Search results for: application based learning

Authors: Matthew Montebello

Abstract:

Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

Procedia PDF Downloads 177

Authors: Isah Mohammed Patizhiko

Abstract:

This paper aimed at discussing the important role learning resources play in enhancing the teaching and learning of science and technology courses in post primary institution in Nigeria. The paper highlighted the importance learning resources contributed to the effective understanding of the learners. The use of learning resources in the teaching of these courses will encourage teachers to be more exploratory and the learners to have more understanding. In this paper, different range of learning resources particularly common learning resources (learning resources not design primarily for education purposes) to enrich their teaching. The paper also highlighted how ordinary resource can be turned into an educational resource. Recommendations were proffered in the sourcing of learning resources ie from the market, library, institutions, museums, and dump refuse and concluded that good demonstration on the use of resources will engage the learner’s interest and will develop higher level of conceptual understanding in the learning area.

Keywords: enhance, learning, resources, science and technology, teaching

Procedia PDF Downloads 374

Authors: Megha Gupta, Nupur Prakash

Abstract:

Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

Procedia PDF Downloads 172

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

Abstract:

In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

Procedia PDF Downloads 212

Authors: Liu Yi Hui, Chun-Liang Lai, Jhang Yu Cih, He You Jing, Chiu Fan-Yun, Lin Yu Fang

Abstract:

For universities offering long-term care education, the inclusion of adulting learning and practices in professional courses as appropriate based on holistic design and evaluation could improve talent empowerment by leveraging social capital. Moreover, it could make the courses and materials used in long-term care education responsive to real-life needs. A mixed research method was used in the research design. A quantitative study was also conducted using a questionnaire survey, and the data were analyzed by SPSS 22.0 Chinese version. The qualitative data included students’ learning files (learning reflection notes, course reports, and experience records).

Keywords: adult learning, community empowerment, social capital, mixed research

Procedia PDF Downloads 131

Authors: Yeo Leng Leng

Abstract:

Blended learning, with its combination of online and face-to-face instruction, presents a unique set of challenges and opportunities in terms of cultivating student agency. While it offers flexibility and personalized learning pathways, it also demands a higher degree of self-regulation and motivation from students. This paper presents the design of blended learning in a Chinese lesson and discusses the framework involved. It also talks about the Edtech tools adopted to engage the students. Some of the students’ works will be showcased. A qualitative case study research method was employed in this paper to find out more about students’ learning experiences and to give them a voice. The purpose is to seek improvement in the blended learning design of the Chinese lessons and to encourage students’ self-directed learning.

Keywords: blended learning, student agency, ed-tech tools, self-directed learning

Procedia PDF Downloads 52

Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

Abstract:

In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

Procedia PDF Downloads 345

Authors: Thapanee Musiget

Abstract:

Ethnic minority children’s language learning is believed that it can be developed through school system. However, many cases prove that these kids are left to challenge with multicultural context at school and sometimes decreased the ability to acquire new learning. Consequently, it is significant for ethnicity parents to consider that prompting their children at home before their actual school age can eliminate negative outcome of children's language acquisition. This paper discusses the approach of instructional use of parents and children language learning in the context of minority language group in Thailand. By conducting this investigation, secondary source of data was gathered with the purpose to point out some primary methods for parents and children in ethnicity. The process of language learning is based on the sociocultural theory of Vygotsky, which highlights expressive communication among individuals as the best motivating force in human development and learning. The article also highlights the role of parents as they lead the instruction approach. In the discussion part, the role of ethnic minority parents as a language instructor is offered as mediator.

Keywords: ethnic minority, language learning, multicultural context, sociocultural theory

Procedia PDF Downloads 364

Authors: Joshefina Bengoechea Fernandez, Alex Bell

Abstract:

In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 81

Authors: Dohun Kim

Abstract:

Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

Procedia PDF Downloads 171

Authors: Shan Jiang, Xinyu Tang

Abstract:

Game-based learning is an emerging pedagogy to make the learning experience more effective, enjoyable, and fun. However, most games used in classroom settings have been overly simplistic. This paper presents a case study on a Python-based online game designed to improve the effectiveness in both teaching and research in higher education. The proposed game system not only creates a fun and enjoyable experience for students to learn various topics in programming but also improves the effectiveness of teaching in several aspects, including material presentation, helping students to recognize the importance of the subjects, and linking theoretical concepts to practice. The proposed game system also serves as an information cyber-infrastructure that automatically collects and stores data from players. The data could be useful in research areas including human-computer interaction, decision making, opinion mining, and artificial intelligence. They further provide other possibilities beyond these areas due to the customizable nature of the game.

