content and instructional strategies, to better support student learning. This analysis, along with the instructional designer’s recommendations, is presented in a comprehensive report to instructors in an hour-long consultation where instructional designers collaborate with the faculty member on how and when to implement improvements. Auburn Online has developed a triage strategy of priority 1 or 2 level changes that will be implemented in future course iterations. This data-informed decision-making process helps instructors focus on what will best work in their teaching environment while addressing which areas need additional attention. As a student-centered process, it has created improved learning environments for students and has been well received by faculty. It has also shown to be effective in addressing the need for improvement while removing the feeling the faculty’s teaching is being personally attacked. The process that Auburn Online uses is laid out, along with the three-tier maintenance and revision guide that will be used over a three-year implementation plan. This information can help others determine what components of the maintenance and revision plan they want to utilize, as well as guide them on how to create a similar approach. The data will be used to analyze, revise, and improve courses by providing recommendations and models of good practices through determining and disseminating best practices that demonstrate an impact on student success.Keywords: data-driven, improvement, online courses, faculty development, analytics, course design
Procedia PDF Downloads 609570 Approaches and Strategies Used to Increase Student Engagement in Blended Learning Courses
Authors: Pinar Ozdemir Ayber, Zeina Hojeij
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Blended Learning (BL) is a rapidly growing teaching and learning approach, which brings together the best of both face-to-face and online learning to expand learning opportunities for students. However, there is limited research on the practices, opportunities and quality of instruction in Blended Classrooms, and on the role of the teaching faculty as well as the learners in these types of classes. This paper will highlight the researchers’ experiences and reflections on blending their classes. It will focus on the importance of designing effective lesson plans that emphasize learner engagement and motivation in alignment with course learning outcomes. In addition, it will identify the changing roles of the teacher and the learners and suggest appropriate variations to the traditional classroom setting taking into consideration the benefits and the challenges of the Blended Classroom. It is hoped that this paper would provide sufficient input for participants to reflect on ways they can blend their own lessons to promote ubiquitous learning and student autonomy. Practical tips and ideas will be shared with the participants on various strategies and technologies that were used in the researchers’ classes.Keywords: blended learning, learner autonomy, learner engagement, learner motivation, mobile learning tools
Procedia PDF Downloads 3039569 Towards Expanding the Use of the Online Judge UnitJudge for Java Programming Exercises and Web Development Practices in Computer Science Education
Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández
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Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.Keywords: online judges, programming skills, computer science education, auto-evaluation
Procedia PDF Downloads 1009568 Exploring Perspectives and Complexities of E-tutoring: Insights from Students Opting out of Online Tutor Service
Authors: Prince Chukwuneme Enwereji, Annelien Van Rooyen
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In recent years, technology integration in education has transformed the learning landscape, particularly in online institutions. One technological advancement that has gained popularity is e-tutoring, which offers personalised academic support to students through online platforms. While e-tutoring has become well-known and has been adopted to promote collaborative learning, there are still students who do not use these services for various reasons. However, little attention has been given to understanding the perspectives of students who have not utilized these services. The research objectives include identifying the perceived benefits that non-e-tutoring students believe e-tutoring could offer, such as enhanced academic support, personalized learning experiences, and improved performance. Additionally, the study explored the potential drawbacks or concerns that non-e-tutoring students associate with e-tutoring, such as concerns about efficacy, a lack of face-to-face interaction, and platform accessibility. The study adopted a quantitative research approach with a descriptive design to gather and analyze data on non-e-tutoring students' perspectives. Online questionnaires were employed as the primary data collection method, allowing for the efficient collection of data from many participants. The collected data was analyzed using the Statistical Package for the Social Sciences (SPSS). Ethical concepts such as informed consent, anonymity of responses and protection of respondents against harm were maintained. Findings indicate that non-e-tutoring students perceive a sense of control over their own pace of learning, suggesting a preference for self-directed learning and the ability to tailor their educational experience to their individual needs and learning styles. They also exhibit high levels of motivation, believe in their ability to effectively participate in their studies and organize their academic work, and feel comfortable studying on their own without the help of e-tutors. However, non-e-tutoring students feel that e-tutors do not sufficiently address their academic needs and lack engagement. They also perceive a lack of clarity in the roles of e-tutors, leading to uncertainty about their responsibilities. In terms of communication, students feel overwhelmed by the volume of announcements and find repetitive information frustrating. Additionally, some students face challenges with their internet connection and associated cost, which can hinder their participation in online activities. Furthermore, non-e-tutoring students express a desire for interactions with their peers and a sense of belonging to a group or team. They value opportunities for collaboration, teamwork in their learning experience, the importance of fostering social interactions and creating a sense of community in online learning environments. This study recommended that students seek alternate support systems by reaching out to professors or academic advisors for guidance and clarification. Developing self-directed learning skills is essential, empowering students to take charge of their own learning through setting objectives, creating own study plans, and utilising resources. For HEIs, it was recommended that they should ensure that a variety of support services are available to cater to the needs of all students, including non-e-tutoring students. HEIs should also ensure easy access to online resources, promote a supportive community, and regularly evaluate and adapt their support techniques to meet students' changing requirements.Keywords: online-tutor;, student support;, online education, educational practices, distance education
