Search results for: LMS–learning management system

Authors: Somtop Keawchuer

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The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.

Keywords: happiness, learning satisfaction, students, Faculty of Management Science

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Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharana

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Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: computer assisted learning, intelligent tutoring system, learner centered design, mobile mediated learning and teacher education

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Authors: Mohsen Maraoui

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In the face of the growth in the quantity of data produced, several methods and techniques appear to remedy the problems of processing and analyzing large amounts of information mainly in the field of teaching. In this paper, we propose an intelligent cloud-based teaching system for E-learning content services. This system makes easy the manipulation of various educational content forms, including text, images, videos, 3 dimensions objects and scenes of virtual reality and augmented reality. We discuss the integration of institutional and external services to provide personalized assistance to university members in their daily activities. The proposed system provides an intelligent solution for media services that can be accessed from smart devices cloud-based intelligent service environment with a fully integrated system.

Keywords: cloud computing, e-learning, indexation, IoT, learning in Arabic language, smart tools

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Ilana Lavy, Rami Rashkovits

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In this study, we describe Information Systems students' learning model which was applied by students in order to cope with professional knowledge gaps in the context of their final project. The students needed to implement a software system according to specifications and design they have made beforehand. They had to select certain technologies and use them. Most of them decided to use programming environments that were learned during their academic studies. The students had to cope with various levels of knowledge gaps. For that matter they used learning strategies that were organized by us as a learning model which includes two phases each suitable for different learning tasks. We analyze the learning model, describing advantages and shortcomings as perceived by the students, and provide excerpts to support our findings.

Keywords: knowledge gaps, independent learner skills, self-regulated learning, final project

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Kittipong Tissayakorn, Fumio Akagi, Yu Song

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Logistics is the integrated management of all of the activities required to move products through the supply chain. For a typical product, this supply chain extends from a raw material source through the production and distribution system to the point of consumption and the associated reverse logistics. The logistical activities are comprised of freight transport, storage, inventory management, materials handling and all related information processing. This paper analyzes the green management system of logistics enterprise for Thailand and advances the concept of Green Logistics, which should be held by the public. In addition, it proposes that the government should strengthen its supervision and support for green logistics, and companies should construct self-disciplined green logistics management systems and corresponding processes, a reverse logistics management system and a modern green logistics information collection and management system.

Keywords: logistics, green logistics, management system, ecological economics

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Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

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Authors: Emin Gundogar, Aysegul Yilmaz

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Strategic performance control is a significant procedure in management. There are various methods to improve this procedure. This study introduces an information system that is developed to score performance for municipal management. The application of the system is clarified by exemplifying municipal processes.

Keywords: management information system, municipal management, performance control

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Authors: Maria Corazon Tapang-Lopez, Alyn Joy Dela Cruz Baltazar, Bobby Jones Villanueva Domdom

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The requisite for an organization implementing quality management system to sustain its compliance to the requirements and commitment for continuous improvement is even higher. It is expected that the offices and units has high and consistent compliance to the established processes and procedures. The Development Academy of the Philippines has been operating under project management to which is has a quality management certification. To further realize its mandate as a think-tank and capacity builder of the government, DAP expanded its operation and started to grant graduate degree through its Graduate School of Public and Development Management (GSPDM). As the academic arm of the Academy, GSPDM offers graduate degree programs on public management and productivity & quality aligned to the institutional trusts. For a time, the documented procedures and processes of a project management seem to fit the Graduate School. However, there has been a significant growth in the operations of the GSPDM in terms of the graduate programs offered that directly increase the number of students. There is an apparent necessity to align the project management system into a more educational system otherwise it will no longer be responsive to the development that are taking place. The strongly advocate and encourage its students to pursue internal and external improvement to cope up with the challenges of providing quality service to their own clients and to our country. If innovation will not take roots in the grounds of GSPDM, then how will it serve the purpose of “walking the talk”? This research was conducted to assess the diverse flow of the existing internal operations and processes of the DAP’s project management and GSPDM’s school management that will serve as basis to develop a system that will harmonize into one, the Learning Management System. The study documented the existing process of GSPDM following the project management phases of conceptualization & development, negotiation & contracting, mobilization, implementation, and closure into different flow charts of the key activities. The primary source of information as respondents were the different groups involved into the delivery of graduate programs - the executive, learning management team and administrative support offices. The Learning Management System (LMS) shall capture the unique and critical processes of the GSPDM as a degree-granting unit of the Academy. The LMS is the harmonized project management and school management system that shall serve as the standard system and procedure for all the programs within the GSPDM. The unique processes cover the three important areas of school management – student, curriculum, and faculty. The required processes of these main areas such as enrolment, course syllabus development, and faculty evaluation were appropriately placed within the phases of the project management system. Further, the research shall identify critical reports and generate manageable documents and records to ensure accuracy, consistency and reliable information. The researchers had an in-depth review of the DAP-GSDPM’s mandate, analyze the various documents, and conducted series of focused group discussions. A comprehensive review on flow chart system prior and various models of school management systems were made. Subsequently, the final output of the research is a work instructions manual that will be presented to the Academy’s Quality Management Council and eventually an additional scope for ISO certification. The manual shall include documented forms, iterative flow charts and program Gantt chart that will have a parallel development of automated systems.