Keywords: game-based learning, programming, research-teaching integration, Hearthstone

Procedia PDF Downloads 144

Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

Abstract:

Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

Procedia PDF Downloads 117

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 59

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 76

Authors: Rattama Rattanawongsa

Abstract:

As technologies continue to develop and evolve, online learning has become one of the most popular ways of gaining access to learning. Worldwide, many students are engaging in both online and blended courses in growing numbers through e-learning. However, online learning is a form of teaching that has many benefits for learners but still has some limitations. The high attrition rates of students tend to be due to lack of motivation to succeed. Gamification is the use of game design techniques, game thinking and game mechanics in non-game context, such as learning. The gamifying method can motivate students to learn with fun and inspire them to continue learning. This paper aims to describe how the gamification work in the context of learning. The first part of this paper present the concept of gamification. The second part is described the psychological perspectives of gamification, especially motivation and flow theory for gamifying design. The result from this study will be described into the guidelines for effective learning design using a gamification concept.

Keywords: gamification, e-learning, motivation, flow theory

Procedia PDF Downloads 503

Authors: Erhan Eroğlu

Abstract:

This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

Procedia PDF Downloads 210

Authors: Komon Paisal

Abstract:

The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: constructivism, learning management, mathematics analysis courses, learning activity

Procedia PDF Downloads 514

Authors: Matthew Montebello

Abstract:

The way e-learning effectiveness has been notoriously measured within an academic setting is by comparing the e-learning medium to the traditional face-to-face teaching methodology. In this paper, a simple yet innovative comparison methodology is introduced, whereby the effectiveness of next generation e-learning systems are assessed in contrast not only to the face-to-face mode, but also to the classical e-learning modality. Ethical and logistical issues are also discussed, as this three-way approach to compare teaching methodologies was applied and documented in a real empirical study within a higher education institution.

Keywords: e-learning effectiveness, higher education, teaching modality comparison

Procedia PDF Downloads 365

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

Procedia PDF Downloads 175

Authors: Leena Alfarani

Abstract:

Although mobile devices are ubiquitous on university campuses, teacher-readiness for mobile learning has yet to be fully explored in the non-western nations. This study shows that two main factors affect the adoption and use of m-learning among female teachers within a university in Saudi Arabia—resistance to change and perceived social culture. These determinants of the current use and intention to use of m-learning were revealed through the analysis of an online questionnaire completed by 165 female faculty members. This study reveals several important issues for m-learning research and practice. The results further extend the body of knowledge in the field of m-learning, with the findings revealing that resistance to change and perceived social culture are significant determinants of the current use of and the intention to use m-learning.

Keywords: blended learning, mobile learning, technology adoption, devices

Procedia PDF Downloads 446

Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

Procedia PDF Downloads 20

Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria

Abstract:

Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.

Keywords: basic life support, paediatric basic life support, web-based learning, blended learning

Procedia PDF Downloads 53

Authors: Avinash Malladhi

Abstract:

Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

Procedia PDF Downloads 66

Authors: Muhammad Nawaz, Sandeep N. Kundu, Farha Sattar

Abstract:

Augmented reality sandbox adds new dimensions to education and learning process. It can be a core component of geoscience teaching and learning to understand the geographic contexts and landform processes. Augmented reality sandbox is a useful tool not only to create an interactive learning environment through spatial visualization but also it can provide an active learning experience to students and enhances the cognition process of learning. Augmented reality sandbox can be used as an interactive learning tool to teach geomorphic and landform processes. This article explains the augmented reality sandbox and the constructivism approach for geoscience teaching and learning, and endeavours to explore the ways to teach the geographic processes using the three-dimensional digital environment for the deep learning of the geoscience concepts interactively.