Procedia PDF Downloads 829567 Active Learning Strategies to Develop Student Skills in Information Systems for Management
Authors: Filomena Lopes, Sandra Fernandes
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Active learning strategies are at the center of any change process aimed to improve the development of student skills. This paper aims to analyse the impact of teaching strategies, including problem-based learning (PBL), in the curricular unit of information system for management, based on students’ perceptions of how they contribute to develop the desired learning outcomes of the curricular unit. This course is part of the 1st semester and 3rd year of the graduate degree program in management at a private higher education institution in Portugal. The methodology included an online questionnaire to students (n=40). Findings from students reveal a positive impact of the teaching strategies used. In general, 35% considered that the strategies implemented in the course contributed to the development of courses’ learning objectives. Students considered PBL as the learning strategy that better contributed to enhance the courses’ learning outcomes. This conclusion brings forward the need for further reflection and discussion on the impact of student feedback on teaching and learning processes.Keywords: higher education, active learning strategies, skills development, student assessment
Procedia PDF Downloads 609566 Perception of Inclusion in Higher Education
Authors: Hoi Nga Ng, Kam Weng Boey, Chi Wai Kwan
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Supporters of Inclusive education proclaim that all students, regardless of disabilities or special educational needs (SEN), have the right to study in the normal school setting. It is asserted that students with SEN would benefit in academic performance and psychosocial adjustment via participation in common learning activities within the ordinary school system. When more and more students of SEN completed their early schooling, institute of higher education become the setting where students of SEN continue their learning. This study aimed to investigate the school well-being, social relationship, and academic self-concept of students of SEN in higher education. The Perception of Inclusion Questionnaire (PIQ) was used as the measuring instruments. PIQ was validated and incorporated in a questionnaire designed for online survey. Participation was voluntary and anonymous. A total of 90 students with SEN and 457 students without SEN responded to the online survey. Results showed no significant differences in school well-being and social relationship between students with and without SEN, but students with SEN, particularly those with learning and development impairment and those with mental illness and emotional problems, were significantly poorer in academic self-concept. Implications of the findings were discussed.Keywords: ccademic self-concept, school well-being, social relationship, special educational needs
Procedia PDF Downloads 1839565 A Comparison between Virtual Case-Based Learning and Traditional Learning: The Effect on Undergraduate Nursing Students’ Performance during Covid-19: A Pilot Study
Authors: Aya M. Aboudesouky
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Covid-19 has changed and affected the whole world dramatically in a new way that the entire world, even scientists, have not imagined before. The educational institutions around the world have been fighting since Covid-19 hit the world last December to keep the educational process unchanged for all students. E-learning was a must for almost all US universities during the pandemic. It was specifically more challenging to use online case-based learning instead of regular classes among nursing students who take practical education. This study aims to examine the difference in performance and satisfaction between nursing students taking traditional education and those who take virtual case-based education during their practical study. This study enrolls 40 last-year nursing undergraduates from a mid-sized university in Western Pennsylvania. The study uses a convenient sample. Students will be divided into two groups; a control group that is exposed to traditional teaching strategy and a treatment group that is exposed to a case-based teaching strategy. The module designed for this study is a total parenteral nutrition (TPN) module that will be taught for one month. The treatment group (n=20) utilizes the virtual simulation of the CBL method, while the control group (n=20) uses the traditional lecture-based teaching method. Student evaluations are collected after a month by using the survey to attain the students’ learning satisfaction and self-evaluation of the course. The post-test is used to assess the end of the course performance.Keywords: virtual case-based learning, traditional education, nursing education, Covid-19 crisis, online practical education
Procedia PDF Downloads 1289564 Digital Design and Practice of The Problem Based Learning in College of Medicine, Qassim University, Saudi Arabia
Authors: Ahmed Elzainy, Abir El Sadik, Waleed Al Abdulmonem, Ahmad Alamro, Homaidan Al-Homaidan
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Problem-based learning (PBL) is an educational modality which stimulates critical and creative thinking. PBL has been practiced in the college of medicine, Qassim University, Saudi Arabia, since the 2002s with offline face to face activities. Therefore, crucial technological changes in paperless work were needed. The aim of the present study was to design and implement the digitalization of the PBL activities and to evaluate its impact on students' and tutors’ performance. This approach promoted the involvement of all stakeholders after their awareness of the techniques of using online tools. IT support, learning resources facilities, and required multimedia were prepared. Students’ and staff perception surveys reflected their satisfaction with these remarkable changes. The students were interested in the new digitalized materials and educational design, which facilitated the conduction of PBL sessions and provided sufficient time for discussion and peer sharing of knowledge. It enhanced the tutors for supervision and tracking students’ activities on the Learning Management System. It could be concluded that introducing of digitalization of the PBL activities promoted the students’ performance, engagement and enabled a better evaluation of PBL materials and getting prompt students as well as staff feedback. These positive findings encouraged the college to implement the digitalization approach in other educational activities, such as Team-Based Learning, as an additional opportunity for further development.Keywords: multimedia in PBL, online PBL, problem-based learning, PBL digitalization
Procedia PDF Downloads 1209563 A Review of Machine Learning for Big Data
Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.