Keywords: productivity, quality, learning management system, agency-based graduate school

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Authors: Peijen Pamela Chuang, Tzu-Hua Wang

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To address the notion of educational equity, undergo the global pandemic, a digital learning system was cross-disciplinarily designed by a 15-year-experienced teaching practitioner. A study was performed on students through the use of this pioneering e-learning system, in which Taiwanese students with different learning styles and special needs have a foreign language- English as the target subject. 121 students are particularly selected from an N= 580 sample spread across 20 inclusive and special education schools throughout districts of Taiwan. To bring off equity, the participants are selected from a mix of different socioeconomic statuses. Grouped data, such as classroom observation, individual learning preference, prerequisite knowledge, learning interest, and learning performance of the population, is carefully documented for further analyzation. The paper focuses on documenting the awareness and needs of this pedagogical methodology revolution, data analysis of UX (User Experience), also examination and system assessment of this system. At the time of the pilot run, this newly-developed e-learning system had successfully applied for and received a national patent in Taiwan. This independent research hoped to expand the awareness of the importance of individual differences in SDG4 (Substantial Development Goals 4) as a part of the ripple effect, and serve as a comparison for future scholars in the pedagogical research with an interdisciplinary approach.

Keywords: e-learning, educational equity, foreign language acquisition, inclusive education, individual differences, interdisciplinary innovation, learning preferences, SDG4

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Authors: Anita D. Adamu, Winston M. W. Shakantu

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Maintenance management is no longer a stand-alone activity. It has now assumed a strategic position in many organisations that have recognised its importance in achieving primary goals and a key aspect of effective management of facilities. This paper aims at providing an understanding of the role and function of strategic management in creating and sustaining an effective maintenance management system in an organisation. The background provides an articulated concept and principles of strategic management. The theoretical concepts paved way for a conceptual framework for which strategic management can be integrated into the maintenance management system of an organisation to improve effectiveness in the maintenance of facilities.

Keywords: facilities, maintenance management, organisations, strategic management

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Authors: K. L. Wong, I. N. Umar

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Online forum is part of a Learning Management System (LMS) environment in which students share opinions. This study attempts to investigate the perceptions of students towards online forum and their patterns of listening behaviour during the forum interaction. The students’ perceptions were measured using a questionnaire, in which seven dimensions were used including online experience, benefits of forum participation, cost of participation, perceived ease of use, usefulness, attitude and intention. Meanwhile, their patterns of listening behaviours were obtained using the log file extracted from the LMS. A total of 25 postgraduate students undertaking a course were involved in this study, and their activities in the forum session were recorded by the LMS and used as a log file. The results from the questionnaire analysis indicated that the students perceived that the forum is easy to use, useful, and bring benefits to them. Also, they showed positive attitude towards online forum, and they have the intention to use it in future. Based on the log data, the participants were also divided into six clusters of listening behaviour, in which they are different in terms of temporality, breadth, depth and speaking level. The findings were compared to previous clusters grouping and future recommendations are also discussed.