Keywords: augmented reality sandbox, constructivism, deep learning, geoscience

Procedia PDF Downloads 377

Authors: Giorgi Gaganidze, Eter Kharaishvili

Abstract:

The atypical crisis has created new challenges in the education system. Globally, including in Georgia, traditional methods of managing the education system have appeared particularly vulnerable. In addition, new opportunities for the introduction of innovative management of learning processes have emerged. The aim of the research is to identify the main challenges in the field of education management in the distance learning process in Georgia and to develop recommendations on the opportunities for the introduction of innovative management. The paper substantiates the relevance of the research, in particular, it notes that in Georgia, as in many countries, distance learning in higher education institutions became particularly crucial during the Covid-19 pandemic. What is more, theoretical and practical aspects of distance learning are less proven, and a number of problems have been identified in the field of education management in Georgia. The article justifies the need to study the challenges of distance learning for the formation of a sustainable education management system. Within the bibliographic research, there are grouped the opinions of researchers on the modern problems of distance learning and education management in the article. Based on scientific papers, the expectations formed about distance learning are studied, and the main focus is on the existing problems of education management during the atypical crisis. The article discusses the forms and opportunities of distance learning in different countries, evaluates different approaches and challenges to distance learning, and justifies the role of education management in effective distance learning. The paper uses various theoretical-methodological tools of research, including desk research on the research topic; Data selection-grouping, problem identification is carried out by analysis, synthesis, sampling, induction, and other methods;SWOT analysis is used to assess the strengths, weaknesses, opportunities, and threats of distance education and management; The level of student satisfaction with distance learning is determined through the Population-based / Census-based approach; The results of the research are processed by SPSS program. Quantitative research and semi-structured interviews with relevant focus groups were conducted to identify working directions for innovative management of distance learning and education. Research has shown that the demand for distance education is growing in Georgia, but the need to introduce innovative education management remains a particular challenge. Conclusions have been made on the introduction of innovative education management, and the relevant recommendations have been developed.

Keywords: distance learning, management challenges, education management, innovative management

Procedia PDF Downloads 113

Authors: Jagannath P. Tegar

Abstract:

The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

Procedia PDF Downloads 57

Authors: Vishnu Pratap Singh Kirar

Abstract:

Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

Procedia PDF Downloads 474

Authors: Jui Hsuan Hung, Jeng Yi Tzeng

Abstract:

Engineering education in the higher education is always male dominated. Therefore, women learning in this environment is an important research topic for feminists, gender researchers and engineering education researchers, especially in the era of gender mainstreaming. The research topics are from the dialectical discussion of feminism and science development history, gender issues of science education, to the subject choice of female students. These researches enrich the field of gender study in engineering education but lack of describing the detailed images of women in engineering education, including their learning, obstacles, needs or feelings. Otherwise, in order to keep up with the industrial trends of emphasizing group collaboration, engineering education turns from traditional lecture to creative group inquiry pedagogy in recent years. Creative project based learning is one of the creative group inquiry pedagogy which the engineering education in higher education adopts often, and it is seen as a gender-inclusive pedagogy in engineering education. Therefore, in order to understand the real situation of women learning in engineering education, this study took place in a course (Introduction to Engineering) offered by the school of engineering of a university in Taiwan. This course is designed for freshman students to establish basic understanding engineering from four departments (Chemical Engineering, Power Mechanical Engineering, Materials Science, Industrial Engineering and Engineering Management). One section of this course is to build a Hydraulic Robot designed by the Department of Power Mechanical Engineering. 321 students in the school of engineering took this course and all had the reflection questionnaire. These students are divided into groups of 5 members to work on this project. The videos of process of discussion of five volunteered groups with different gender composition are analyzed, and six women of these five groups are interviewed. We are still on the process of coding and analyzing videos and the qualitative data, but several tentative findings have already emerged. (1) The activity models of groups of both genders are gender segregation, and not like women; men never be the ‘assistants’. (2) The culture of the group is developed by the major gender, but men always dominate the process of practice in all kinds of gender composition groups. (3) Project based learning is supposed to be a gender-inclusive learning model in creative engineering education, but communication obstacles between men and women make it less women friendly. (4) Gender identity, not professional identity, is adopted by these women while they interact with men in their groups. (5) Gender composition and project-based learning pedagogy are not the key factors for women learning in engineering education, but the gender conscience awareness is.

Keywords: engineering education, gender education, creative project based learning, women learning

Procedia PDF Downloads 283

Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

Abstract:

The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

Procedia PDF Downloads 426

Authors: Rafia Rafique, Arifa Khadim

Abstract:

This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 415