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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.Keywords: active learning, big data, deep learning, machine learning
Procedia PDF Downloads 4459562 Metamorphosis of Teaching-Learning During COVID-19 Crisis and Challenges of Education in India
Authors: Saroj Pandey
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COVID-19, declared by the World Health Organization a pandemic (WHO,2020), has created an unprecedented crisis world over endangering the human survival itself. Corona induced lockdowns forced approximately 140 million students of 190 countries at various levels of education from preprimary to higher education to remain confined to their homes. In India, approximately 360 million students were affected by the forced shut down of schools due to the countrywide lockdown in March 2020 and resultant disruption of education. After the initial shock and anxiety the Indian polity and education system bounced back with a number of initiatives, and online education came as a major rescuer for the education system of the country. The distance and online mode of learning that was treated as the poor cousin of conventional mode and often criticized for its quality became the major crusader overnight changing the entire ecosystem of traditional teaching -leaning towards the virtual mode. Teachers who were averse to technology were forced to remodel their educational pedagogies and reorient themselves overnight to use various online platforms such as Zoom, Google meet, and other such platforms to reach the learners. This metamorphosis through ensured students was meaningfully engaged in their studies during the lockdown period but it has its own set of challenges. This paper deals with the government initiatives, and teachers' self-efforts to keep the channel of teaching learning on providing academic and socio emotional support to students during the most difficult period of their life as well as the digital divide between the rich and poor, rural and urban, and boys and girls in India and resultant challenges. It also provides an overview of few significant self-initiatives of teachers to reach their students during the crisis period, who did not have internet and smartphone facilities as well as the initiatives being taken at the government level to address the learning needs and mitigate the learning gaps of learners, bridge the digital divide, strategic planning and upskilling of teachers to overcome the effect of COVID-19 crisis.Keywords: COVID-19, online education, initiatives, challenges
Procedia PDF Downloads 1149561 Review on Rainfall Prediction Using Machine Learning Technique
Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya
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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.Keywords: ANN, CNN, supervised learning, machine learning, deep learning
Procedia PDF Downloads 2019560 Teacher Mental Health during Online Teaching
Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi
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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.Keywords: mental health, teacher, COVID-19 pandemic, MHI-38
Procedia PDF Downloads 1839559 Identifying Learning Support Patterns for Enhancing Quality Outputs in Massive Open Online Courses
Authors: Cristina Galván-Fernández, Elena Barberà, Jingjing Zhang
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In recent years, MOOCs have been in the spotlight for its high drop-out rates, which potentially impact on the quality of the learning experience. This study attempts to explore how learning support can be used to keep student retention, and in turn to improve the quality of learning in MOOCs. In this study, the patterns of learning support were identified from a total of 4202592 units of video sessions, clickstream data of 25600 students, and 382 threads generated in 10 forums (optional and mandatory) in five different types of MOOCs (e.g. conventional MOOCs, professional MOOCs, and informal MOOCs). The results of this study have shown a clear correlation between the types of MOOCs, the design framework of the MOOCs, and the learning support. The patterns of tutor-peer interaction are identified, and are found to be highly correlated with student retention in all five types of MOOCs. In addition, different patterns of ‘good’ students were identified, which could potentially inform the instruction design of MOOCs.Keywords: higher education, learning support, MOOC, retention
Procedia PDF Downloads 3359558 A Self-Adaptive Stimulus Artifacts Removal Approach for Electrical Stimulation Based Muscle Rehabilitation
Authors: Yinjun Tu, Qiang Fang, Glenn I. Matthews, Shuenn-Yuh Lee