Keywords: e-learning, learning management system, listening behavior, online forum

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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

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Authors: H. Alqunayeer, S. Zamir

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Blended learning, an ideal amalgamation of online learning and face to face traditional approach is a new approach that may result in outstanding outcomes in the realm of teaching and learning. The dexterity and effectiveness offered by e-learning experience cannot be guaranteed in a traditional classroom, whereas one-to-one interaction the essential element of learning that can only be found in a traditional classroom. In recent years, a spectacular expansion in the incorporation of technology in language teaching and learning is observed in many universities of Saudi Arabia. Some universities recognize the importance of blending face-to-face with online instruction in language pedagogy, Qassim University is one of the many universities adopting Blackboard Learning Management system (LMS). The university has adopted this new mode of teaching/learning in year 2015. Although the experience is immature; however great pedagogical transformations are anticipated in the university through this new approach. This paper examines the role of blended language learning with particular reference to the influence of Blackboard Learning Management System on the development of English language learning for EFL learners registered in Bachelors of English language program. This paper aims at exploring three main areas: (i) the present status of Blended learning in the educational process in Saudi Arabia especially in Qassim University by providing a survey report on the number of training courses on Blackboard LMS conducted for the male and female teachers at various colleges of Qassim University, (ii) a survey on teachers perception about the utility, application and the outcome of using blended Learning approach in teaching English language skills courses, (iii) the students’ views on the efficiency of Blended learning approach in learning English language skills courses. Besides, analysis of students’ limitations and challenges related to the experience of blended learning via Blackboard, the suggestion and recommendations offered by the language learners have also been thought-out. The study is empirical in nature. In order to gather data on the afore mentioned areas survey questionnaire method has been used: in order to study students’ perception, a 5 point Likert-scale questionnaire has been distributed to 200 students of English department registered in Bachelors in English program (level 5 through level 8). Teachers’ views have been surveyed with the help of interviewing 25 EFL teachers skilled in using Blackboard LMS in their lectures. In order to ensure the validity and reliability of questionnaire, the inter-rater approach and Cronbach’s Alpha analysis have been used respectively. Analysis of variance (ANOVA) has been used to analyze the students’ perception about the productivity of the Blended approach in learning English language skills. The analysis of feedback by Saudi teachers and students about the usefulness, ingenuity, and productivity of Blended Learning via Blackboard LMS highlights the need of encouraging and expanding the implementation of this new approach into the field of English language teaching in Saudi Arabia, in order to augment congenial learning aura. Furthermore, it is hoped that the propositions and practical suggestions offered by the study will be functional for other similar learning environments.

Keywords: blended learning, black board learning management system, English as foreign language (EFL) learners, EFL teachers

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Authors: Muhammad Abba Jallo, Fred Fudah Moveh

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This study addresses the challenges faced by Nigerian law enforcement agencies due to the lack of an integrated crime management system. While various agencies use ICT-based systems, the absence of interoperability creates barriers to effective collaboration and information sharing. The research proposes the development of an Interagency Crime Management System (ICMS), which integrates the Crime Management Systems (CMS) of different agencies through an Application Program Interface (API). The system is designed to allow all law enforcement agencies to input data using a standardized format, improving crime tracking, reporting, and management across Nigeria. This paper details the design and implementation process, highlighting the benefits of enhanced collaboration for crime management.

Keywords: crime management, Nigeria, law enforcement, ICT

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Authors: Djamel Saba, Fatima Zohra Laallam, Brahim Berbaoui

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This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.

Keywords: communications protocols, control process, energy management, hybrid energy system, modelization, multi-agents system, simulation

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Authors: Chitsuphang Ungsvanonda

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Objective of this research is to study the government’s theater management system regarding planning and operation. Also studying how the management associate with the change of an environment. This is to gather an appropriate model to develop a theater management system especially regarding all show performance. The research will be done by a Qualitative Research with an interview of 35 person by specify and unexpectedly group.