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This paper reports an efficient and rigorous self-adaptive stimulus artifacts removal approach for a mixed surface EMG (Electromyography) and stimulus signal during muscle stimulation. The recording of EMG and the stimulation of muscles were performing simultaneously. It is difficult to generate muscle fatigue feature from the mixed signal, which can be further used in closed loop system. A self-adaptive method is proposed in this paper, the stimulation frequency was calculated and verified firstly. Then, a mask was created based on this stimulation frequency to remove the undesired stimulus. 20 EMG signal recordings were analyzed, and the ANOVA (analysis of variance) approach illustrated that the decreasing trend of median power frequencies was successfully generated from the 'cleaned' EMG signal.Keywords: EMG, FES, stimulus artefacts, self-adaptive
Procedia PDF Downloads 3999557 Analysis of Knowledge Circulation in Digital Learning Environments: A Case Study of the MOOC 'Communication des Organisations'
Authors: Hasna Mekkaoui Alaoui, Mariem Mekkaoui Alaoui
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In a context marked by a growing and pressing demand for online training within Moroccan universities, massive open online courses (Moocs) are undergoing constant evolution, amplified by the widespread use of digital technology and accentuated by the Coronavirus pandemic. However, despite their growing popularity and expansion, these courses are still lacking in terms of tools, enabling teachers and researchers to carry out a fine-grained analysis of the learning processes taking place within them. What's more, the circulation and sharing of knowledge within these environments is becoming increasingly important. The crucial aspect of traceability emerges here, as MOOCs record and generate traces from the most minute to the most visible. This leads us to consider traceability as a valuable approach in the field of educational research, where the trace is envisaged as a research tool in its own right. In this exploratory research project, we are looking at aspects of community knowledge sharing based on traces observed in the "Communication des organisations" Mooc. Focusing in particular on the mediating trace and its impact in identifying knowledge circulation processes in this learning space, we have mobilized the traces of video capsules as an index of knowledge circulation in the Mooc device. Our study uses a methodological approach based on thematic analysis, and although the results show that learners reproduce knowledge from different video vignettes in almost identical ways, they do not limit themselves to the knowledge provided to them. This research offers concrete perspectives for improving the dynamics of online devices, with a potentially positive impact on the quality of online university teaching.Keywords: circulation, index, digital environments, mediation., trace
Procedia PDF Downloads 639556 Exploring the Compatibility of The Rhizome and Complex Adaptive System (CAS) Theory as a Hybrid Urban Strategy Via Aggregation, Nonlinearity, and Flow
Authors: Sudaff Mohammed, Wahda Shuker Al-Hinkawi, Nada Abdulmueen Hasan
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The compatibility of the Rhizome and Complex Adaptive system theory as a strategy within the urban context is the essential interest of this paper since there are only a few attempts to establish a hybrid, multi-scalar, and developable strategy based on the concept of the Rhizome and the CAS theory. This paper aims to establish a Rhizomic CAS strategy for different urban contexts by investigating the principles, characteristics, properties, and mechanisms of Rhizome and Complex Adaptive Systems. The research focused mainly on analyzing three properties: aggregation, non-linearity, and flow through the lens of Rhizome, Rhizomatization of CAS properties. The most intriguing result is that the principal and well-investigated characteristics of Complex Adaptive systems can be ‘Rhizomatized’ in two ways; highlighting commonalities between Rhizome and Complex Adaptive systems in addition to using Rhizome-related concepts. This paper attempts to emphasize the potency of the Rhizome as an apparently stochastic and barely anticipatable structure that can be developed to analyze cities of distinctive contexts for formulating better customized urban strategies.Keywords: rhizome, complex adaptive system (CAS), system Theory, urban system, rhizomatic CAS, assemblage, human occupation impulses (HOI)
Procedia PDF Downloads 419555 Adaptive Routing in NoC-Based Heterogeneous MPSoCs
Authors: M. K. Benhaoua, A. E. H. Benyamina, T. Djeradi, P. Boulet
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In this paper, we propose adaptive routing that considers the routing of communications in order to optimize the overall performance. The routing technique uses a newly proposed Algorithm to route communications between the tasks. The routing we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed routing approach provides significant performance improvements when compared to those using static routing.Keywords: multi-processor systems-on-chip (mpsocs), network-on-chip (noc), heterogeneous architectures, adaptive routin
Procedia PDF Downloads 375