Keywords: management, theatre, social, culture

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Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

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Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

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Authors: Ting Hsiang Chang

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Nowadays in Taiwan, higher education, which was previously more emphasized on teaching-oriented approaches, has gradually shifted to an approach more focusing on students learning outcomes. With student employment rate as an important indicator for University Program Evaluation periodically held by the Ministry of Education, it becomes extremely critical for a university to build up a teaching and learning quality assurance system to bridge the gap between learning and practice. Teaching and Learning Quality Assurance System has been built and implemented at Chaoyang University of Technology for years and has received substantial results. By employing various forms of evaluation and performance appraisals, the effectiveness of teaching and learning can consistently be tracked as a means of ensuring teaching and learning quality. This study aims to explore the evaluation system of teaching and learning quality assurance system at the Chaoyang University of Technology by means of content analysis. The study contents the evaluation reports on the teaching and learning quality assurance at the Chaoyang University of Technology in the Academic Year 2013-2015. The quantitative results of the assessment were analyzed using the five-point Likert Scale. Quality assurance Committee meetings were further held for examining and discussions on the results. To the end, the annual evaluation report is to be produced as references used to improve approaches in both teaching and learning. The findings indicate that there is a respective relationship between the overall teaching evaluation items and the teaching goals and core competencies. In addition, graduates’ feedbacks were also collected for further analysis to examine if the current educational planning is able to achieve the university’s teaching goal and cultivation of core competencies.

Keywords: core competencies, teaching and learning quality assurance system, teaching goals, university program evaluation

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Authors: H. van Rensburg, B. Adcock, B. Al Mansouri

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This paper discusses the impact of pedagogical and learning differences on Arabic international students’ (AIS) learning when they come to study in Australia. It describes the difference in teaching and learning methods between the students’ home countries in the Arabic world and Australia. There are many research papers that discuss the general experiences of international students in the western learning systems, including Australia. However, there is little research conducted specifically about AIS learning in Australia. Therefore, the data was collected through in-depth, semi-structured interviews with AIS who are learning at an Australian regional university in Queensland. For that reason, this paper contributes to fill a gap by reporting on the learning experiences of AIS in Australia and, more specifically, on the AIS’ pedagogical experiences. Not only discussing the learning experiences of AIS, but also discussing the cultural adaptation using the Oberg’s cultural adaptation model. This paper suggests some learning strategies that may benefit AIS and academic lecturers when teaching students from a completely different culture and language.

Keywords: arabic international students, cultural adaption, learning differences, learning systems

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Authors: Takwa Belwakess

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With the wave of the digitization that invades the modern world, communication tools took their place in the world of business. As for organizations, being part of the digital era necessarily involves an evolution of the management style, mainly in processes management, knowing also as quality management system (QMS). For more than 50 years quality management standards have been adopted by organizations to prove their operational and financial performances. We believe that achieving a high-level of communication can lead to better quality management and greater customer satisfaction, which is essential to make sure long-term competitiveness. In this paper, a questionnaire survey was developed to investigate the use of collaboration tools such as Content Management System and Social Networks. Data from more than 100 companies based in France was analyzed, the results show that adopting new digital communication tools while applying quality management practices over a reasonable period, contributed to delivering a better implementation of the QMS for a better business performance.

Keywords: communication tools, content management system, digital, effectiveness, French companies, quality management system, quality management practices, social networks

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Authors: Rosilah Hassan, Karam Dhafer Mayoof, Norngainy Mohd Tawil, Shamshubaridah Ramlee

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Application of adaptive online quiz system and a design are performed in this paper. The purpose of adaptive quiz system is to establish different questions automatically for each student and measure their competence on a definite area of discipline. This model determines students competencies in cases like distant-learning which experience challenges frequently. Questions are specialized to allow clear deductions about student gains; they are able to identify student competencies more effectively. Also, negative effects of questions requiring higher knowledge than competency over student’s morale and self-confidence are dismissed. The advantage of the system in the quiz management requires less total time for measuring and is more flexible. Self sufficiency of the system in terms of repeating, planning and assessment of the measurement process allows itself to be used in the individual education sets. Adaptive quiz technique prevents students from distraction and motivation loss, which is led by the questions with quite lower hardness level than student’s competency.

Keywords: e-learning, adaptive system, security, quiz database

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Authors: Dong Seop Lee, Byung Sik Kim

Abstract:

In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 129

Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

Abstract:

Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

Procedia PDF Downloads 96